International Conference on Computer Networks and Communication Technologies

The operator driving vehicle in night has become a major problem nowadays. The largest number of accidents in the world is due to drowsiness. To overcome this problem, we have developed a machine for a longer period which detects drowsiness and alert the operator. Early detection of fatigued state has become important to develop a detection system. According to the previous work, we found a lot of issues in detecting drowsiness when wearing spectacles and in dark and light condition. In our research paper, we have overcome these issues to detect drowsiness based on the fusion of visual parameters like face detection, eye detection, and yawning in all conditions and wearing spectacles.

Rapid development of automation technology makes people life very simple and easy. In today’s world, all of them depend only on automatic systems over manual system. An IoT-based smart classroom system mainly deals with the automation of electronic appliances in a classroom based on the Internet of Things (IoT) protocol called MQTT. The system architecture is comprised of several wireless nodes, a middleware, and user interface. All the wireless nodes communicate over dedicated or existing network with the middleware. This communication is based on Message Queue Telemetry Transport (MQTT) connectivity protocol which is designed for Internet of things. The MQTT protocol uses publish/subscribe-based messaging on the top of TCP/IP protocol. Through the user interface section, a user can interact with middleware of the system. The interaction is done by recognizing the command of the user through his speech. Mainly, secret commands are used for the interaction with the middleware. Raspberry Pi is the backbone of the system. It operates as a middleware, in the system architecture. Wireless nodes used in this system are called as Node MCU, and this Node MCU is placed in each classroom. After the execution of user interface section, the control is forwarded to the middleware which is placed in the staffroom. Finally, based on the user secret commands, the automation of appliances of each classroom will be done through Node MCU resulting in classroom automation.

Digital repository is a collection of online resources, in order to make web-based repository accessible, we are developing a repository which describes information resources about all the seminar and projects of the students in an educational institutes available on the users on the browser. In this repository it is sectioned into all the departments in an institution, stores the details of the student’s seminars and project reports; hence it would be easier to retrieve the information available on the college website. Basically students and professors do not have time to go to the library or to their respective department to check out every citation. We need a system which deals with both the information overload problem, and difficulties in obtaining copies of the published works. We are incorporating few features in this project to meet the needs using eclipse IDE and tomcat server.

Plenty of algorithms are available for datamining. LP-Growth occupies an important place in data mining. LP-Growth algorithm constricts data required for mining frequent itemsets in LP-tree and recursively builds LP-tree to mine entire frequent itemsets. In this study, an algorithm of top-down linear prefix tree (TD-LP-Growth) is proposed for mining frequent itemsets. The proposed TD-LP-Growth algorithm searches LP-tree from top to down order which is opposite to the old LP-Growth algorithm. TD-LP-Growth does not generate conditional pattern base and conditional LP-tree. Thus, it improves the performance of proposed TD-LP-Growth algorithm. In this paper, the benchmark databases considered are Online shopping dataset 1, Chess and Mushroom. While using online shopping dataset, the frequent purchaser of the dataset is visualized using Google map in geographical method. From the experimental results, it is concluded that the proposed TD-LP-Growth algorithm consumes lower runtime and memory space during the process of mining. Thus, the proposed TD-LP-Growth algorithm outperforms LP-Growth algorithm in mining frequent itemsets.

In a Wireless Sensor Networks, localization techniques are needed to identify the exact position of an event. In this paper, we proposed Fuzzy Inference System (FIS) based target localization algorithm in a three-dimensional wireless sensor networks. In the proposed scheme, distance between anchor and target nodes are calculated by adding correction factor with hop size of an anchor node. The concept of fuzzy logic-based edge weight calculation is introduced to improve the localization accuracy. Simulation result shows that proposed scheme achieves less localization error and better accuracy as compared with existing localization technique.

Green energy efficiency technology provides environment-friendly approach towards mobile communication. In order to achieve this energy efficiency, we considered renewable energy resources and efficient use of eNB (BS) in our work. We designed an optimal eNB ON/OFF operation and renewable resources like solar and wind energy to reach the effective energy and power consumption. The eNB’s active/idle state is identified by measuring the responder frequency. We proposed a unique algorithm to carry out the switching between eNB by considering number of users as load. The potency of our work is endorsed by simulation results and to control the pollution by mainly reducing the CO2 in order to reduce the global warming.

Social Network (SN) is an online platform broadly used as communication tool by millions of users in order to build social relationships with others for knowledge point of view, career purposes and many more. Social Networks such as Twitter, Facebook, and LinkedIn have become the most leading tools on the web. Spam, floods the Internet with many copies of the same message and it can be manifest in numerous ways, it includes bulk messages, malicious links, fake friends, fraudulent reviews and personally identifiable information. The aim of this paper is to classify the tweets into spam and non-spam using Machine Learning and which will give the best results.

Cloud computing is a growing trend which provides us less cost with many types of facilities like resources of maximum, elasticity, dynamic resource provisions, and self-service providing to the user on an Internet. Cloud offers a huge and vast platform in allocating and provision of resources to the user with less computing speed and makes it very easy to use. Resource allocation and provision is done based on the quality of service in an effective manner, but it lack with certain cases of dynamic resource provision, many of the works done are based on resource management and utilization with high cost and speed. But our proposed method wills effectively management in allocation the resources with less time dynamically based on the available of the resource and manage it very effectively, effectiveness is based on low cost and high utilization of resource. Our aim is to allocate the resource in peak time and control it very effectively in managing the resource. The proposed algorithm will analyze and allocate the resource in based on various policies and is compared with the others.

Mobile Ad hoc Networks (MANETs) have no centralized infrastructure; they are dynamic in nature. A node can act as a host or a router and can freely join or leave the network any time. The challenges in creating MANETs are mainly because of their limited physical security and energy constraints. As most of the nodes are battery operated their energy gets drained rapidly. This paper presents a modification of the existing AODV routing protocol called M-AODV. AODV uses the HELLO packets to discover and maintain the neighbors; we have added two new parameters in HELLO packet that is Trust and the Willingness (based on the remaining battery of the node). The intermediate nodes for routing packets are selected based on these two parameters. NS2 simulator is used for analyzing the performance of the protocol in terms of throughput, PDR, Packet drop, and routing overhead. All the performance parameters for the proposed algorithm were compared with the regular AODV and the results for M-AODV compared to AODV are better.

In current era, online social networking performs an important role in content sharing. Information diffusion takes place very rapidly through social network. There are so many positive and negative impacts for information spreading. An Internet meme is a unit of information, which is copied and spread very fast in internet, may be with slight variations. This movement will spread from person to person via social networks. In this paper, we put forward a method for predicting the virality of meme in future. The data collected from Twitter and machine learning algorithms are used to predict the virality.

Underwater Acoustic Sensor Networks (UASN) have different applications such as oil platform monitoring, earthquake, tsunami forewarning, water pollution tracking, etc. In UASN, localization is the fundamental step to make the sensed data meaningful and the localization is performed after random deployment of nodes. It is useful in different ways such as node tracking, target detection, etc. Existing works do not consider the ocean current drift during node localization. In this paper, node localization in UASN is achieved by incorporating the ocean current drift for the sensor nodes. As underwater environment is usually complex, the Meandering Current Mobility (MCM) model is considered as the ocean current model and the unlocalized node position is estimated using Dive and Rise Localization method with Distance Vector Hop algorithm. Aquasim software is the simulation tool used to implement the UASN model. Simulation results indicate that the proposed localization method incorporating the ocean drift model outperforms the existing localization scheme in terms of packet delivery ratio, delay, localization ratio, and coverage.

A continuous time model called Air Quality Data-Model was developed to assist air quality measurement in urban areas. This model can be utilized in several large areas to estimate the Air Quality parameters for measurement of pollinations in urban area because of urbanization. The model can used to predict the air quality for upcoming time of interval for the city. This work is pertaining to Surat Urban area which includes southern part of Tapti River and Arabian Sea to its western coast. The predictive model developed for the air quality monitoring based on training model. This predictive model will present the forecasting of the air quality measurement of the upcoming years.

Cloud computing technique is most generally used technique nowadays, in that clouding up is completed over giant communication network. And provides massive space for storing in all sectors like administrative unit, private enterprises, etc. Additionally stores personal information on cloud, but the foremost necessary drawback in cloud is that giant quantity of space for storing is needed and conjointly duplicate copies of knowledge is store on cloud. There is a unit of several techniques that is employed for preventing duplicate copies of continuation information. The necessary technique is data deduplication, Data Deduplication is specializes data compression techniques for removing duplicate copies of repeated data and has been widely utilized in cloud storage to reduce the quantity of space for storing. To safeguard the confidentiality of sensitive data on cloud, the confluent encryption technique is utilized to cipher the data before storing it on cloud. In projected system we have used Shamir Secrete sharing algorithm.

Forecasting of future rainfall from previous years data samples has always challenging and major area to focus. There are various factors are applied to anticipate the rainfall such as Mean sea-level, temperature, pressure, wind speed, humidity, etc. We have inaugurated a strategy for predicting the average ground rainfall over the districts of Karnataka state from the past rainfall data applying modified ANN approach without conceiving the rainfall parameters, but considering the average rainfall rates of the previous years and primarily focus on optimization techniques to reduce the error rate during training process. The proposed approach predicts the average rainfall of next consequent year, on inputting anyone year’s rainfall data of any districts taken into account. The suggested technique is implemented in MATLAB and the results are tested.

The modern world had been dominant to the automation applications. We can see that the smart applications are being leveraged significantly. The deployment of Smart watch, Smart Cars, Smart Homes are the common examples that can be referred to automation. The core of the automation technology lies in the domain of Wireless Sensor Networks referred as WSN and the Internet of Things, i.e., IoT. The prominent part or the concept in the technology is the sensors. The common name for this sensors are nodes in common network terms. The major consideration in any of the sensor networks or the IoT environment is the energy availability at each nodes. Therefore the minimal energy consumption by the nodes of the network or the energy consumption factors are highly observed. The nodes are also supposed to perform immediate regrouping of the network whenever the nodes die. In this paper, the behaviour of the low power protocol called 6LowPan abbreviated as IPv6 over Low-Power Wireless Personal Area Networks is analysed under various topological scenarios. Cooja Contiki simulator is the tool used in for the simulation purposes of the 6LowPan.

Indoor positioning system is a challenge for most military operations because conventional technologies like GPS do not work in indoor conditions. Also at this point in time there is no proven technology that is globally accepted that provides indoor navigation and positioning. In this project a indoor positioning system based on a combination of technologies and features is proposed that can provide the best possible solution to this requirement. This project uses a combination of 3D accelerometer to provide information about the movement of the person. A 3D 360° Digital magnetometer which provides information about the direction of movement. A Gyroscope which provide information about the person’s orientation and finally a barometric pressure transducer that uses atmospheric pressure as reference to calculate the height or elevation of the individual. Thus using these multiple inputs and a slew of processing and calculations can provide information about the movement and location of a person in 3D space additionally this information can be transmitted using wireless communication technologies to keep track of the respective position on soldiers inside a building where GPS and other conventional technologies do not work. If every soldier is provided with a device like this then a military operation can be coordinated easily from a remote location by knowing the respective location of all the soldiers. The location of various soldiers can be plotted on a software like LabVIEW on a remote computer terminal in a control room away from the danger zone.

Demand Forecasting, undeniably, is the single most important component of any organizations Supply Chain. It determines the estimated demand for the future and sets the level of preparedness that is required on the supply side to match the demand. It goes without saying that if an organization does not get its forecasting accurate to a reasonable level, the whole supply chain gets affected. Understandably, Over/Under-forecasting has deteriorating impact on any organizations Supply Chain and thereby on P and L. Having ascertained the importance of Demand Forecasting, it is only fair to discuss about the forecasting techniques which are used to predict the future values of demand. The input that goes in and the modelling engine which it goes through are equally important in generating the correct forecasts and determining the Forecast Accuracy. Here, we present a very unique model that not only pre-processes the input data, but also ensembles the output of two parallel advanced forecasting engines which uses state-of-the-art Machine Learning algorithms and Time-Series algorithms to generate future forecasts. Our technique uses data-driven statistical techniques to clean the data of any potential errors or outliers and impute missing values if any. Once the forecast is generated, it is post processed with Seasonality and Trend corrections, if required. Since the final forecast is the result of statistically pre-validated ensemble of multiple models, the forecasts are stable and accuracy variation is very minimal across periods and forecast horizons. Hence it is better at estimating the future demand than the conventional techniques.

Digital twin will gain new insight in sports domain. It will not only help to connect and monitor sportsperson virtually in a lab but also help to simulate actions, movements in the ground and play shots which recommend coach and trainer to redefine the game strategy on the fly or even half time or break during the match.

The number of connected things or devices will be 125 billion by 2030 as per IHS market survey. It indirectly translates that large number of users will be accessing these devices for collecting, controlling, monitoring and building edge analytics. The device management policy and data policy on accessing data from different resources needs proper governance and control. The data security will help these users to assure regulatory compliance, security, privacy and protection. This paper is a centralized data security management across different layers of Internet of Things along with rule builder. Mainstream of this study focusses on compliance standard, identity management, data management and policy engine and audit reports. The specific regulatory compliance, security standards or firmware or hardware security and vulnerabilities at IoT layer has not been captured in this paper.

The paper proposes a user location-based dynamic radio resource allocation in MIMO-OFDMA systems to mitigate Inter-Cell Interference (ICI) using evidence theory. In order to utilize the limited radio resources like subcarrier and its associated power efficiently, it is needed to develop a scheme. In cellular communication, for better utilization of resources, if the radio resources are repeatedly used in the neighboring cells, it leads to ICI. In order to address this issue, a two-step resource allocation technique is devised. In the first step, the evidence of the user in a cell is calculated in order to categorize the users as Cell Edge Users (CEU) and Cell Center Users (CCU) and in the second step, the dynamic allocation of radio resources is carried out. The criterion for resource allocation is the frequency of occurrence of a user evidence in a cell. It increases the datarate and efficiency of the system.

Phishing is considered as a form of the Internet crime. To detect a phishing website, human experts compare the claimed identity of the website with the features of the website along with its content. Every website URL has its own lexical features like length, domain names, etc. The phishing websites may appear to perform the same activities of another website but the content of the two websites will be different. In traditional networks, a proxy server handles the URL requests and determines whether an URL is malicious or not. In this paper, URL filtration is incorporated into an SDN framework as a security application. The proposed system uses deep packet inspection and machine learning techniques at the controller and the rule installation in the switches for efficient URL phishing detection. The phishing system analyzes the lexical and content-based features of the URLs. Based on the categorization, the rules are formed and installed in the switches. The performance of the system is evaluated based on the response time and accuracy in the detection of phishing URLs using a simulation framework.

SDN is a recent blooming architecture which provides greater flexibility for the network professionals. SDN decouples the control logic from the forwarding devices, and the centralized controllers decide the forwarding rules in the network. In spite of the flexibility provided, it is vulnerable to many kinds of attacks. Our focus is on mitigating the denial-of-service attack on flow tables which can result in severe degradation of the network switches. In order to address this issue, we propose a path randomization technique and flow aggregation algorithm. The performance of the system has been evaluated in a simulation environment which has shown a positive result.

This paper deals with smart home which caters for the comfort of citizens. Smart homes are those where household devices/home appliances could be monitored and controlled remotely. This aims at controlling home appliances via smartphone and voice by using Alexa acting as a client. Local network created by home router or cloud is used for monitoring and controlling of the connected devices such as LEDs, fans, motors, dimmers, PWM devices, etc. System consists of devices connected to a central hub called a “gateway” from which the system is controlled with a user interface which is provided by the Android application or through Alexa. The communication between the devices and gateway takes place through Power Line Communication (PLC) and the RF links either through TCP protocol or Message Queue Telemetry Transport (MQTT) protocol.

In this paper, a modular architecture for Internet of Things (IoT) based on an agricultural setting for data acquisition and mining is proposed, developed, and implemented for validation. This work is an attempt to modularize the general IoT architecture and separate functional layers to make them independent of each other. The purpose of the presented solution is to make development and deployment of IoT systems, easy and cost-effective in agriculture to accelerate the adoption of precision agriculture. The architecture involves four functional layers: things layer (sensors, controllers, and actuators), edge computing layer (microcomputer), gateway layer (Wi-Fi Modem/Broadband), and cloud layer (Database, web application). The local machine-to-machine communication between things layer and the edge computing layer uses a high-level implementation of the message queue transport telemetry protocol.

The advanced development of the wireless sensor today is termed as the “smart sensors”. The smart sensor in the field of agriculture is one of the new levels of developing factor in artificial intelligence system. The smart sensor in the field of agriculture is a need for country which is having a water scarcity, as well the growing countries that take the irrigation to the next level with the help of technology. This motivates an enormous attempt in the research activities of the irrigation field, standardization, and investment in the field of agriculture for the better management of the water resources. This survey paper aims at reporting an overview of sensors Saturas on miniature SWP technology for irrigation, major applications, and also provides the features of the Saturas, designs, and a case study based on a real implementation is also reported. Trends and probable evolutions are traced based on the agro-sensors for irrigation purpose.

Shared computing resources in a pool enable various services that accessed over Internet for storing large company data. It has reduced the cost and infrastructural needs but there is a concern for data safety and integrity. The existing remote data auditing technique integrates the application of algebraic signature properties of a cloud and new architecture, and divides rule table to allow users to carry out data manipulations quickly. However, majority of the auditing techniques are done on static dataset and also incurs a computational overhead when data size increases. In this paper, dynamic data updating which is a pivotal function in data auditing is used. To reduce the overhead and increase the computational efficiency, the proposed system uses MongoDB. This enables the system to be scaled to larger files and also reduces the computation time elapsed in identifying updated data by using JSON format of stored files in the database. Additionally, the security concern and client’s overhead are minimized by using RSA signatures to conserve the confidentiality of the data uploaded by the cloud consumer. The auditor quickly and efficiently scans only the updated data block for any viruses or malware, thereby reducing the cost and computational power requirements of the third-party auditor and also improves the overall speed and efficiency, encouraging more people to approach the cloud space with trust.

Smart home networks today span from technological advances that introduced highly networked devices of high density to applications which are more vulnerable due to its increasingly invasive nature to personal space and data. Such networks are becoming susceptible to multiple types of attacks that are seen today with a high number of third-party framework vendors in increasing risk of malicious attack. In such scenarios, dynamic- or context-aware authentication may provide a reinforced measure that takes into account environmental changes or behavioral changes in the network to enable the administrator in the decision-making process. The following work intends to explore a methodology in the incorporation of context-based processing that attaches the context-based filtering intelligence deep within the IoT network at the data processing center.

Virtual Cellular Network (VCN) is a mobile communication network which is wireless in nature. This communication network includes one Mobile Station (MS) which has the provision of communicating with many (more than one) Base Stations (BSs) at the same time. One of the inherent properties of VCN is that when the mobile station sends a signal to the base station, the base station receives it, thereby reducing the probability of outage that could be caused by shadowing. A mobile station is in continuous and parallel communication with two base stations during the phase of handing over. This communication is achieved by communicating the same data of downlink from the two base stations to the mobile station. When such a downlink data of a single mobile station is shared over multiple base stations, higher bandwidth efficiency is achieved in full virtual cellular network implementation. The VCN also gives the provision that will enable many base stations to receive the signal from one mobile station, thereby setting an environment to improve the reliability of satellite communication. In the proposed scheme, distributed multiple access protocol is used and simulation of this protocol is done using stationary users and mobile users. Every BS is considered to be a separate object which is linked by a simulated backbone which is wired. The simulator used is a time-based simulator where all the base stations are synchronized to one common clock. This paper presents the evaluation of multiple access protocol in combination with link protocol. The proposed work can be a contribution toward the design of multidisciplinary Mobile Multimedia Communications (MMC). The proposed scheme aims to support Asynchronous Transfer Mode, Internet Protocol (IP), and also a support for inexpensive mobile stations.

Healthcare monitoring system is introduced to reduce the daily visit of patients to the hospital. The patients can collect their vital parameters and send those measured values to the doctor or hospital. Healthcare monitoring system introduces the real-time monitoring of vital parameters of the patients such as collecting all the information from the patients and sending it to the web server. The authorized person can log into his account and see the patients’ vital parameters. These vital data can be stored and analyzed for further decision-making and analysis. By identifying the pattern of the vital parameters which is observed, the nature of the disease can be predicted. The system collects patient’s body temperature, oxygen saturation percentage, heart rate, blood glucose, and blood pressure using Raspberry Pi board and cloud computing. The communication protocol used in the system is AMQP protocol. It supports reliable communication via message delivery guarantee primitives including at-most-once, at-least-once, and exactly once delivery. The collected data from various patients could not be handled easily by the physician. The main concern of the physician is that he should take the critical decisions about their patient’s health from this huge volume of health information. The huge amount of information can be stored in cloud and the data can be analyzed using data mining.

In current scenario of automotive industry, Vehicular Networks are providing enhanced support to improve driver security and efficiency. But still, security is an essential requirement in vehicular ad hoc networks since VANET packets contain life critical information. A rogue node can transmit fake messages to their neighbors. In this paper an effort is made to explore an environment with simulated Sybil attack and its effects on network performance. We propose an efficient and scalable data centric approach based on the comparison of average flow rate or mobility information exchanged between the vehicles in the network. Our approach does not require any help from the infrastructure during attacker detection. Simulation results show the effectiveness of the proposed system to locate rogue nodes and inform their peers to avoid communication with them, by checking a Boolean flag. So the proposed system will make VANETs more fault tolerant and robust against transmission of fake messages.

Maximal Frequent Patterns can be mined using breadth-first search or depth-first search. The pure BFS algorithms work well when all maximal frequent itemsets are short. The pure DFS algorithms work well when all maximal frequent itemsets are long. Both the pure BFS and pure DFS techniques will not be efficient, when the dataset contains some of long maximal frequent itemsets and some of short maximal frequent itemsets. Efficient pruning techniques are required to mine MFI from these kinds of datasets. An algorithm (MFIMiner) using Breadth-First search with efficient pruning mechanism that competently mines both long and short maximal frequent itemsets is proposed in this paper. The performance of the algorithm is evaluated and compared with GenMax and Mafia algorithms for T40I10D100K, T10I4D100K, and Retail dataset. The result shows that the proposed algorithm has significant improvement than existing algorithms for sparse datasets.

Pollution occurs at an unprecedented scale around the globe. Among various types of pollution, air pollution is a major threat to life and ecosystem as a whole. This paper presents the application of the Internet of Things to model a smart environment by developing a user-configurable air pollution monitoring device. This user configurable device monitors air pollution, collects location coordinates and send the collected data along with the location to an online Internet of Things platform called ThingSpeak. The Public can make use of the information in this platform. This device consists of sensors, Raspberry Pi 3, and GPS module. User configurability is achieved by developing a Bluetooth-based Android application thereby making the device more flexible.

In this fast-paced environment, people often forget to take medicines on time, which is highly essential for one’s health. The presence of this situation is more in senior citizens. They even have problems using e-commerce websites. Smart HealthCare System is a permanent and long-term solution for elders to organize their medicines and take care of their health. This product reminds them at right time and also maintains the summary of intake of pills. Both doctor and caretaker can monitor the medicine intake of the patient. It also aids the patient to order medicines online in an easier way which also provides the provision for separately programmed pillboxes. Customers can schedule an appointment with the doctor. No-stock feature is available in this system which reminds the user about placing an order. All the features are regulated by a portable CPU (Raspberry Pi) which is connected with the system and Android app. Orders are confirmed via Android app and pharmacist handles them by using the e-commerce website. The user can simply order medicines by a single click of a button and also differentiate all medicines.

A comparative study with simulation has been carried out in this paper to choose a combination of routing protocol with the suitable TCP variant for video transmission over mobile ad hoc networks. Simulation is carried out to choose a routing protocol out of AODV, AOMDV, DSR and DSR protocols for ad hoc networks that suit the need of ad hoc scenario. AODV protocol is found to perform better than other routing protocols. Performance of TCP variants such as TCP Reno, TCP NewReno, TCP Tahoe, TCP Vegas, and TCP Sack is then compared for the video transmission in ad hoc networks by adapting AODV as routing protocol. The simulation results show that TCP Vegas with AODV gives good performance.

Cloud computing is forthwith educing like nevermore heretofore, with companies of all shapes and sizes mending to this neoteric technology. Industry experts accredit that this fantasy will only abide to grow and flourish even further in the forthcoming few years. Cloud services are bestowed by profuse clients. There are umpteen services in cloud, and clients without any erudition about the quality traits of cloud services modestly utilize the service and feel mournful, depressed if the essence of service quality is not congenial. Cognition of quality characteristics of cloud services is very important for clients to use cloud service and to feel ecstatic, satisfied by utilizing cloud service. In this paper, by exerting proximate technique and clustering technique, cognition of quality traits of services in cloud is achieved, which can be exerted by forthcoming consumers and cloud service clients. In proximate approach method, the quality traits of each cloud service are computed with the help of stewards. A lot of security predicaments may eventuate while taking input for proximate approach. The security predicament is resolved by exerting ultimatum response method and miscegenation cryptography method in this paper. The output of proximate approach is taken as input to proximate fuzzy c-means (PFCM) clustering. In clustering approach, the services of cloud are clustered based on quality ranking traits calculated in proximate approach. The output of clustering which is based on quality ranking traits of cloud services is bestowed to forthcoming clients with the help of stewards, so that the clients by scrutinizing clustering approach can use the cloud service with the quality trait they fascinate among accessible cloud services. Service patrons can also emend their quality of service by scrutinizing the clustering output if their quality of service of a service patron is not sterling.

Mobility is becoming a very significant theme in cognitive radio networks due to unlimited access to the network. As a result of using IPv4 protocol, there is a problem of data loss, if the user moves from one network to another. The 802.16e standard was developed for future supporting mobility and IPv6 protocol is mainly designed to support mobility and end-to-end security. So, we propose a protocol Ipv6 and integrating mobile TCP with 802.16e standard, which allows the users to roam over the network seamlessly and securely.

Dimensionality Reduction is one of the preferred techniques for addressing the problem of the curse of dimensionality associated with high-dimensional data. At present, various significant research works have been already carried out toward emphasizing the dimensional reduction methods with respect to projection-based, statistical-based, and dictionary-based. However, it is still an open question to explore the best technique of dimensional reduction. Hence, we present a compact summary of our investigation towards finding the contribution of existing research methods of dimensional reduction. The paper outlines most frequently adopted techniques of dimensional reduction. At the same time, this survey also emphasizes on exploring the problems addressed by the present researchers with an aid of their own techniques associated with both advantages, limitations, and addressing the issues of the curse of dimensionality. The survey also introduces the latest research progress and significant research gap associated with the existing literature.

Ambulatory health care is a type of remote patient monitoring that allows a medical caretaker to use the medical device in the ambulance to perform a routine test and send the test data to a healthcare professional in real time. Even though there are various methods to observe the health condition of the patient at home or in the hospital, the necessity of the quick measures to treat the person in case of emergencies are not yet fulfilled. If the person suddenly falls ill and is being carried to the hospital, the doctor will get to know the condition or the cause of the illness only after diagnosing the patient which will consume more time. There is a need for monitoring technology in ambulances since in case of emergency lots of time is wasted in carrying patient to the hospital and diagnosing. To overcome this problem, online system for remoting health parameters of a patient in the ambulance is proposed in this paper . The experiment is conducted to compare the system values with the values obtained by the standard devices and the results are in a good format and the system is efficient.

Research shows that there are few GSM channels available for the assignment of control channels and remaining channels dynamically are available for service as secondary channels users of CR network. For the design of CR-OFDM in 900 MHz GSM band, it is necessary that the channel shall be considered as frequency selective and time variant within the scope of practical limits. The OFDM parameters need to be calculated within the availability of vacant GSM bands, that is, 200 kHz which is very narrow in comparison with the existing bands deploying OFDM technology that is above and in multiples of 1.25 MHz. The results have been obtained and compared using three methods: (a) Measurement of OFDM efficiency at 2600 MHz band and GSM spectral efficiency at 900 MHz band both at Chakan, Pune to ascertain the geographical location. This will help to map 2600 MHz data to 900 MHz band for OFDM. The Atoll planning tool is used with the same geographical location parameters at 2600 MHz OFDM technology and is validated with the obtained results. The GSM 900 MHz RF parameters were used for simulation of Atoll parameters using OFDM technology, (b) Parameters pertaining to frequency selective and time-variant channel, viz., coherence bandwidth and Doppler delay were calculated based on the practical data available for Indian Geographical locations and matched with the ITU Table for same parameters. The OFDM parameters for GSM 900 MHz band with 200 kHz bandwidth was calculated subject to the limitation imposed by OFDM technology. (c) The obtained result was verified using Atoll planning tool and finally, the spectral efficiency was calculated. Although OFDM subcarriers are very low in size to combat coherence bandwidth, not much research work has been done to use OFDM technology for narrow bandwidth. The present work shows the design of cognitive OFDM system for frequency selective and time-variant channel in 900 MHz GSM band. The suggestions are based on the calculation done and the design has been verified using data collected for live network and results are summarized on the basis of adaptive CP length, finally, the result has been calculated using three methods, i.e., from live network, from mathematical calculations, and from Atoll tool has been summarized.

Ad Hoc network is a collection of wireless devices (nodes) forming a temporary network which has any established infrastructure or centralized administration. These devices have the ability to move which means that the topology of Ad Hoc network changes according to the mobility of nodes. In order to maintain the connectivity between nodes in Ad Hoc network it is necessary that mobile nodes work together. Many routing protocols have been proposed to keep the connectivity between nodes, including the AODV protocol (Ad Hoc On-Demand Distance Vector), which is maintained as a standard by the IETF. This protocol has limitations in terms of stability of links between nodes. To overcome these limitations, we proposed an improvement of AODV protocol to find stable links, which endure between source and destination. Our idea is based on the quality of the received signal strength between the different nodes. In this article we proposed a new strategy of finding routes and predicting ruptured links. The results of simulation and comparison with the standard version of AODV show the effectiveness of our propositions.

This paper proposes a prototype for multi-level secured PIN (Personal Identification Number) entry authentication. This system is based on ARM microcontroller in which Stegano PIN method is implemented. If in Emergency situation to withdraw amount, owner of an ATM card gives it to a third party, there is possibility to withdraw extra amount. Moreover even if a user is directly accessing the ATM machine there is a possibility of shoulder surfing to track PIN number. To achieve security and usability, a practical indirect PIN entry method Stegano PIN is designed and implemented. A random key is generated using the Stegano pin method in the keypad matrix each time the card is inserted. This prevents the shoulder surfing attack. If the card is given to third party, the card owner will send a message to the server placed in the ATM machine specifying the amount limit for that card number. If the third party tries to withdraw extra amount the ARM processor will process only the amount specified by the owner through the message from the GSM. The extra amount entered by the third party is not processed by the ATM machine. Thus a highly secured and user-friendly system is developed and tested.

In recent communication systems, Direct Digital Frequency Synthesizer (DDFS) plays dominant role in signal generation. DDFS is highly stable and highly controllable circuitry. DDFS requires read only memory (ROM) for signal generation, but usage of high ROM size leads to high power consumption and more hardware requirements. In this paper, on utilizing a quarter wave symmetry technique and storing the difference value between consecutive segments in ROM Look-up table (LUT) is proposed. The proposed architecture has reduced ROM size with beneficial effects in terms of speed and power. For 8-bit resolution SNR is of 44.92 dB and SFDR is of 50.64 dBc.

In today’s prospective and perspective nature optical communication and networks have been emerged by means of Fiber Distribution Connectivity (FDC), Optical Relocation Mechanism (ORM), Optical Link Path Assortment Approach (OLPAA) and System Survivability Network Integrated Approach (SSNIA). Further it can be enhanced in the direction of Link Layer Traffic Connectivity Protocol Applications and Mechanism (LLTCPAM) is enlightened in our paper. In future course demand queuing is a versatile factor, it will be used as a resource facility for the users hence the different mechanism such as Parcel List Algorithm (PLA) have been analyzed in order to compare the Network Connectivity Parameter (NCP).

Internet of Things is the one based on data analytics and the competence to gain an accurate and deep understanding about the sensors. Security is the most crucial and vital need for developing IoT Communication wireless network. Classical Cryptography has provide a way to ensure the fundamental needs of communication networks but the security is not to the optimal level and the downside may be dealt by Quantum technology. To constrain these insights, IoT applications depend on neural networks and machine learning to extract Knowledge data based decision support. The DORBRI architecture proposed in this paper addresses the issues that are faced by the cryptosystem through the Post-Quantum cryptography based Quantum IoT. The block chain allows us to ensure the soundness and permanence of the information since you cannot modify or capture data without that particular action get recorded. Communication over the proposed secure channel will be faster and considerably reduce the loss of data.

In today’s world, the most popular method of utilizing the public-key cryptosystem for secure communication between users is through a public-key infrastructure (PKI). But this infrastructure is time consuming, error prone, not user friendly as it requires authentication of public key using a valid Certifying Authority (CA). The most suitable alternative to PKI is ID-Based Cryptosystem (IBC). It is faster, secure, and user friendly as the public keys are constructed using the unique IDs of the registered users in the system. This infrastructure does not require a CA for ensuring public-key validity, thus speeding up the cryptographic procedure. However, the overall time consumed by the IBC algorithm can be significantly reduced by parallelizing. In this article, we have implemented Boneh–Franklin’s IBC scheme using bilinear pairings. We have parallelized the decryption phase, thereby reducing the total communication time. The performance result of the parallelization is recorded in tabulated form as well as graphical form.

The selection of cluster heads in a wireless sensor network (WSN) is a very challenging area of research. Many algorithms have been proposed for the selection of cluster heads to prolong network lifetime, but maintaining an energy efficient network remains a problem. To overcome this, we propose a new algorithm for cluster head selection based on the Spiritual Energy of the whole WSN, which is known as the SEER (simple energy-efficient reliable) protocol. In addition, the implementation of the double tier fuzzy algorithms on the SEER protocol makes the network more energy efficient. The proposed algorithm has been simulated with MATLAB and compared with the other energy efficient algorithms such as CLERK and LEACH. The results proved to be very promising in terms of the reduction of energy consumption.

Printed antennas are most suited for aerospace and mobile application due to their inherent characteristics namely low profile, reduced weight, less difficulty in fabrication and integration. Regardless of these advantages, they suffer from narrow bandwidth, less gain, and poor directivity. In this project, to design a microstrip planar antenna for 2G, 3G, 4G, and 5G mobile communication applications. The multiband antenna design should be highly directive and should have high gain. The antenna should resonate at 0.924, 1.88, 2.112, 3.4, and 3.844 GHz. The multiband antenna so designed can be adaptively used for mobile communication application, as the antenna so designed satisfies the gain and VSWR requirements along with radiation pattern and can also be used for RF Energy harvesting, which is being studied and to be designed in the future.

In this paper, a dual-mode microstrip bandpass filter is designed employing Peano fractal geometry. The filter design uses the square patch with a perturbation element added at the corner of the patch for dual-mode configuration. The proposed bandpass filter structure has been designed based on the second iteration Peano fractal curve at 2.45 GHz using two substrates (RT/Duroid 6010 and FR-4) and their performance is simulated for return loss and insertion loss. The design process is continued up to second iteration of Peano fractal in order to achieve the center frequency at 2.4 GHz, which can be used for WLAN applications. The comparison is made on the simulation results of the proposed fractal filter between the two substrates.

This paper provides a detailed explanation of a system that aims at detecting and capturing the movements of people in the proximity of a door, using Internet of Things (IOT). The door will be able to sense the movements of people within a predefined range. Once the movement is sensed, an attached camera will click a high quality image of the person. The image will be uploaded to the cloud in real time and transmitted to the owner’s phone which will appear as a push notification on a custom application. The owner can view the incoming image and decide the future course of action, which may include sending back a prerecorded message, talking to the visitor over the phone, or setting off an alarm in case of suspicious activity. It can also interact with other appliances inside the home to pretend that someone is there. This system can be a great tool in crime detection and prevention.

Notice board is an important thing in any institution. But sticking various information on notice board is a tedious process. A separate manpower is required to take care of that traditional notice board. In this paper, we are using an electronic LED or LCD display to display the notices on our campus. In this electronic bulletin board, we are displaying both the text and multimedia messages entered by an authenticated user. The authenticated users can also delete the messages whatever they entered in the bulletin board. The messages entered by an authenticated user is displayed on e-bulletin board by using the HTTP protocol.

An Augmented Line Segment-Based (ALSB) algorithm with delayed overlap consideration is proposed for the construction of Rectilinear Steiner Minimum Tree (RSMT). The algorithm incrementally augments the four line segments drawn from each point in four directions. When the line segments of two points interconnect, the edge connecting those two points is included to RSMT. The selection of the L-shaped layout is done after all the edges are identified. After the RSMT edges are selected, the two layouts of each edge are compared based on overlap count, and the layout with maximum overlap is added to RSMT, thereby reducing the total length of RSMT. RSMT has wide application in the field of VLSI during global routing.

Nowadays, the road accidents in modern urban areas are increased to uncertain level. In highly populated countries like India, more than 410 people get swooped up every day. A leading cause of the global burden of public health and fatalities is road accidents. The loss of human life due to accident is to be avoided. There is no technology in current times for detection of accident. Reaching of ambulance to the accident location is mostly delayed due to the conjested traffic that increases the chance of victim death. To reduce loss of life or save life of person due to accidents and reduce the time taken by ambulance to reach the hospital, there is a need of system which needs to come into force in our daily lives. To bar loss of human life due to accidents, we introduce a scheme called automatic accident rescue system (AARS). There is an automatic detection of accident by crash sensors in the vehicle. A GPS module in the vehicle will send the location coordinates of the accident using IoT platform to central unit which will notify and send an ambulance from the nearest hospital in the vicinity to the accident spot. This scheme is fully automated; thus, it finds the accident spot, helping to reach the hospital in time. This system can help in reducing the loss of lives of human which happen by the accident.

Data clustering is the most important technique in knowledge discovery and data engineering. Recently, the possibilistic C-means algorithm (PCM) was proposed to address the drawbacks associated with the constrained memberships used in algorithms such as the fuzzy C-means (FCM). Among different variations of clustering, possibilistic C-means (PCM) uses constrained membership functions. But the drawback of PCM converges to coincident clusters. The purpose of this paper is to overcome the drawback of PCM while preserving the privacy of sensitive data. The proposed algorithm in this paper is tensor PCM (TPCM), which makes use of tensor relational data model. TPCM algorithm is further modified as privacy-preserving TPCM algorithm to preserve the privacy by using Brakerski–Gentry–Vaikuntanathan (BGV) technique.

The main idea of smart login system is to provide security to our beloved things, places, libraries, institutions, etc. To keep our data safe or to avoid them being stolen by third party, we use smart login. Nowadays, it is essential to protect or secure our things or valuable data and even money. This system is based on biometrics that is fingerprint template to unlock the door which provides security to many banks, institutes, and various organizations. The door lock system using biometrics interfaces with a biometric reader that is fingerprint scanner and a door lock that will secure a room or environment. This system is a replacement for keys, locks, and cards. This system consists of fingerprint scanner, Arduino board, magnetic solenoid lock, and LCD to unlock the door. Kiel compiler is used in the programming to interact with the fingerprint reader for triggering purpose. With this system, securing access will be provided while providing convenience and efficiency. If the fingerprint template which is authorized matches, then the door lock opens, otherwise it remains in closed state.

We are in the middle stage era of the digital revolution where all consumers and businesses demand decisions to be based on evidence collected from data. The challenge of big data is mainly well defined in the health and bioinformatics space where, for example, whole genome sequencing (WGS) technology leads researchers to cross-examine nearly all three billion base pairs of the human genome. When compared to traditional big data disciplines, such as astronomy, Facebook, YouTube and Twitter, data acquisition in this genomic space is predicted to outpace more, and nearly 50% of the world’s population would be aimed for a medical decision by 2030. As of now, the analysis of using medical genomics data is having the front position of this growing need to apply complicated machine learning techniques to large high-dimensional datasets. Biology is even more complicated than this genomic space. In this paper, we explored the parallel algorithm for random forests with large genomic data, which is classified to find the ethnicity nature of a human being. Apache Spark’s MLlib is mainly designed for the common use cases where the genomics data have nearly thousands of features and that need to be scaled up for the millions of genomic features. The study is conducted using VariantSpark based on Spark core, and it has the parallelization computing to coordinate with genomic massively distributed machine learning job.

Recently, almost everyone in the world owns a vehicle. On the other hand, there is an effective increase in the automobile theft, which is becoming a major problem in the present traffic scenario. However, in the current scenario, there is a lack of integrated systems which can effectively track and monitor the driver using Global Positioning System (GPS), GSM and camera. To overcome these issues, an effective anti-theft tracking system is introduced in this paper, which makes use of GPS to collects the latitude and longitude location of the vehicle and also the camera to take the picture of the intruder for further analysis. The resultant information is sent to the server, and the server sends message about intruder of the vehicle to the owner using GSM module. The evaluated results of the experimental setup illustrate the better performance of the proposed framework in terms of accurate identification of intruder and the location of the vehicle, and thereby, this framework can be employed in real time to prevent automobiles thefts.

It does not take much to see and experience the rapid advancement of technology in the world. We can observe personal technologies are getting smaller, smarter and overall more efficient but that is not to say that technological advancement is stopping at consumer level. People of this generation are busy in their day-to-day life as such that they do not get enough time to maintain the food storage facilities at home. Due to busy life schedule, they have to shop for the food commodities such as grains, etc. in bulk quantity to be maintained and used for over a period. We are proposing a system to monitor food grains and to maintain storage system at home. The proposed system is equipped with auto SMS and email alert system to alert the owner regarding the food storage level and the information related to the food spoilage. We come across local unscientific food storage systems in home-based kitchens. There is a chance for food grains getting spoilt due to moisture, humidity, temperature and various other factors. Hence, it becomes very important for us to monitor the food storage level and maintain it to lead a tension-free healthy life. For this purpose, we are going to use various sensors. For our design, an advanced board such as Renesas GR Peach has been used as a central processing unit with different sensors embedded to create a smart home food and grains storage maintenance and monitoring system.

This research work presents a vehicle security system for safeguarding the vehicle from theft issues under the architectural design of capturing and comparing the vehicle user’s face. Since the face of human beings are unique and has different biometric characteristics which are complex to make fraudulent activities. Authenticating the vehicle users with face recognition mechanism is highly secured than token-based and knowledge-based security mechanisms. This research ultimately models and classifies the vehicle users into authorized and unauthorized users. Initially, an experimental prototype for vehicle security system is developed, and the application of image processing algorithms is incorporated into the model. The system uses Haar feature-based cascade classifier and AdaBoost method which is a machine learning algorithm used for detecting the authorized user’s face effectively. The algorithm is trained initially with appropriate amount of positive and negative images, and the feature gets extracted. When the person tries to access the vehicle, the experimental system captures the image of the person and makes comparison with extracted features to identify the authorized user. Finally, the results obtained from the prototype system are satisfied and beneficial against the issue of vehicle theft.

Network-on-Chip (NoC) approach emerged as a promising alternative to overcome the bottleneck and scalability problems of traditional bus-based and point-to-point communication architectures. NoC implementation can be either fully synchronous, Globally Asynchronous and Locally Synchronous (GALS) or fully asynchronous. Asynchronous system is a potential solution to overcome the synchronous NoC design issues in deep submicron regime. GALS NoCs have reduced data throughput due to latency overheads caused by the synchronization interfaces whereas in asynchronous NoCs, each packet needs to traverse only two synchronization interfaces. This paper makes a comparative study of the state-of-the-art asynchronous NoC routers.

The goal of the paper is to present an omnichannel architecture for air travel applications that enables seamless access and up-to-date travel information across channels. Air travel applications are characterized by diversity and various actors participating in the travel lifecycle. The life cycle is fulfilled by different systems starting from travel inspiration to post-trip activities. The traveler as a consumer of travel applications has multiple options like websites, call center, and travel agent offices to search, book, track, and manage the travel activities. The presence of multiple channels makes the traveler experience easy in terms of time-saving and convenience. The challenge with multiple channels is to ensure the consistency of travel data and keeping them up-to-date. The multichannel does not mean an omnichannel experience. A truly omnichannel experience means that traveler gets travel information flowing seamlessly from one channel to the other. It can be achieved by the architecture building blocks which are powered by big data paradigms including personalization, context management, scaling, and sharing the travel data states. In this paper, we will present the approach, architecture in detail and also discuss the survey results that motivated the research for omnichannel interactions. The architecture includes an in-memory layer that can serve across the channels with traveler data like preferences, interaction information, and history in a scalable way.

The world has evolved to a point where it is impossible to imagine interaction without networks or without connections between devices and people. The advent of the fifth industrial revolution saw the rise of interconnected devices and ‘things’. Internet of Things (IoT) has become the defacto standard for devices and people communicating with each other. The newer the devices that are released in the market so has to be the security be updated to counter security attacks. Every device has to be updated to the latest firmware to keep it secure and work optimally; this paper proposes an architecture to facilitate a secure firmware update in a distributed trust-based blockchain IoT network.

Machine-Type Communicating (MTC) Devices (MTCD) are usually wireless devices, for example, sensors, actuators and smart metres which can talk with each other through exchanging data and take decisions with little or no human intervention. Cellular networks are considered to be one of the best technologies for accommodating MTC. The characteristics generated by MTC traffic are completely different from Human-to-Human (H2H) communications. There will be no control on the increasing number of MTCDs and because of which volume of MTC traffic keeps on increasing. In this paper, we make a comprehensive survey on MTC traffic issues over cellular network and solutions to improve the MTC over cellular network. This paper provides a brief overview of 3GPP standards supporting MTC. We also survey MTC traffic issues in heterogeneous networks consisting of cellular networks, capillary networks. Finally, we review recent standard activities and discuss the open issues and research challenges.

The capabilities of new generation wireless networks can be utilized in Vehicular Ad Hoc Networks (VANETs) to provide improved collision warnings, traffic information and infotainment applications. Information about one vehicle can be forwarded to another vehicle by configuring the IEEE 802.11p standard protocol with security until it reaches a Road Side Unit (RSU) providing autonomous vehicles with secure information such as the speed and direction of the approaching vehicle. This paper evaluates the performance of Ant Colony Optimization (ACO) based Routing with Improved QoS and Security for VANETs (RIQSV) by comparing the metrics delay and jitter with the AODV protocol for vehicular ad hoc networks with QoS without security. Packet level encryption/decryption of the data is carried out using substitution cyphers to provide additional security apart from that offered by the 1609.2. The QoS metrics were measured at three RSUs, averaged over a 2-min period with 0.07 s time interval. Results indicate substantial reduction in average delay and jitter of traffic, proving this suitable for real-time traffic with delay guarantees.

Nowdays, use of the Internet for transaction of knowledge is very common. The end users who are accessing Internet or system are vulnerable to malicious user attacks which results in legitimate user being prevented from accessing the websites. Recently, there are several methods presented for application layer DDoS attacks by considering the different properties of attacks. However, most of the methods suffered from the poor accuracy performance of DDoS attack detection at the application layer. Hence, DDoS attacks have been low volume and act on its own as a legitimate transaction on layer seven means application layer hence such attacks are not detected easily by IDS (Intrusion Detection Systems) or firewall systems. We believe that the accuracy and efficiency of attacks detection are based on correctness of capture data traffic. In state-of-the-art methods, there is no provision to remove the noisy data from the capture logs and hence leads to incorrect detection results. In this paper, we presented the real-time computer networks data capturing for normal as well as attack infected traffics, then designed the preprocessing algorithm to remove irrelevant data to optimize the attack detection performance. In this architecture, we use LOIC DDoS attack generator tool to create attack at packet capturing time and also use KDD cup data set for other attacks trace such as DoS, R2L, L2R, Probe, etc., of the communication network. The experimental results show that proposed data preprocessing method is easy and efficient as compared to state-of-the-art solutions.

Rural India faces a multitude of problems due to its digital divide as compared to the urban areas of the country. Internet of Things (IoT) may help to reduce the divide and lead to the digital development of rural India. Rural IoT can be designed to support smart village vision, which aims to provide automation in many sectors such as noise monitoring, energy consumption, smart lighting, environmental monitoring, health monitoring, education, agriculture, etc. and improve life quality of the people. This paper gives an insight of IoT, cloud computing, and fog computing concepts; and proposes a general model based on these computing paradigms with an objective to have digital inclusion of rural India in cyberspace. The paper presents the gram panchayat as the local grid for the data aggregation and transmission from IoT devices to cloud with nonconventional energy resources to minimize the effects of rural power supply inefficiencies that lead to the digital growth of rural India with urban India.

Seamless continuity is the main objective and challenge in fourth era remote networks (FERNs). To help intelligent constancy in heterogeneous networks, the traditional vertical handover management (VHM) approaches are sufficiently bad. Thus, it is essential to manage those difficulties like a choice of a system and activating of contradictory handover. In heterogeneous remote systems, principle test is a consistent relationship of diverse systems like Wi-Fi, WI-Max, WLAN, and WPAN and so forth. This paper proposed a system called scatter cuckoo searches (SCS) algorithm for vertical handoff, the handover choice stage as well as to mitigate the handling delay and improve the fitness of nodes and quality of a network. We additionally contrasted along and GRA and TOPSIS techniques over SCS in view of the mobile terminal (MT) to get the availability with the best system it estimating by quality of service (QOS) parameters.

Artificial intelligence (AI), and in particular machine learning(ML), deep learning (DL) has seen huge pace in recent years and is now set to really start influencing all aspects of community and occupations in which people are engaged. This growth has been charged the advancement in computing power, combined with headway in algorithms and cybersecurity is no exception. AI is “an area of computer science that deals with giving machines the ability to look like they have natural brilliance.” Systems which are based on AI, sometimes called as cognitive systems, are helping us automate many jobs and gear up difficulties which are more complex than most humans are capable of solving. New generations malware and cyber-attacks can be difficult to detect with traditional cybersecurity procedures. They develop over time, so more vigorous approaches are necessary. Solutions for these problems in security rely on ML use data from earlier attacks to respond to newer. Another significant advantage of AI systems in cybersecurity is that they will free up a huge amount of time for IT employees. AI is most commonly used to detect threats and attacks. The systems are developed in a such a way that it must be able to act quickly to the situation on its own. And AI systems do not make errors in completing their tasks. So each threat is responded in the most effective and proper way. In future days, there will be a rapid increase of an international clash in cyberspace. This may include attacks on infrastructure and utilities, as well as damaging normal operations of government and financial bodies, traditional society institutions such as banks, press, law enforcement, and judicial. So taking the cybersecurity as an issue for this paper and let us see the challenges and what is the role of AI, ML, and DL in avoiding cybercrime in future.

Cloud registering is rising standard to provisioning administrations over the web. It may be the zone about investigating the place a cloud may be used to get data, files, product, and so on. It permits offering from claiming networks servers, information applications, and capacity what’s more benefits likewise registering assets. For cloud registering, there will be a collaboration around different heterogeneous free cloud platforms. This may be conceivable best through interoperability which assumes a way part over giving work to get to cloud registering in distinctive situations. While doing different straightforward expressions it implies that the client necessities interoperability should ship their possessions from you quit offering on that one cloud on different cloud [1]. Multi-tenancy approach knowledge and programs are living with knowledge and programs of alternative firms and that get entry to exclusive knowledge is imaginable through shared systems, shared garage, and shared networks. This section defines the critical consideration which should be addressed when designing for convenience and interoperability.

Today, in the present scenario, many people were facing a lot of problems in getting blood for patients at right time. The needy does not know where to get the blood or how to get access to a required quantity of blood quickly in an emergency. Blood donation is a big issue and consumes a lot of time to the donor. The blood bank systems have no proper tool for managing the blood collected from the camps. The needy in an emergency could not find the compatible blood or platelets with the patient. There are many existing mobile apps for blood donation. Though smartphones are available it is not possible to find a right donor who has compatible blood group with the patient in right time. We propose an integrated solution which will connect blood banks, donors, and the needy. This solution provides efficiency and convenience for the needy to search for required blood group or platelets in your neighbourhood easy and simple. Get instant help form blood banks without signing up required. The solution works for the encouragement of blood donation and ensures the availability of blood or platelets accessible to the needy. It also assists quality management programs for blood platelets transfusion services. Finally, this solution is used to notify/communicate with the nearest blood bank organizations timely to ensure the availability of safe and quality blood accessible to the needy with minimum effort.

With the huge use of smart devices, consumption of IPv4 is increased So, in that case, there is a demand of IPv6 to fulfill the demand. However, in modern days, all smart devices have options of this and due to use of IPV6, all the limitations of IPv4 are crossed. In this paper, we have considered the Open Shortest Path First version 3 (OSPFv3) and presented a topology which is implemented in IPv6 Network. The whole network topology is implemented in GNS3 and the results are obtained. In this network topology, we are finding the shortest path, encryption, and authentication between all nodes of network topology.

Wireless sensor network most knowing topic in the current time. The popularity of wireless sensor network growing very fast because it is low cost devices as well as low energy consumption with higher utilization. Routing protocol is an important part of sensor network. Routing protocols play an important role in the wireless sensor network. LEACH protocol is cluster-based routing protocol. LEACH protocol work on two steps, the first step is setup phase and the second step is a steady phase. In the setup phase, we select the one cluster head in the group of nodes after that come to the steady phase here we aggregate the data or compress the data then send the data to sink node or gateway. In this paper, we propose a new protocol Reappointment LEACH (Re-LEACH) which is more energy efficient than other protocols as well as lighter overhead. Re-LEACH protocol increases the life period of sensor network with low energy consumption.

PSI (Ψ) shaped slotted fractal antenna (PSSFA) that operates in multiband behavior was designed for Long-Term Evolution (LTE) applications. The shape which is again repeated on base of PSI geometry is known as Modified PSI shaped slotted fractal antenna (MPSSFA). The simulated results were obtained by the use of Zeland IE3D v.14.1. The simulated values of reflection coefficient for PSSFA obtained are −23.68, −15.94, and −14.04 dB for the resonant frequencies 2.33, 4.60, and 5.08 GHz. As the numbers of repetitions were increased, the resonant frequencies were shifted in the left direction from the base geometry. The simulated values of resonant frequencies for MPSSFA are 2.32, 4.52, and 5.12 GHz at reflection coefficient −24.10, −10.18, and −24.28 dB. The dimensional analysis was also performed for PSSFA. The length of PSSFA was varied in comparison to the previous cases taken and it was exhibited a left shift in the resonant frequency.

Nowadays, grid computing is a recognized name in the area of computation. Grid computing provides a strong platform for the jobs demanding high computational power. Resource scheduling and job scheduling are two broad categories of grid computing. A lot of work has been done in this area. In this paper, we present a new job scheduling algorithm which focuses on standard round-robin algorithm with the addition of new “Enhancement Factor”. The experimental evaluation shows that the proposed algorithm reduces Average Waiting Time and Average Turnaround Time, and it takes very less time to process the jobs than other existing algorithms.

Advances in Wireless Sensor Network (WSN) has led to its utilization for development of broadscale and long-term natural checking. In the past, there have been difficulties experienced in meeting end-clients necessities for data gathering and real-time situation monitoring. The essential point is to provide ease of installation, real-time monitoring, and also to give more imperative reliability and productivity to affect choices of system hardware and programming. This paper suggests a method for better utilization of Wireless Sensor Network (WSN) for real-time water quality monitoring to prevent the delay in handling the situation. The method comprises of sensor nodes with a networking capability that can be deployed for continuous monitoring purpose. The temperature and turbidity parameters associated with the water quality assurance is estimated in real time by the sensors, and this information is updated in a remotely located server through GPRS.

Cloud Computing has significantly changed the field of distributed computing systems today, with rapid advancements in web-based computing. As a promising utility service, cloud enables users to access distributed, scalable, virtualized hardware and/or software infrastructure over the internet. Cloud has a pay-per-use model which serves as a major advantage. Task scheduling is an essential and momentous part in a cloud environment. Scheduling mainly focuses to enhance resource utilization thereby reducing the total execution time. Several algorithms like Max-Min, Min-Min, ant colony optimization based, etc., have come into being to handle the complex issue of scheduling. Here, a Priority-Based Max-Min scheduling algorithm is proposed which aims to achieve lower makespan and maximized throughput. This algorithm schedules tasks based on the new priorities obtained from the designed fuzzy inference system, which takes user-set priority and Maximum Completion Time (MCT) of the tasks as inputs.

Diverse cloud advantage bearers outfit substances garage relationship with datacenters oversaw visit. These datacenters give particular get/organized latencies and unit charges for resource utilization and reservation. Consequently, then as settling on enormous CSPs’ datacenters, cloud clients of essential administered programs (example—online social party) go up against two requesting occasions a technique to control bits of figuring out how to general datacenters to meet programming provider deal with objective (SLO) necessities, expansive of every datum recuperation torpidity and openness the ideal approach to managing disperse data and keep up resources in data centers having a place with boundless CSPs to compel the regard charge. To address those issues, we first frame the respect minimization trouble under SLO objectives using the whole grouping programming. Because of its NP-hardness, we by then present our heuristic alliance, sweeping at a shocking cost basically based estimations allocating the set of essentials and an impeccable asset reservation figuring. We what’s more critical support three change techniques to decrease the segment charge and transporter torpidity coefficient-based completely genuinely bits of learning reallocation multicast-fundamentally chiefly based data moving ask for redirection-basically based blockage control. We, at last, adjust an establishment with permit the conduction of the estimations. Our sign driven trials on a supercomputing association and on certifiable fogs (i.e., Amazon S3, Windows Azure Storage, and Google Cloud Storage) demonstrate the sensibility of our counts for SLO guaranteed associations and client cost minimization.

The aim of intrusion detection systems (IDSs) is to detect the malicious traffic and dynamic traffic which changes according to network characteristics, so intrusion detection system should be adaptive in nature. Many of IDS have been developed based on machine learning approaches. In proposed approach, experiment have been carried out on KDD-99 dataset with three classes DoS attack, other attacks and normal (without any attack). Paper checks the potential capability of optimization-based features with artificial neural network (ANN) classifier for the different types of intrusion attacks. A comparative analysis with ANN and other optimizer with ANN has been carried out. The experimental results show that the accuracy of intrusion detection using particle swarm optimization with genetic algorithm (PSO_GA) improves the results significantly by reducing false positive alarms and also improve individual class detection.

Wireless sensor network senses the environment where the human access is limited. Sensor nodes will collect the information and pass it to the sink node. When passing the information, malicious node or compromised node will corrupt it and forward it to the sink node. In the receiver side, a corrupted message will create a problem. The proper information will not be conveyed to the sink node. The presence of compromised node will generate incorrect report and it affects the event detection. In this paper, we proposed an EERN algorithm to provide reliability for the entire wireless sensor network against compromised node. To provide reliability and to save time, we introduced vigilant node and aggregator node. Aggregator node will detect the suspicious node. Vigilant node will identify the suspicious node as malicious, compromised or faulty node.

In recent years, due to the fastest development in digital data exchange, the security of information becomes highly important for storing the data and its transmission process. The data size of text and image are different. So, for providing security to both text and image involves various methods. Choosing the best method to encrypt and decrypt the data also plays a crucial role. Traditional methods may require more time to encrypt and decrypt. Since the compilation time for one method differs from the other. The proposed model provides security for both text and image by means of embedding encrypted text into an encrypted image, and the same can be decrypted to view the original text and image. The algorithms used in the proposed model are chaotic algorithm for text and AES algorithm is used for image encryption and decryption process. Encrypted text is embedded in encrypted image using diamond encoding data hiding strategy and the same is decrypted to get the original text and image.

In this paper, the concept of symmetric encryption method, AES (Advanced Encryption Standard) and asymmetric encryption method, RSA followed by an EX-OR operation are combined to introduce a new Hybrid Algorithm for the enrichment of data security over network. The proposed scheme adds up more complexity in data by increasing confusion and diffusion in ciphertext using AES for data encryption and RSA for key encryption. Thus, intruder will require more time to decrypt the text and it also resolves the brute-force attack, differential attack, and linear attack. The performance analysis of proposed scheme is done and compared with the AES and RSA on the basis of encryption and decryption time. The result shows that the proposed scheme takes less time for encryption process and more time for decryption process, hence it improves the security of the data.

Cognitive radio network is an intelligent radio network that adapts its transmission parameters based on the sensed free spectrum. Sensing the vacant spectrum is a major issue in cognitive radio networks. The spectrum availability is dynamic. Before data transmission, secondary users sense the spectrum to check the occupancy of primary user. In this paper, the comparison of transmitter-side spectrum detection is carried out. The variation of probability of detection is analyzed with respect to probability of false alarm and SNR. Simulation results show that a signal transmitted with high SNR can be detected accurately by having fixed probability of false alarm. In this work, when the SNR is increased from −20 to −10 dB, the probability of detection is increased on an average of 38 and 57% in matched detection technique and energy detection technique, respectively. This paper also gives a comparative study of energy detection techniques, cyclostationary feature techniques, and matched-filter detection techniques.

Internet of Things (IoT) devices is generating large volume and variety of data. These unconnected devices are generating more than two exabyte of data each day. Today’s cloud models are not suited to manage these tremendous data. Moving them from these devices to the cloud for analysis would require huge bandwidth. Cloud servers communicate only through an Internet protocol (IP). But some of the IoT devices are machines that are connected to a controller using countless industrial protocols. Before sending the information retrieved from these devices to the cloud for analysis and storage, it must be translated to IP. The ideal place to analyze IoT data is near the devices that produce these data. This paper introduces fog computing or edge computing, a computational method that is suited for data generated by IoT devices and a few protocols to handle these data.

In the recent years, SDN is an emerging architecture that is ideal for today’s application. It is dynamic and also cost-effective in order to deal with the networking application. It consists of two planes, namely data plane and control plane that are separated from each other. Open flow is the default protocol that has been used in SDN, and it works on the basis of rules framed by the control plane. It may lead to a denial-of-service attack called control plane saturation attack. To overcome this attack, Avant-Guard technique [2] was introduced which overcomes the control plane saturation attack but it leads to another attack called Buffer saturation attack due to SYN flooding. Then, Line Switch technique was introduced with proxy to blacklist the spoofed IP address in order to block the node. But it was not a permanent solution to the problem. Therefore, we proposed a Block Link Flooding (BLF) algorithm which uses Legitimate User Table (LUT) to provide an effective solution. From the experimental results, our Block Link Flooding algorithm is able to identify and block the spoofed IPs and discards the link to the server. This technique is efficient for saving energy up to 33%.

In heterogeneous wireless networks, vertical handoff support provides seamless connectivity. There are multiple context parameters that influence the decision of vertical handover, hence Multiple Attribute Decision-Making (MADM) algorithms are leveraged in deciding the best network for handover. This paper proposes an MADM-based technique to select an appropriate radio access, out of available WLAN and WiMAX radio access technologies. The authors have proposed a novel HUETANS:Handoff Urgency Estimator and Target Access Network Selector module to facilitate vertical handoff. HUETANS ensures Quality of Service (QoS) by incorporating fuzzy logic controllers to handle the vagueness of wireless environment parameters. Usage of Grey Prediction technique for predicting Received Signal Strength (RSS) further restricts number of unnecessary handoffs at low level. Simulation results show that the proposed HUETANS module selects the best network.

Human mobility and walking pattern interpret a lot about the activities and behavior of an individual. Tracing these patterns and detecting abnormalities in the traced patterns can be used for health and fitness monitoring. Human resident sensors like the pocket IMUs uses the Body Area Network (BAN) for motion tracking, measuring vitals and other human behavior. Several works have been carried out to determine the posture by researchers. From the survey, it is found that no attempt has been made to detect abnormality. Hence, in this work, a model is proposed to determine abnormalities in walking and transition pattern using artificial neural network. The experiments were conducted using Castalia Wireless Body Area Network (WBAN) simulator for standard UCI data set. The simulator result shows that the proposed model detects irregularity more accurately.

Developing cost-effective solutions to deliver broadband connection to undeserved or under-connected communities using fixed wireless access technology can be achieved by canopy networks. The former can be implemented using MIMO-OFDM technique. The implementations of MIMO-OFDM in systems have shown promising results in terms of system performance improvement. This paper presents high-speed FFT algorithms for wireless personal area network (WPAN) applications which uses high data rate. In WPAN, the FFT/IFFT block plays the major role. To eliminate the huge burden of the computational requirement of the FFT/IFFT process, the divide and conquer algorithm is employed here. This method not only improves the efficiency but is also easy to implement. In this work, the concept of Discrete Fourier Transform is discussed and the same is implemented using MATLAB for the MIMO-OFDM process.

In the current railway system, it is important to have safety measures to avoid accidents and loss of human life and resources. The important issue that causes an accident is the obstacles on the track. This project deals with the efficient method to avoid accidents due to cracks on the track and obstacles. The main aim of this project is to detect the crack in the railway track and alert the nearby stations. A GPS system is being used to point the location of faults on tracks. The project presents a solution to provide an intelligent train tracking and management system to improve the existing railway transport service. The solution is based on a powerful combination of ultrasonic sensor, peripheral interface controller (PIC), global system for mobile communication (GSM), global positioning system (GPS) technologies, Bluetooth module, and Android application. Using Android application, we can send messages to nearest railway stations.

Data mining has been gaining widespread significance in recent times with the ever-increasing volume of data to be handled and processed in real time scenarios. This research paper investigates a hybrid scheme of data mining implemented for a classification problem on a repository consisting of large volumes of data. A hidden Markov model (HMM) has been utilized for modeling the high dimensional data pool and classification achieved using a naive bayesian classifier. A data repository with four different subjects and 50,000 instances has been mined using the proposed hybrid algorithm and compared against recent mining techniques like radial neural network and bayesian models and superior performance in terms of classification accuracy, computation time has been observed and reported.

Service-Oriented Computing (SOC) could be served as a good platform for the growth of Context Aware Mobile applications with the multi-functionality smart mobile devices. The other key drivers for the evolution of these location aware systems are ease-of-use, convenience, social interactions and anytime-anywhere availability. Additionally, the Context Aware Mobile Applications facilitates day-to-day activities such as search services, business, entertainment, advertising, marketing, shopping, ticket purchasing, payment and mobile banking live and smarter. These applications utilize services as fundamental elements that support rapid, low-cost, loosely connected and dynamic services in heterogeneous environment. Service Computing (SC) promises the development of a world of services with cheaper and agile distributed applications. Underneath the hype and publicity over these new technologies, the design specifications and the physical properties of the involving devices define the capabilities and limitations for many distributed enterprise computing applications.

Resource Allocation is a significant issue in wireless communication and Cognitive Radio Networks in particular, in order to ensure effective utilization of spectrum and telecommunication resources. In this paper we discuss an optimal resource allocation policy for SU in a multi-PU Lost Calls Cleared (LCC) CR Network environment. Here, the primary user (PU) initiates a bargaining to optimally share its underutilized radio resources with the Secondary Users and optimize its profit subject to system constraints. In our proposed model, the Secondary User (SUs) also participate in the bargaining and jointly decides the optimum usage of the shared spectrum from the primary user (PU) satisfying its utility function. Since both the primary and the secondary users aim to maximize their profits by mutual cooperation, we model their interaction by a Nash Bargaining problem using Game Theoretic Approach. We introduce a two-step algorithm in order to obtain the optimal resource allocation for PU and SU. We propose a multi-PU LCC model for optimal resource allocation and obtain an optimal SU assignment policy satisfying the system constraints. The comprehensive simulation results of the analytical model are presented. The result shows encouraging values of average blocking probability and low degradation of system performance with enhanced interference levels.

Day-to-day vehicle usage count is gradually increasing. To provide safety and security to the driver the proposed Advanced Driver Assistance Systems (ADASs) is developed for vehicle/driver safety and better driving. An ADAS is a vehicle intelligent system that uses environmental vision data to improve traffic safety and driving comfort by helping the driver by recognizing and reacting to potentially hazardous in traffic environment. Since an ADAS performs autonomously with passive safety systems (Anti-Lock Braking System, Electronic Stability Control System, Active Steering System, and so on). While driver drives the vehicle, the ADAS-developed electronic system shall provide sufficient information like sleep warning and automatic braking, lane departure warning, blind spot detection, driver monitoring information, pedestrian collision warning information, and speed alert. A driver assistance system keeps on monitoring driving actions and if the driver out-of-at any time overridden by the driver.

In the digital world, the field of communication has developed many applications. In most sectors of communication, the input message or data is encoded at the transmitter and transferred through the communication channel. Data is received at the receiver and after the decoding of the received data, original data is recovered successfully. Noise can be added to the communication channel. Noise affects the input data and data might get corrupted during the transmission. So it is essential for the receiver to have applied some functions, which are able to localize the error at the receiver end data. There are many types of forward error-correcting code. Hamming code is one of them, which has got numerous applications. Hamming error detection and correction code are used in many common applications, including optical storage devices, random access memory, wireless communication system, high-speed modems (ADSL, xDSL) and digital television system. This paper tries to elucidate the design process of hamming code using VLSI because FPGA is more cost-effective than the other system. In this paper, the algorithm for hamming code encoding and decoding has been discussed and after hamming error detection and correction code has been implemented in Verilogger pro 6.5 to get the results. Hamming code is an improved version compared to the parity check method and it is implemented in Verilog in which n-bit of information data is transmitted with (n − 1) redundancy bits. In order to find the value of these redundant bits, a hamming code is written in Verilog, which will be simulated in Xilinx software. The result of simulation and test bench waveforms is also explained.

Wireless Sensor Networks (WSN) have great benefits of reduced costs, lesser scalability factor, and can be employed upon complex and dangerous locations for the purpose of control/automation of tasks and for sensing, processing, sharing/forwarding data. Denials of service (DoS) attacks hinder the regular functioning of such networks leading to compromise of the objectives of them. In this paper a hierarchical clustering approach is proposed to detect the compromise of nodes in WSN due to DoS attacks. This approach outweighs other approaches in the aspect of elimination of outliers and faster response time in detecting the attacks.

In cloud computing, outsourcing a data to third-party cloud providers is not trusted. Ensuring the security is major concern in clouds, our method proposed the security with minimal cryptographic system by fragmenting a data and replicates over Multi-Clouds. We implement RRNS encoding method for fragmenting the data and CTNA which has the centrality measure as a point of distributing and recovering the data. Even in the case of successful attack no information is revealed to anyone. We compute different fragmentation process analysis on several multi-cloud systems, impact in increasing number of nodes, fragments and also the analysis based on different dissemination and retrieval process efficiency with multi-cloud systems. The higher level of security and performance was observed.

The main objective of work is to develop an efficient energy clustering algorithm with merging and splitting. Energy efficiency is the main issues in WSNs, because of battery that is available in WSN cannot be replaced or recharged. The proposed method is an efficient energy re-organized clustered model which uses merging and splitting (EECSM). This algorithm performs merging and splitting for efficient energy in clusters. Previous works show that balancing of load is considered with distributed organized self manner. To eliminate the existing work drawback, we develop a system of proposed for use. EECSM will use energy state information related to sensor nodes for reducing consumption of energy and load maintenance and balancing. EECSM will prolong the network life by merging and splitting the clusters using cluster heads in a sensor network. The experimental results shows that EECSM will performance better in terms of life of the network, scalability, energy residual, and robustness.

IEEE 802.11 wireless network is the widely used network which offers a good connectivity at low cost. A mobile node connects to the Access Point (AP) from which it receives the best signal. In present days, every user wants best service from the network domain. In IEEE wireless 802.11 network user change their position. This is the main causes of handoff. Real time applications should not experience any interruption when user travels to different network coverage. Handoff is the critical issue for continue network services in IEEE 802.11 networks. Different handoff process schemes are introduced for offering seamless handoff to the clients. In this paper, a classification of handoff schemes in 802.11 networks has been presented. The schemes have been classified based on number of radios used. The handoff schemes have also been discussed in brief. A comparative study of the schemes has been presented in this paper.