Computing and Network Sustainability

The principle venture resists through remote sensor systems is security. Acknowledge as valid with models had been nowadays guided as a productive security way for WSNs. In this errand, it prompts a trust model for secure directing and restricting malignant assailants in WSN. To start with, report conviction, vitality conviction, and data acknowledge as valid with are mulled over at some stage in the estimation of direct consideration. Moreover, if the source and destination hubs are far away, then exhortation and diagonal concur with are figured. Consider, consistency and consideration are characterized to reinforce the rightness of exhortation conviction. Malignant hubs might be related to low conviction values that is distinguished in direct and proposal concur with figuring. The proposed model can think about constancy of sensor hubs more prominent effectively and maintain a strategic distance from the security breaks additional accurately.

The aim of the present paper is to analyze probabilistically various performance measures of two redundant systems under Weibull failure and repair activities using semi-Markov processes and regenerative point technique. Two stochastic models comprise of one original and one duplicate units are developed with the provision of a single repair facility and priority. All repairs and preventive maintenance, after a pre-specific time, are perfect. Recurrence relations of availability, mean time to system failure and profit function for both the models are derived. To highlight the importance of the system, numerical and graphical results for the difference of both models are obtained with respect to failure rate of original unit.

The intriguing characteristics of remote sensor systems, for instance, mindful nature of action to base station that happens through its various to-one topology and effect in physical channel are essential reasons of stop up in remote sensor frameworks. Also when sensor center points imbue material data into framework the block is possible. Blockage impacts the predictable stream of data, loss of information, deferral in the arrival of data to the destination and undesirable use of gigantic measure to a great degree obliged measure of imperativeness in the hubs. Along these lines Clog in remote sensor frameworks ought to be controlled with a particular deciding objective to draw out structure lifetime improve sensibility, high essentialness capability, and upgrade nature of organization. This broadsheet has generally depicted the trademark and the substance of stop up controlling remote sensor establish and surveys the inspection related to the block control traditions for remote sensor systems.

In this epoch, Web and network applications are new quick. With the rapid development of various multimedia technologies, thousands of multimedia expertise are created and transmitted within the administration places of work (CID, FBI), study organization, E-trade, and navy fields, so the necessities to ensure such purposes are expanded. Video encryption calculations have turned into a vital discipline of study nowadays. As the cost of making use of video is getting increased, the security of video expertise seems to be extra essential. Hence, there is an incredible interest for storing and transmission methods for secured information. In the course of the most recent couple of years, numerous encryption algorithms have offered to secure constant video transmission, while countless encryption techniques have been proposed and some have been utilized as a part of real time. In this work, we introduce another relative study between IDEA and RSA encryption algorithms.

In this paper, it has been discussed improved AODV routing protocol for mobile ad hoc network. Later, we compared performance of AODV, improved AODV (AODV+), and DSR routing protocols in mobile and non-mobile scenarios. From thorough simulation analysis, we conclude that our improved AODV protocol can improve the average throughput by an average of 30% and energy consumption by an average of 16% as compared to existing AODV protocol.

In the present work, a circular dual-band patch antenna structure with four rectangular slots is proposed and fabricated for wireless applications. The performance of patch antenna has been analyzed in terms of antenna parameters return loss, VSWR, radiation pattern, and gain. A maximum gain of 3.93 dB at lower resonant frequency of 3.71 GHz and a gain of 3.09 dB at upper resonant frequency of 5.51 GHz are achieved. E-field beam width of 230° and 205° and H-field beam width of 250° and 165° are observed for lower and upper resonance frequencies at −3 dB. The experimental results of return loss and VSWR of the proposed structure are presented along with the simulated results .

This paper presents the design of a smart intent-based triggering system to trigger a functional electric stimulator, based on an electromyography (EMG) measurement of voluntary muscle activity and IMU measurement of gait. Thus, an atrophied/weakened muscle is electrically stimulated by identifying predefined gestures and EMG signal strength of the active muscle bundle, thereby restoring the movements of the affected muscle. This smart FES triggering system is designed as a strap on module and deployed at the site of the affected muscle.

Every year, many students enroll themselves on various courses offered by institutions. In that bundle of admissions, a few tend to fall out of their academic programs. Students drop out of their courses due to varied reasons. Analyzing these reasons in order to predict the dropout rate of an institution is of interest. In this research chapter, we are considering a few reasons such as student attendance, educational history, medical history, family background, disciplinary issues, attendance, etc. as factors to compute and predict future dropout rates of registered courses at institutions. To compute and predict dropout rate, a pre-survey and post-survey is conducted. By applying a Naïve Bayesian classifier we predict the probability of students dropping out. Early prediction of student dropout rates, will help to improve the performance of an organization, both professionally and economically.

There are several approaches to reduce the energy consumption. Among them, one approach which allows for reducing the transmission energy consumption is Delay Tolerant Networks (DTNs). Several techniques are adopted to optimize the energy efficiency. Adjusting the resource allocation and decreasing the equipment usages are the basic two categories, which are used to reduce the energy consumption. With the increasing data transmission rate the energy consumption increases, which result in the diminishing of its efficiency. So, it is a necessity to manage the trade-off between energy and performance in Delay Tolerant Networks. The DTN nodes commonly operate on low-power battery resource; hence, there is need of improving the energy efficiency by using appropriate technique to increase the lifetime of the node and also to increase the probability of delivering the bundle. For that purpose, this paper describes the various techniques to achieve energy efficiency in Delay Tolerant Networks.

This paper presents a novel design of a triband antenna for wireless communications. Presently, many research groups are working on LTE/4G/5G mobile communications technologies and proposed various types of antenna designs. We have proposed an antenna which not only operates at three resonant frequencies but also having high gain. This antenna also fulfills the requirement of low cost, less weight, small size for wireless mobile devices. The design and simulation of proposed triband mobile antenna carried out with Flame Retardant 4 (FR-4) substrate and dimension of antenna substrate is 95 mm × 50 mm. Performance parameters of this antenna is investigated in terms of gain, return loss, VSWR, and radiation pattern. The resonant frequencies of the proposed antenna are 2.45, 5.09, and 7.65 GHz. High Frequency Structure Simulator software’s (HFSS’s) optometric is used for the proposed antenna for more accuracy, and results are optimized. The proposed antenna provides an operating band, covering the (UMTS) Universal Mobile Telecommunications System bands (2300–2400 MHz), (WLAN) Wireless Local Area Network bands (2400–2497 MHz), and (WiMAX) World Interoperability for Microwave Access system bands (3300–3790 MHz) simultaneously. The simple configuration and low profile attributes of the proposed antenna made it easy for fabrication and suitable for the application in the UMTS/WiMAX/WLAN and satellite communications.

The crucial task for Indian policy makers and farmers is the decision of crop selection by taking into consideration the various factors, which boosts the precision farming. To overcome this scenario, a decision support system is proposed by using GIS and DM techniques, which helps in deriving a pattern by associating various factors to enhance DSS to suggest potential crop for a region. The system was designed, developed, and implemented across a selected region. This paper narrates the architectural framework of the implemented system.

Transforming text into executable code at runtime with a function Eval() in dynamic languages such as PHP and JavaScript provides the ability to programmers to extend applications at any time. But every extensive power comes with a price, and here, performance security and efficiency are the cost. In prior work, we examine reason behind the performance degradation by Eval() calls. But in PHP, Zend compiler has some limitation, and in JavaScript, browser has few limitations. Though the execution of Eval() remains unchanged, we identified few replacements for the same functionality. As few large-scale PHP frameworks have a common pattern of unnecessary use of this dynamic feature, we targeted moodle (a large-scale PHP framework) to prove performance enhancement by replacing Eval’d code with some other programming features. Our static analysis survey reflects that almost 70% Eval’d code is replaceable.

Network security in organizations is not limited to tangible systems but beyond the physical existence, its focusing on security of non-tangible data flowing in network inside and outside of organization while communicating through Internet. In this paper, we will discuss about different types of intrusion detection system (IDS) available and comparison of their various aspects. Finally, I propose my research work as intrusion filtration system (IFS), which will be a new methodology for network security.

In wireless communication, Mobile Ad hoc networks (MANETs) offer multi-hop communication for mobile nodes which are bounded within limited transmission range. Thus, to transmit data through multiple hops, improve the network lifetime and utilization of power, routing of packets plays a vital role. There are various routing protocols such as reactive, proactive, and hybrid. In this paper, we have developed a new routing protocol called as Modified Dynamic Source Routing Protocol (MDSR) which builds multi-path routes and selects the optimum path among several paths to destination based on threshold level of energy and distance, and it also improves network lifetime. MDSR gives improved performance result, such as a residual energy, active routing path energy ratio, packet loss ratio, energy consumption, and overhead, under different pause time. Compared to existing conventional DSR routing protocol, the proposed MDSR is implemented with certain simulation parameters using Network Simulator (NS-2) tool.

It is very interesting to identify human facial expression in the domain of image processing. Since last decade, a lot of research has been focused on this area. The role of this field in human–computer interaction has increased its importance multifold. In this paper, we have used manual database of eyes and mouth which is further classified on the basis of emotion. The expressed emotions included anger, sadness, happiness, and neutral. This classified database is then used to retrieve corresponding facial emotion. We have used Haar cascade technique for detecting the eyes and mouth and nearest neighbor for classification of emotion. The accuracy of this technique is measured on $$400+$$ sample images taken arbitrarily. From the result, we conclude that presented algorithm is able to precisely classify emotion in frontal images on the basis of eyes and mouth only.

To develop good quality software product, there is a need of continuous defect identification and classification in each module before delivering a software product to the customer. Developing software needs proper managing of the available software resources. To deliver a software product on time, developing quality software products, Information Technology (IT) industries normally use software tools for defect detection. Based on severity, defects are detected and classified. This can be automated to reduce the development time and cost. Nowadays, machine learning algorithms have been applied by many researchers to accurately classify the defects. In this paper, a novel software defect detection and classification method is proposed and neural network models such as Probabilistic Neural Network model (PNN) and Generalized Regression Neural Network (GRNN) are integrated to identify, classify the defects from large software repository. Defects are classified into three layers based on the severity in the proposed method abstraction layer, core layer, and application layer. The performance accuracy of the proposed model is compared with MLP and J48 classifiers.

This paper presents the design of a portable low-cost wireless wearable embedded system to provide motion capture in real-time. The system consists of multiple wireless nodes strapped on to the subject. Each node contains a Wi-Fi module, battery, inertial sensors, magnetometer and a microcontroller sealed inside a 3D printed enclosure. The microcontroller runs an attitude estimate algorithm and streams the data to a Blender game engine. Data from all the nodes is collected using round-robin algorithm and given to an avatar model which mimics the human gait.

This paper presents the design of a level sensor for the purpose of liquid level sensing and monitoring using capacitive sensing techniques. Conventional techniques have many drawbacks with respect to accuracy and they cannot be used reliably for remote sensing. The design proposed here uses three capacitive sensors and a capacitance to digital converter IC integrated onto a sensor Printed Circuit Board. The sensor PCB is attached to the walls of the container and this allows the measurements to be made without any contact with the liquid. The sensing mechanism is independent of the liquid or the environment in which it is placed. The levels are uploaded onto a database located at a local server, and this data can be easily accessed by the user as per his requirement. Further, an android application has been developed for monitoring the liquid levels conveniently.

Outlier is referred to as deviated behavior from normal. Outlier detection is crucial for normal functioning of the network. Suitable actions are needed to thwart such behavior. Event is an expected network behavior, caused by change in the state of the networks, whereas attacks are unexpected behavior in network that cause difficult situations to the network. Event detection and attack detection are many times mistook as same. Event detection is followed by suitable actions to handle the event, whereas attack detection should be followed by countermeasures to subdue the situation. In this paper, we propose an outlier detection scheme (ODS) for detecting events and attacks in the wireless sensor network. We evaluate the efficiency of scheme through simulations.

With the emergent natural disasters and numerous emergency situations, the world is looking for interchangeable reliable medium of communication. Mobile ad hoc network (MANET) is the feasible solution toward maintaining connectivity in a pure infrastructure-less scenario. Providing appropriate quality of services (QoSs) in MANET for applications such as voice, video, and data is a challenging task. Due to dynamic network topology changes and also for the delay-sensitive nature, services like voice or video demand specialized treatment compared to their counterpart data service. In this paper, we present real-time AODV (RT-AODV), a novel AODV-based routing mechanism that improves the quality of service for real-time packets in a MANET. In order to build RT-AODV, first we developed another routing protocol, power and delay-optimized AODV (PDO-AODV), which introduces the concept of load balancing over MANET in a best-effort manner. Simulation results reveal that the proposed RT-AODV accomplishes enhanced performance than best effort PDO-AODV routing protocol in terms of delay, data dropped and network throughput .

IoT is assumed to offer higher connectivity of smart devices, systems, and services that move beyond machine-to-machine communication by using some protocols (RPL, Wi-fi, ZigBee) and techniques (RFID and GSM). Physical objects communicate with each other. Objects can be monitored and controlled through the Internet. IoT has the capability to make home and our life smarter. It can be implemented in different areas such as smart cities, agriculture, energy, healthcare, home automation, and business models. When networks are organized at the large scale, then the security of motes is the main concern. In this paper, we focused specifically on security issues, challenges, and mechanisms of IoT. To secure the network, it is important to establish secure links for the end-to-end communication of motes by using cryptographic mechanism over a home network. We give a solution to secure network communication between motes by purposing Hierarchical Group Key Management Scheme using threshold cryptography in smart homes using IoT.

In today’s world, increasing population density changes the need of the human beings. Today that number has swelled up to 450 and will continue to grow in the future. The need for controlling the devices has made people in developing new technologies like IoT. In today’s era, IoT used in many applications such as smart city, retail, smart agriculture, waste management, household waste, and smart home. Household waste is difficult to manage in all over the world. In the waste management system, many types of waste include solid waste, construction waste, industrial waste, agriculture waste and household waste. To overcome the problem of disposing and managing recycled household waste in a smart city, a weight-based billing system is proposed in this framework that will help to clean the environment. This paper also presents information related to IoT, smart city, waste management system problems, and solutions.

Feature extraction in dental images in the form of radiographs involves the identification of major defect areas. While analyzing complex radiograph images, one of the major problems stems from the types of defects present. Analysis with a large number of defects present generally requires a large amount of memory and computational power. Feature extraction applied over the radiographs, once the edge detection process is accomplished, derives combinations of the defects to get around the problems while still describing the problem areas with sufficient accuracy. The process has been implemented over a set of 20 extracted human dentitions for the identification of similar features to actualize the presence of defects in the dentition.

Quality, efficiency, and scalabilities are main focusing concepts in image retrieval from various image databases. These are major topics in image retrieval from image databases with preferable analysis. Image retrieval from large image databases is a complex task in present days because of image color, shape, and visual features of images in CBIR (content-based image retrieval). So in this paper, we analyze already presented different index-based image retrieval techniques with procedure of each technique for processing quality-based image retrieval from various image databases. Each technique follows basically features such as color, shape, and image length and width in image retrieval from different image data warehouses. We analyze each method implementation procedure for retrieving efficient image retrieval based on query, relevancy with index-based structures.

Software program key loggers were used to spy on laptop users to accumulate sensitive statistics for decades. Their primary attention has been to seize keystroke statistics from keyboards. Cyber assaults targeting critical infrastructure using this information could bring about tremendous catastrophic structure failures. It is important to shield society in this age of modern technology. Online security risks manipulate the extended complexness and connection of critical facilities components, linked to a country’s security, economic climate, and public security. Prior techniques have focused on using dedication techniques that are cryptographic primitives only protecting data stored in RREP and RREQ message formats as part of a sequential execution of tasks. These techniques proven to be effective, might be used along with attack recognition techniques for determining affected routers to increase overall system security by marginalizing the working limitations of an attacker, thus jeopardizing their visibility. A realistic execution validates our claim.

In order to localize mobile nodes, know the correct positions for the placement of static nodes and reduce the time taken to scan the Wi-Fi SSIDs. Wi-Fi path loss models are developed from the setup test bed. The three models can then be used to localize mobile nodes using triangulation method. With the three models, Wi-Fi heat maps have been created. The maps give us complete information for the signal strengths in the given test bed.

Clustering is data mining method to divide the data objects into n number of clusters. Clustering algorithms can be used in domains such as e-commerce, bio-informatics, image segmentation, speech recognition, financial analysis, and fraud detection. There is abandon knowledge in the clustering research and applications and also various improvements are done on various clustering algorithms. This paper includes the study and survey of various concepts and clustering algorithms by experimenting on it on some data sets and then analyzed gaps and scope for enhancement and scalability of algorithms. Then improved k-means is proposed to minimize these gaps. This improved algorithm automatically finds value of number of clusters and calculates initial centroids in better way rather random selection. From the experimentation, it is found that numbers of iterations are reduced; clusters quality increased and also minimized empty clusters in proposed algorithm.

Accurate and economical traffic state estimation is a challenging problem for future smart cities. To curb this problem, fixed roadside sensors are used for traffic data collection traditionally, but their high costs of installation and maintenance has led to the use of probe vehicles or mobile phones containing GPS-based sensors as an alternative cost-effective method for traffic data collection. However, the data collected by the latter method are sparse because the probe vehicles are very randomly distributed over both time and space. This survey paper presents state-of-the-art techniques prevalent in the last few years for traffic state estimation and compares them on the basis of important parameters such as accuracy, running time, and integrity of the data used. The dataset used for the implementation of techniques comes from probe vehicles such as taxis and buses of cities such as San Francisco, Shanghai, and Stockholm with different sampling rates (frequencies) of probes. Finally, it represents the challenges that need to be addressed along with the possible data processing solution.

The dominant operation in cryptographic scheme of elliptic curve is the multiplication using point on an elliptic curve by an integer. This paper specifically discusses the competent algorithms for scalar multiplication a very tedious process in Elliptic Curve Cryptography that are relevant for systems using constrained resources like smart cards. The taxonomy of the work in the open literature for these devices is not only from security perspectives, but likewise some implementation attack, such as fault attacks, must be considered. We survey different implementation approaches and algorithms with the purpose of providing a valuable reference of implementing scalar multiplication in order to retrieve information with a way to determine secret signing key. In addition, this paper provides a review of injecting different fault attacks in a system constrained environment with Elliptic Curve Cryptography. Finally, some arguments about future scope that should be undertaken are provided.

With the growth in IT infrastructure and advances in technologies, workflow scheduling poses many challenging issues for complex applications which require many computing resources. Hence, there is a requirement of a workflow management system adaptable with many cloud environments due to the heterogeneity of resources and applications. In this paper, we have proposed a general workflow management system architecture and a scientific workflow model, followed by a model for monitoring tool in the cloud environment, based on a comprehensive study of literature in cloud computing.

In this paper, the author has developed a system of wirelessly controlling remote units using hand gesture and Internet. A lot of research has already made communication between silent people and the general audience using flex sensor. Here, we will control remote devices with different hand gestures depending upon the measured flexity of the flex sensor. Using IoT, anything across the globe can be monitored and controlled from any place. The microcontrollers used as well as the remote units that are being controlled are connected to Internet either via LAN or Wi-fi module. This system will help those who generally forget small things such as switching the power off when not in use!

A lot of literature is found in the area of vehicular networks. There are several studies that focus on the security issue. Security and privacy become major issues since the public disclosure of identity and location of vehicle is possible. Not only security but also vehicular networking lacks in applications such as emergency services. This paper presents anonymity of driver or passenger in vehicle, the privacy issue by authenticating the vehicle based on a time-dependent secret. The vehicle communicates with the remote server over a reliable and secure medium. For the purpose of simulation, Raspberry Pi, a Linux-based minicomputer, acts as a vehicle interfaced with a GPS module which gives the position of the vehicle. In the case of emergency, the driver pushes the emergency button on his vehicle and its most recent position is recorded at the server. Server sends this location to ambulance or other emergency services which in turn provides the service at the accident-prone zone with minimum delay. Security of entire communication is enhanced by using AES algorithm along with RSA key exchange technique. The entire implementation is a wireless system with added security and can aid to provide quick emergency services in the accident-prone area. This can save the lives of many people.

With recent advancement in various networking technology, many field packet classifications have evolved from traditional classification so as to classify large rule sets. Most of the previous algorithms provide excellent performance when rule set was small. As rule sets grew in size, performance degraded due to lack of memory and do not have enough processing capabilities to route incoming packet at such a high rate. Packet pre-processing is one of the most important aspects of classification, as it will increase the throughput as well as improve the search performance. The proposed method mainly focuses on pre-processing of pre-defined rule set used during classification. In proposed approach, double hashing technique is to optimized memory usage for high throughput. Proposed algorithm implemented on Xilinx ISE design suite 14.2 with 10000–50000 rules. Simulation results shows that the memory consumption is only three fourth compared to existing approaches.

AODV (ad hoc on-demand distance vector) is a reactive routing protocol for MANETs, and it enables multihop routing within the mobile nodes taking part in initiating and preserving an ad hoc network. In multihop routing, route is requested only when it is required and it does not keep track of routes to the destination node. The primary idea of this paper was to assess the AODV variants underneath acquainted mobility models. We have considered three mobility conditions, i.e., Group mobility model, Random Waypoint, and Manhattan model. In our paper, performance metrics such as PDR (packet delivery ratio) and throughput are used to evaluate the performance of AODV variants. The performance metrics are examined with varying node density, and Ns-2 is used as a network simulator to carry out these simulations.

Collaborative filtering is one of the successful techniques in generating personalized recommendations. This paper provides a novel trust mechanism between nodes which is inspired from dynamic trust relation between crime inspectors and their secret informers. In the proposed technique, collaborative filtering has been merged with K-means clustering which improves the overall efficiency and speed of the recommendations. The trust value changes dynamically based on the confidence and similarity between users, which increase the confidence of user in recommendations and overcomes the issues such as shilling attacks. Performance of trust based recommender system is evaluated on Movielens dataset and compared with traditional collaborative filtering and K-means clustering without trust.

The steganography is the discipline of trouncing data into innocuous media in a manner that reality of the hidden data remains invisible to an antagonist. Varieties of methods have been developed over time in the area of image steganography. Robust steganography technique increases data protection from an adversary even if an attacker clutches the knowledge about the embedding process. Modern information security system combines both cryptography and steganography techniques. This paper proposes an image steganography method, at the initial stage secret image is encrypted using advance encryption standard (AES) and afterwards hide the results of AES into the picture (i.e. cover media or cover image) with the assistance of Haar Discrete Wavelet Transform and alpha blending. These efforts ensure that the proposed data hiding mechanism gives higher imperceptibility and trustworthiness which is the essential requirements of any steganography technique. All practical implementation perform on MATLAB.

In the modern generation of “Semantic Web Data”, cloud data services play a important role. These services are based on the MapReduce Programming Model. Hadoop is an open source implementation of MapReduce. Hadoop based extensions such as PIG and HIVE are query languages which provide high level data flow. Although SPARQL is considered as the backbone of the semantic web based applications but in this paper we introduce HIVE and PIG for querying RDF data. The goal of the paper is to compare the results of SPARQL, HIVE and PIG and analyze the retrieval time for a query in RDF data.

Some of the problems faced by commuters today are as follows: (i) accidents due to running over potholes; (ii) reporting accidents to call for medical help (especially if the accident is on isolated/remote roads); (iii) inability to identify the vehicle which was involved in the accident; (iv) unexpected vehicle breakdown; and (v) monitoring the levels of gas emission from vehicles. In our paper, we propose a solution for the above-mentioned problems using an application that works based on the concept of IoT. The application uses various sensors to collect the relevant details and send it to the (i) traffic-related authorities to fix the identified potholes; (ii) hospitals/ambulance services to help the accident victims; (iii) legal authorities to use it as evidence while investigating accidents; (iv) vehicle service centers to fix the vehicle; and (v) to monitor vehicular pollution.

In railways, if all the systems work synchronously and accurately then only security can be ensured. To avoid manual errors, we are hereby proposing a machine-to-machine communication network which will connect all critical machinery and subsystems. It will be a data aggregation and decision-making system during the railway operations. Whole critical machinery will be having their local error detection and correction mechanisms through sensors and transducers. They also have the proposed communication capability with the sink. All threats will be collected at a common node outside the train at a global sink which forwards the train required information for next 10-km propagation. A risk score is calculated which when higher than threshold then the train is signaled to stop immediately. All the threats have their priority score. Collected threats’ priority score is added to get final risk score. This is first ever implementation of machine-to-machine network for railway security. The implementation of work is done using MATLAB v14 which is used to simulate the proposed algorithm. The simulation results are compared with the previous approaches on the basis of average transmission time. Priority score-based analysis also is done in the simulation.

Vehicular ad hoc network (VANET) has been emerged as a prominent technology for intelligent transportation systems. A VANET consists of a number of vehicles equipped together for communication on road side. VANETs are used to fulfill many requirements such as drivers’ safety, data transformation and traffic control, and so on. In VANET, each vehicle behaves independently and as a result, some vehicles might behave selfishly to save their resources. This issue can induce network latency, network break down, security breach, and other issues. In this paper, we address this issue by proposing a honeypot detection approach which endeavors to mitigate selfish vehicles from the network. For experimental results, proposed scheme is incorporated with AODV protocol. We present the behavior of selfish vehicles based on energy constraints. Simulation results under various network parameters depict that the proposed approach provide more robust and secured routing among the vehicles in VANETs.

Digitization of personal data is resulting in nefarious activities encircling them which in return perpetually call for immediate implementation of data security method, cryptography being one of them wherein sender can securely transmit the data over a secure platform. Sender can encrypt the data by encoding the text in an image, and receiver on another part can decode the message by collecting the respective shares. Generations of shares, where slight changes are performed accordingly, are implemented using XNOR operation. Until and unless all the shares are received by the receiver, the secret cannot be decoded, which provides an immense scope of security. Also alteration of the shares formed is not possible, and this gives a great perception of security issue being solved.

Wireless sensor networks which are formed by sensor nodes are used widely for sensing the environment and observing useful information from the data gathered. Due to harsh environmental conditions, the network can be disconnected. Restoring the network’s lost connectivity is crucial for future functioning of the network and is done by placing relay nodes, which are small devices used for transmission of sensed data. This problem of reconnecting the network in an optimal manner is shown to be NP-hard; therefore, we practice meta-heuristics to this problem. In this paper, we propose Federating Network using Particle Swarm Optimization (FN-JPSO), which can be applied efficiently for restoring the lost connectivity. Our proposed approach first finds the representative node for each disconnected segment and then creates Steiner points for reconnection. These Steiner points are further used to create random spanning trees, which are used as particles in FN-JPSO to provide an optimal interconnected network.

This paper presents a cloud-based intelligent traffic controlling and monitoring system to address a major problem of traffic congestion faced by the people. Radio frequency identification (RFID) provides a cost-effective solution to implement the system. Vehicles will be deployed with RFID tags which will give vehicle unique identity. This will give vehicle density at each traffic signal and which will in turn help to control traffic congestion using a smart algorithm. Live traffic density data will be updated in the cloud-based server. Cloud data can be used by police control room (PCR) for monitoring traffic. In case, if the RFID tag belonging to a stolen car is detected, police can take special action to catch the thief. If tag belonging to the ambulance or any other special vehicle is detected, traffic can be rerouted. Android application will use cloud data to display traffic density on user demand.