Cybernetics and Algorithms in Intelligent Systems

Many of the problems addressed at the industrial level are of a combinatorial type and a sub-assembly not less than these are of the NP-hard type. The design of algorithms that solve combinatorial problems based on the continuous metaheuristic of swarm intelligence is an area of interest at an industrial level. In this article, we explore a general binarization mechanism of continuous metaheuristics based on the percentile concept. In particular, we apply the percentile concept to the Grasshopper optimization algorithm in order to solve the set covering problem (SCP). The experiments are designed with the aim of demonstrating the usefulness of the percentile concept in binarization. Additionally, we verify the effectiveness of our algorithm through reference instances. The results indicate the binary grasshopper optimization algorithm (BGOA) obtains adequate results when evaluated with a combinatorial problem such as the SCP.

This paper provides a broad overview of the adaptive methods for noise reduction used in the analysis of data in the different sensors such as acoustic emissions sensors, power quality signal analysis. The two algorithms are the Empirical Mode Decomposition and the Ensemble Empirical Mode Decomposition. We selected these two algorithms because our focus is on these methods. Firstly, this paper exhibits the inner workings of each algorithm both in the original authors’ intuition and the mathematical model utilized. Next, we discuss the advantages of each of the algorithms based on recent and credible research papers and articles. We also critically dissect the limitations of each algorithm. This paper aims to give a general understanding on these algorithms which we hope will spur more research in improving the field of signal processing in the fiber optic sensor for the oxidised carbon steel.

This contribution focuses an overview of selected results on time-delay systems stability analysis in the delay space, recently published in outstanding high-impacted journals and top conferences and meetings. A numerical gridding algorithm solving this problem designed by the first author is included as well. The theoretical background and a concise literature overview are followed by the list of practical and software applications. Unsolved tasks and open problems stemming from the analysis of presented methods and results concisely conclude the paper. The reader is supposed to use this survey to follow some of the presented techniques in his/her own research or engineering practice.

Paper describes procedure of first principle modelling and experimental identification of Magnetic Levitation Model CE 152. Author optimized and simplified dynamical model to a minimum what is needed to characterize given system for the simulation and control design purposes. Only few experiments are needed to estimate the unknown parameters. Model quality is verified in the feedback control loop where the real and simulated data are compared.

Along with the rise of Internet of Things devices the threat of adopting the IoT devices for cyber-attacks has increased. The number of IoT devices would be more than a billion in the world. Communication potential of such amount of devices is robust and has become more and more interesting for hackers. Mainly DDoS (Distributed Denial of Service) attacks carried from IoT devices seem to be a preferred method of attacker last years.This paper illustrates a special type of DDoS attack using commonly available IoT devices called reflection attack which does not need to compromise the IoT devices. In reflection attacks, the attacker tries to use an innocent third party item to send the attack traffic to a victim to launch a distributed flooding attack, and to hide the attackers’ own identity.To demonstrate this type of attack, we consider the case of three categories of IoT devices: smart light-bulb (primarily used just for control of the intensity and color of the lights in a room), IP camera (digital video camera commonly employed for surveillance directly accessible over a network connection) and Raspberry Pi device (representing a single board computer). The paper demonstrates the potential of the IoT devices to be involved into such attack as well as first insight into communication traffic.

The pedagogical cybernetics has been widely researched corresponding to the modern educational approaches. However, it can be advantageous to complement this theory using the approaches from the technical cybernetics. The particular aspects of the educational processes can be modeled in the general feedback strategy. In the previous research of author of this paper, the modified approach of the feedback strategy, extended using principles of the adaptive control strategy, was proposed for the practical utilization in the pedagogical cybernetics. In this paper, this principle is further improved by aspects of the offline part of the adaptive control strategy. This connection between the pedagogical and technical cybernetic rules is discussed and concretely implemented in favor of the educational process of the foreign students, respectively of the future teachers, at the departmental offered foreign language course of the linear algebra. For purposes of the modern based educational approaches, the information technologies are included in the proposal in this paper in favor of didactics of the mathematical courses.

With significant progress in cryptographic protocols, it has been seen that not all efficient protocols were investigated for encrypting image. At present, we find that existing approaches for image encryption still lacks robustness with respect to forward as well as backward secrecy. Harnessing the potential feature of public key cryptosystem, the proposed system utilizes elliptical curve cryptography for cost effective computation of secret keys required for performing encryption. The security strength is further leveraged by using nucleotide sequencing rules in order to perform scrambling operation of the encrypted image and thereby offering dual layer of security. The study outcome shows that proposed system offers better retention of signal quality as well as lower level of correlation in order to prove better imperceptible features in contrast to existing approaches.

Empirical studies of personal autonomy as state and status of individual freedom, security, and capacity to control own life, particularly by independent legal reasoning, are need dependable models and methods of precise computation. Three simple models of personal autonomy are proposed. The linear model of personal autonomy displays a relation between freedom as an amount of agent’s action and responsibility as an amount of legal reaction and shows legal equilibrium, the balance of rights and duties needed for sustainable development of any community. The model algorithm of judge personal autonomy shows that judicial decision making can be partly automated, like other human jobs. Model machine learning of autonomous lawyer robot under operating system constitution illustrates the idea of robot rights. Robots, i.e. material and virtual mechanisms serving the people, deserve some legal guarantees of their rights such as robot rights to exist, proper function and be protected by the law. Robots, actually, are protected as any human property by the wide scope of laws, starting with Article 17 of Universal Declaration of Human Rights, but the current level of human trust in autonomous devices and their role in contemporary society needs stronger legislation to guarantee the robot rights.

In distributed computing, clustering of the nodes is generally used to make the communication process energy-efficient. However, in the mechanics of clustering, the number of clusters increases as the energy of the nodes gets depleted. This dispersive nature of clustering probability leads to the quick death of the nodes. This chapter explains the usage of an optimization matrix from clustering probability as obtained from a network evolution model. The proposed framework of an optimization matrix shows considerable promise in boosting the efficiency of data delivery and network lifetime of the hierarchical clustering protocols in wireless sensor networks.

The majority of present DC-DC converters operate at a fixed frequency with the only exception at low output load. This approach allows simple suppression of switching noise from the output voltage. For some applications, noisy supply voltage is not the essential problem. The total operating time is more important for many devices powered from a battery or energy harvesting. This paper observes efficiency of DC-DC converter which allows dynamic change of switching frequency under variable operating conditions typical for renewable sources in handheld scale. Experimentally evaluated converter, composed of discrete components, uses SEPIC topology to allow for seamless step-up or step-down transition. Gathered data, shows important features for the development of the new control model of DC power management systems.

In this paper a multiple-model description of supply chain (SC) is presented. The SC state change is described through differential equations based on a dynamic interpretation of the job execution. The problem is represented as a designing control of SC problem in presence of external actions. The approach is based on decomposition of the problem on two parts and its solution with the help of optimal control theory methods and linear programming.

Visualization of vector fields plays an important role in many applications. Vector fields can be described by differential equations. For classification null points, i.e. points where derivation is zero, are used. However, if vector field data are given in a discrete form, e.g. by data obtained by simulation or a measurement, finding of critical points is difficult due to huge amount of data to be processed and differential form usually used. This contribution describes a new approach for vector field null points detection and evaluation, which enables data compression and easier fundamental behavior visualization. The approach is based on implicit form representation of vector fields.

Up to current moment it is actual to lock trustworthy cryptographic services of the complex product providing information security services. These cryptographic services, as usual, are included in as part of delivering complex product and must not be activated without proper additional license.In this article, we provide a method of cryptographic services locking and a protocol of its activation including a legal customer authentication.The main reason of this work is that the law of some countries prepends to export complex information security products with available cryptographic tools.

A modification of the iterative Takahashi—Takami method is discussed to calculate the distribution of the number of requests in the closed multiphase queueing systems. A method is proposed for calculating the moments of waiting time distribution. The results of the calculations are compared with those obtained from a simulation model.

This contribution describe the process that usually precedes the design of the controller - a modelling and a simulation of the observed technological system. Two types of models, physical and abstract, are discussed here. While physical model is usually small or simplified representation of the originally bigger system, the abstract (mathematical) model is description of the system in the form of linear or nonlinear ordinary or partial differential equations. Simulation of the mathematical model then means numerical solution of these equations using some mathematical software. The proposed modeling and simulation procedure is then applied on the real model of the water tank. The mathematical model was then derived and then subjected to the simulation of the steady-state and dynamic analysis.

This paper introduces a novel ISS stability evaluation for a LNU based HONU-MRAC control loop where an LNU serves as a plant and a HONU as a non-linear polynomial feedback controller. Till now, LNUs have proven their advantages as computationally efficient and effective approximators, further optimisers of linear and weakly non-linear dynamic systems. Due to the fundamental construction of an HONU-MRAC control loop featuring analogies with discrete-time non-linear dynamic models, two novel state space representations of the whole LNU based HONU-MRAC control loop are presented. Backboned by the presented state space forms, the ISS stability evaluation is derived and verified with theories of bounded-input-bounded-state (BIBS) and Lyapunov stability on a practical non-linear system example.

Promising orbital remote sensing of the Earth are created in the form of clusters of small spacecraft. One of the central problems of creating small satellites clusters is the development of management systems of their information interaction. The lack of effective control technologies multi-satellite group, transmission, and processing of distributed information huge volumes can negate the impact of the latest achievements in the construction of future space systems usedness. Management system of small spacecraft clusters information interaction should be oriented mostly on maintaining a separate spacecraft and control its production cycle, and to assess the status of the entire cluster and making decisions on its reconfiguration and use for the intended purpose in conditions of limited resources (information, energy, etc.) of the cluster. The solution to such a complex question fraught with difficulties, caused by the imperfection of the existing scientific and methodological apparatus management information by the interaction of complex objects (systems network architecture) [1–4]. The authors proposed a technique based on the developed models [5], which allows to optimize structure and parameters of the Earth’s remote sensing small spacecraft cluster information interaction system. The article shows that the application of the developed technique enhances the performance of the small spacecraft cluster application.

Ball & Plate is a well-known concept and interesting example of an unstable process. Numerous types of Ball & Plate structure can be found and this paper tries to extend its potential of moving the whole plate in space by using an industrial robotic manipulator as the most flexible way to achieve this goal. The collaborative dual-arm robot YuMi from ABB is chosen for this task as the balance between precision and safety. The purpose of the paper is to investigate restrictions and boundaries of such solution, thus the model is identified and based on this identification is designed a controller, which is tested in a simulation environment.

The purpose of the study was to develop a general scheme for measuring and analyzing the dynamics of the state of environmental assets using a set of indicators constructed from environmental, social and economic monitoring data. Methodical approaches to the collection and integration of heterogeneous data describing the functioning of eco-economic objects (port, object of agriculture, recreational zone) have been developed. These data can be obtained as a result of ground-based measurements, remote sensing of the Earth, research of online activity of the population related to environmental responsibility and environmental concerns, and the determination of statistical indicators describing dynamics of environmental assets. The set of the indicators obtained from the remote sensing data of the land has been determined for the port area as a source of adverse impact on environmental assets. It was found out that the data on the Internet search queries for keywords related to environmental pollution reflect the degree of concern of the population with the environmental situation in the region and can be used as an indirect indicator of environmental ill-being. A general framework for integration of heterogeneous data in multi-criteria assessment of the state of eco-economic objects was grounded.

Various bilaterally symmetrical traits have not the same variability in the magnitude of the fluctuating asymmetry. Directional asymmetry (DA) is the second type of asymmetry with a clear predominance of either right or left structures. Since the FA is a considered indicator of instability, traits with DA are not used in the integral environmental monitoring. In presented paper the geometric morphometrics method is considered. This takes into account the labels that are placed on the bilaterally symmetric structures. The centroid points of consensus figure are drawn by the averaging of landmarks in Cartesian coordinates and the value of the FA shape of lamina is evaluated. In present study the MorphoJ1.06d package was used. The sampling procedure resulted in a nested dataset design. The increase in the accuracy of the measurement indicated a large fraction of the directional asymmetry. 90% of population studied possessed this type asymmetry. 10% of samples were characterized by clear fluctuating asymmetry. The results conclude the importance fine compute approach to testing of stability of development in natural biosystem.

Educational Data Mining is an emerging field in the data mining domain. In this competitive world scenario, the quality of education needs to improve. Unfortunately most of the students’ data are becoming data tombs for not analyzing the hidden knowledge. The educational data mining tries to uncover the hidden knowledge by discovering relationships between student learning characteristics and behavior. With this educational data modeling, the educators may plan for future learning pedagogy to support the student’s learning style. This knowledge may be applied by the academic planners to improve the quality of education and decrease the failure rate. In this paper, we had collected real dataset containing 666 instances with 11 attributes. The data is from the Common Entrance Examination (CEE) data of a particular year for admission to medical colleges of Assam, India conducted by Dibrugarh University. We tried to find out the association rules using the data. Various clustering and classification methods were also used to compare the suitable one for the dataset. The data mining tools applied in the educational data were Orange, Weka and R Studio.

With the adoption of increasing number of occupancy sensor in building premises, there is a growing concern about the inclusion of the smarter features for catering up sophisticated demands of information processing in Internet-of-Things (IoT). Although, there are various commercially available occupancy sensors, but there is a bigger deal of trade-off between the existing offered featured and actual demands of the user that is quite dynamic. Therefore, we reviewed the most potential research work carried out towards incorporating various features of occupancy sensor in present times in order to investigate the degree of effectiveness in existing research contribution with respect to problems, techniques, advantages, and limitation. This is the first reported review manuscript in occupancy sensing that offers a quick view of existing research trends as well as brief of potential research gap with respect to open-end problems that are yet to be solved in future studies.

This paper describes a 3D interactive web application which visualizes the appearance of the town of Zlín in the Eighteen-nineties. The Blender software suite was used to create a complex 3D model of Zlín and its municipality in previous years. Now, this model has been revisited, improved and extended. This was followed by work in order to convert it into a 3D web application. The Blend4Web - which is an external software module that extends Blender was used to do this. In order to obtain an application with the correct level of interactivity and rendered image outputs, it is necessary to set all of the corresponding parameters and to optimize them.

Multi-agent systems consist of agents and their environment. the agents in a multi-agent system could equally well be robots, humans or human teams. And may contain combined human-agent.Multi-agent systems can be used to solve problems that are difficult or impossible for an individual agent or a monolithic system to solve. Intelligence may include some methodic, functional, procedural approach, algorithmic search or reinforcement learning.In a system with agents that have their own objectives and schedules, when tasks are dependent on one another or when resources are to be shared, it can be important to add the function of coordination to the system, otherwise there is a risk of redundancy or even of a “locked” situation occurring.With the modeling in Event-B we are now ready to make precise what we mean by a “faultless” system, which represents our ultimate goal as the title of this prologue indicates.In this paper and with the abstract machine, we are going to present a formal approach to develop the addressing and the relation between Multi-Agents and its convenient scope achieving the allocated missions.On the refinement machine the technique of adding auxiliary resources is considered during the mission life-cycle.

Cloud computing provide services to many users at the same time by providing virtual resources via internet, General example of cloud services is Google apps, provided by Google. In most of cloud applications, processing is done on remote cloud computing nodes. So, there are more chances of errors, due to the undetermined latency and lose control over remote nodes, so it is very important apply the techniques for fault tolerance in cloud computing.In this paper, a fault tolerance in real time cloud computing is proposed. In our model, the system tolerates the faults and makes the decision on the basis of reliability of the processing nodes.And we will present an event-B as formal method that can be used in the development of reactive distributed systems and we propose using the Rodin modeling tool for Event-B that integrates modeling and proving.

This paper addresses the problem of channel access in multi-rates IEEE802.11 WLANs (Wireless Local Area Networks). Unlike some current solutions for performance anomaly only aiming to the saturated network, we propose a fine-grain channel access mechanism that takes the saturated and unsaturated network into account simultaneously. Meanwhile, we present a model to detect the network state under different network density. This novel framework can detect the network state by collision rate for the dynamic network scenarios and perform more efficient channel access by combining the legacy IEEE802.11 DCF (Distributed Coordination Function) and airtime fairness algorithm. The simulations show that our algorithm can improve the aggregate throughput and reduce the collision rate during channel access compared to the legacy DCF mechanism.

The paper presents a new method of determining 3D permittivity profile using electromagnetic measurements in the closed waveguide system. The method is based on the application of artificial neural network as a numerical inverter, and on the approximation of 3D profile with quadratic polynomial function. The neural network is trained with numerical data obtained with FDTD modeling of the electromagnetic system. Special criteria for choice of a number of hidden layer neurons are presented. The results of numerical modeling show possibility of determination of permittivity profile with a relative error less than 10%.

The industrial processes and systems have become more sophisticated and also adopted in diverse areas of human activities. The Industrial Control System (ICS) or Internet of Things (IoT) have become essential for our daily life, and therefore vital for contemporary society. These systems are often included in Critical Information Infrastructure (CII) which is crucial for each state. Consequently, the cyber defense is and will be one of the most important security field for our society. Therefore, we use the novelty detection approach in order to identify anomalies which can be a symptom of the cyber-attack in ICS environment. To achieve the main goal of the article One-Class Support Vector Machine (OCSVM) algorithm was used. Moreover, the anomaly detection algorithm is adjusted via multi-criteria evaluation and classifier fusion.

In today’s world, transmission and reception of data secrecy are the foremost concerns in wireless communication. Recently Radio Frequency Identification (RFID) has perceived the massive amount of attention as it inhibits privacy invasions and data disclosure. An entire generation of new security and privacy attacks might arise as the RFID technologies have a widespread deployment all over. One of the significant drawbacks in RFIDs are the unsteady authentication, either the password itself is leaked else data among the reader and a tag. Also, researchers have observed that there are threatening security drawbacks in Electronic Product Code-Class I Generation 2 (EPC-C1G2). To overcome this issue, a function called as the Pad Generation is used that assists in refining the security parameter in the mutual authentication scheme. This paper stresses on Tag-Reader Mutual Authentication (TRMA) - system of RFID tag-reader with the modified version of PadGen. The modified Pad-Gen design uses XOR operation for the RIFD-TRMA protocol. For the cost-effective hardware implementation, the proposed framework is simulated on FPGA Artix7-XC7A100T-3CSG324 device and physically verified on Chip scope pro tool.

A MANET is a form of the wireless network among the mobile, wireless nodes. The presence of various significant attributes in MANET like end to end communications, dynamic topology and simple setup, leads to difficulties like routing, security, and clustering. Network security is an important aspect for both wired and wireless communication. This paper, provide a detail review on different security attacks over the MANETs. Further discussion is carried out by providing of prior solutions to overcome the security attacks and gives a bench mark for future study. An extensive survey of existing researches towards security in MANET is addressed. Later on, a research gap in current state of art in MANET security is discussed. Especially, this survey study mainly focus on security problems, challenges and solution strategies for security concerns in mobile ad-hoc networks.

The Ad hoc technology enables a unique network namely mobile Ad hoc Network (MANET), where the establishment of the routing is a challenging task because of various characteristics such as mobility of the node and resource constraints of individual nodes. The self-configurability of the nodes makes the network vulnerable to initiate different forms of attacks in a very easy way. The malicious activities by the nodes are identified by its behavior of deceiving the other nodes data using participating into routing then dropping the packets, at the same time similar activities of packet drop could happen by non-malicious nodes due to some fault in the nodes. It is a challenging task to distinguish these two categories of nodes. Most of the current approaches focus on the trust building by the previous behavior of the nodes and black listing it, this approach leads to minimize the size of the network and sometimes permanent clustered network partition which leads to network failure. This paper introduces a novel strategy of defensive approach by the regular nodes as opposed to the malicious node and the method is named as “Defensive Strategy in MANET (DSMANET).” The performance parameters like throughput and routing overhead is compared with one of state of the art secure routing method DSMANET and found exhibiting better performance.

Grid computing offers significant platform of technologies where complete computational potential of resources could be harnessed in order to solve a complex problem. However, applying mining approach over distributed grid is still an open-end problem. After reviewing the existing system, it is found that existing approaches doesn’t emphasized on data diversity, data ambiguity, data dynamicity, etc. which leads to inapplicability of mining techniques on distributed data in grid. Hence, the proposed system introduces Optimized Clustering with Statistical Based local Model (OCSLM) in order to address this problem. A simple and yet cost effective machine-learning based optimization principle is presented which offers the capability to minimize the errors in mined data and finally leads to accumulation of superior quality of mined data. The study outcome was found to offer better sustainability with optimal computational performance when compared to existing clustering algorithms on distributed networking system.

A new investigation using meshfree methods to resolve the linear free surface water waves problem. Two methods are used in this current investigation, the method of fundamental solutions (MFS) and multiquadric (MQ) radial basis function. The problem is solved by collocation of boundary points since the governing equations are satisfied automatically in order to provide information on fast and accurate method for an efficient hydrodynamic prediction.

Wireless Adhoc Network has a bigger range of application where some are already in commercial market and majority of them are still under roof of investigation. The degree of vulnerability of wireless adhoc network is quite high irrespective of presence of various existing techniques, which are too much specific to attack or orchestrated scenario of attack. Therefore, the proposed study introduces a framework that introduces a zombie node to capture the attention of attacker by advertising possession of many hops. The study also introduces broker node that is meant for balancing transmission demands along with robust security requirements. The message of zombie node is registered in hop table which makes the virtual zombie node to look like original node. An algorithm is constructed for identifying the malicious node and the study outcome is found to excel better performance with respect to the existing system.

The future applications include a multi-technology based paradigm, which includes wireless sensor network, Internet of things and cloud computing to be synchronized for the accurate and real-time analytics. The applications client will be a smart phone user who will request the wireless sensor network data or key data points of sensors through the universal data centers. This paper highlights the problem identification of the sensor data quality and reliability aspects by proposing a model for sensor data quality enhancement (SDQE) by synchronizing the priority of critical data with time factor. The data request prediction based optimization is proposed to maximize the usefulness factor which is the measure of sensor data quality as reliability and minimize the energy consumption. The model is simulated in numerical computing platform and found acceptable response.

The study considers the resource allocation (R_Al) for Orthogonal Frequency Division Multiple Access (OFDMA) future cellular network (i.e., Cloud-RAN), where multiple mobile operators can distribute the Cloud-RAN infrastructure as well as network resources possessed by infrastructure providers. We have designed the resource allocation system by solving the dual-coupled problems at two distinct levels (i.e., Upper Level and Lower Level). The first level problem responsible for slicing the front haul capacity (F_cap) and computation of cloud resources for all operators (O_p’s). This would indeed tend to increase the overall profits for each O_p as well as infrastructure provider by accounting the numerical constraints on F_cap and computational resources. The study introduces a dual-level algorithmic approach to solve this two level R_Al problem. At first-level, system considers both U_level and L_level problems by relaxing discrete values with continuous ones. While in the second-level, we introduce two rounding methods to solve the optimal relaxed problems and attain a practical solution for the proposed problem. Finally, simulation results show that the designed algorithms efficiently perform the greedy approach to resource allocation and attain the discrete value very near to the total rate of upper bound acquired by solving resource allocation relaxed problems.

The Cloud computing environment is the ultimate infrastructure for almost every kind of application missioned as a smart city or smart application concept, where heterogeneous network generating large data file of varied characteristics of increasing volume on time line which data at move as velocity etc. need to be stored, processed and analyzed. This paradigm shift from proprietary infrastructure to cloud infrastructures leads sudden and random loads as cloudlet to it. The conventional traffic management methods lack the robustness in terms of handling synchronization of heterogeneous network generated large data system. This paper proposes an intelligent traffic management namely ITM-CLD to provision a mechanism of varied traffic load in cloud environment for large data stream. The model ITM-CLD is simulated on numerical computation platform and computes performance metrics such as (1) Cloudlet handling time, (2) Unused resource, (3) Unused memory and finally, (4) Resource cost. Theses metrics are compared for different kinds of traffic load as job category with state of art work and it exhibits better performance.

Over the past decade, mobile ad-hoc networks (MANET) gained the attention of researchers and became a key technology in many aspects owing to its potential applicability and increased usage in providing efficient wireless networking. The ability of enabling an instant temporary wireless networking scenario in situations like flooding and defense made MANET a prominent domain of research. Although, it has been extensively studied with respect to different means of issues including network security, power consumption issues etc. but the core findings in the area of security were found mostly limited to theoretical contributions. Moreover, An intrusion detection systems (IDS) enable different procedures involved into monitoring the activities being exercised in a MANET whether; it poses any suspicious or malicious events that could be harmful for the entire system. The conventional IDS models are more likely to consume higher level of energy which minimizes the network lifetime owing to rapid depletion of node’s battery power. The study thereby primarily addressed this issue and come up with an efficient scheme which targets to optimize the time period in which IDS remain busy in a large-scale MANET. It also incorporated a technique which relates probabilistic theory of optimization to bring an effective cooperation among IDSs and neighbor nodes which leads to reduce their individual busy time. The proposed approach aims to reduce busy time of individual IDS while maintaining their effectiveness towards achieving defined tasks. To support the performance efficiency the proposed study developed an algorithm and simulated it over a numerical computing tool in terms of different performance parameters.

The wireless sensor network has been positioned itself from a complete network system to a sub-net of future internet namely Internet of Things, where a communications among anything to anything is possible. The extensible use of wireless sensor network makes it more risky if the security threats are not handled wisely. The conventional methods adopted for securing the WSN vulnerability based attacks introduces delay, which brings congestion in the routing flow as well as influence the quality of service. The proposed DSP-IR is a secure routing algorithm to handle security with delay sensitivity. The DSP-IR framework evaluates MAC protocols including S-MAC, Q-MAC and IH-MAC along with RSA, AES and DSP-IR encrypt process. For all the three combinations performance evaluation is done by simulating the model to know the behavior of residual energy, energy consumption and average packet delay with varying interval of message arrival time and it is found that the proposed IH-MAC with DSP-IR exhibits better performance.

Ensuring highest degree of resistance against potential adversaries in Internet-of-Thing (IoT) is still an open challenge, and the prime reason behind this is the computational complexities associated with designing security algorithms and its corresponding transformation between the cloud and Wireless Sensor Network (WSN) via gateway node. Hence, the proposed system develops a lightweight and highly responsive encryption technique to offer minimal resource consumption from the resource-constraint sensor nodes. The significant contribution is also to introduce a novel bootstrapping key mechanism with the unique generation of the secret key to maintain both forward and backward secrecy. The study outcome shows that proposed system is highly practical to offer reduced resource consumption and faster algorithm processing time in the presence of dynamic scenario of IoT.

The development of the Wavelength Switched (WS) Optical Networks (ONet) is introduced to extract the significances of entire Optical Switching (OS) fabrics pertaining to high efficiency and automation. However the selective switches of wavelength (SW) indicates the prior switching elements subjected with Reconfigurable Optical Add/Drop Multiplexers (ROADM) frameworks exhibiting the different color-less, direction-less and also with contention-less (Col-Dl-Conl) switching features. With the implementation of the Col-Dl-Conl based ROADM, the WSw ONet nodes will be asymmetrical subjected to its switching abilities. In the process of Quality of Service (QoS) enhancement, choosing switching abilities plays a major role subjected to number of ports (Np) and the asymmetry depends over SSw port size. This paper introduces an efficient model of ROADM switching connectivity (SwC) to achieve Qos for given Np. The performance analysis is performed by considering QoS and found that it depends on SwC.

A new hybrid of the conjugate gradient (CG) method that combines the features of five different CG methods is proposed. The corresponding CG algorithm generated descent directions independent of line search procedures. With the standard Wolfe line search conditions, the algorithm was shown to be globally convergent. Based on numerical experiments with selected large-scale benchmark test functions and comparison with classical methods, the method is very promising and competitive.

Traveling Salesman Problem is a well-known NP-Hard problem, which aims at finding the shortest path between numbers of cities. Chemical Reaction Optimization (CRO) is a recently established meta-heuristic algorithm for solving optimization problems which has successfully solved many optimization problems. The main goal of this paper is to investigate the possibility of parallelizing CRO for solving the TSP problem called (PCRO). PCRO is compared with Genetic Algorithm (GA), which is a well-known meta-heuristic algorithm. Experimental results show relatively better performance for PCRO in terms of execution time, Speedup, optimal cost and Error rate.

The random nature of the occurrence of road congestion has a negative impact on the capacity of the road network. Such congestion occurs at the delay points-sections of the road network on which the vehicle has to stop or slow down. Effective control of the capacity of delay points, thus, can be considered an important and urgent scientific problem. Despite the variety of effective methods of assessing the road situation, traffic routing, and road network planning, the task of dynamic control of capacity is not solved in a complex manner. Also an important aspect is the lack of effective means of mass informing the participants of road traffic on ways to avoid congestion. The random character (both spatial and temporal) of the appearance of delay points, in turn, requires the creation of automated control methods based on configurable information systems. The article presents the concept of a method for managing the movement of traffic flows, based on the elimination of the delay point by means of information technology.