The impact of the death criterion on the WSN lifetime using EM pollution monitoring algorithm

Wireless sensor networks (WSNs) are one of the most advanced means that are used for monitoring and reporting. The fact that they consist of small, low cost sensor nodes that are continuously used in a variety of applications has made them become a very attractive field in research. One of the main applications of interest in this research is monitoring the electromagnetic (EM) pollution caused by the rapid expansion of electronic and wireless devices. Research has proven that radiations that these devices emit have a huge effect on the human’s health and therefore are worth monitoring. An advanced algorithm was developed in order to monitor these emissions and its main parameters were randomized to give the algorithm a room of flexibility to suit a variety of monitoring scenarios. Although WSNs are used in numerous critical applications, they still face some challenges. Relying on battery-operated sensors causes the network to be resource constrained and therefore, there is a continuous need for prolonging the network lifetime. In this thesis, different death criteria will be applied and their effect on the network lifetime will be investigated. Moreover the impact of changing the number of sensing cycles per network master will be investigated, since the main aim is to exploit the sensor’s energy efficiently. Finally, the selection of network master will be examined, i.e., random vs. planned to evaluate its effect on the previous simulations and more importantly on the network lifetime

FCS-MBFLEACH: Designing an Energy-Aware Fault Detection System for Mobile Wireless Sensor Networks

Wireless sensor networks (WSNs) include large-scale sensor nodes that are densely distributed over a geographical region that is completely randomized for monitoring, identifying, and analyzing physical events. The crucial challenge in wireless sensor networks is the very high dependence of the sensor nodes on limited battery power to exchange information wirelessly as well as the non-rechargeable battery of the wireless sensor nodes, which makes the management and monitoring of these nodes in terms of abnormal changes very difficult. These anomalies appear under faults, including hardware, software, anomalies, and attacks by raiders, all of which affect the comprehensiveness of the data collected by wireless sensor networks. Hence, a crucial contraption should be taken to detect the early faults in the network, despite the limitations of the sensor nodes. Machine learning methods include solutions that can be used to detect the sensor node faults in the network. The purpose of this study is to use several classification methods to compute the fault detection accuracy with different densities under two scenarios in regions of interest such as MB-FLEACH, one-class support vector machine (SVM), fuzzy one-class, or a combination of SVM and FCS-MBFLEACH methods. It should be noted that in the study so far, no super cluster head (SCH) selection has been performed to detect node faults in the network. The simulation outcomes demonstrate that the FCS-MBFLEACH method has the best performance in terms of the accuracy of fault detection, false-positive rate (FPR), average remaining energy, and network lifetime compared to other classification methods

An Energy Aware and Secure MAC Protocol for Tackling Denial of Sleep Attacks in Wireless Sensor Networks

Wireless sensor networks which form part of the core for the Internet of Things consist of resource constrained sensors that are usually powered by batteries. Therefore, careful energy awareness is essential when working with these devices. Indeed,the introduction of security techniques such as authentication and encryption, to ensure confidentiality and integrity of data, can place higher energy load on the sensors. However, the absence of security protection c ould give room for energy drain attacks such as denial of sleep attacks which have a higher negative impact on the life span ( of the sensors than the presence of security features. This thesis, therefore, focuses on tackling denial of sleep attacks from two perspectives A security perspective and an energy efficiency perspective. The security perspective involves evaluating and ranking a number of security based techniques to curbing denial of sleep attacks. The energy efficiency perspective, on the other hand, involves exploring duty cycling and simulating three Media Access Control ( protocols Sensor MAC, Timeout MAC andTunableMAC under different network sizes and measuring different parameters such as the Received Signal Strength RSSI) and Link Quality Indicator ( Transmit power, throughput and energy efficiency Duty cycling happens to be one of the major techniques for conserving energy in wireless sensor networks and this research aims to answer questions with regards to the effect of duty cycles on the energy efficiency as well as the throughput of three duty cycle protocols Sensor MAC ( Timeout MAC ( and TunableMAC in addition to creating a novel MAC protocol that is also more resilient to denial of sleep a ttacks than existing protocols. The main contributions to knowledge from this thesis are the developed framework used for evaluation of existing denial of sleep attack solutions and the algorithms which fuel the other contribution to knowledge a newly developed protocol tested on the Castalia Simulator on the OMNET++ platform. The new protocol has been compared with existing protocols and has been found to have significant improvement in energy efficiency and also better resilience to denial of sleep at tacks Part of this research has been published Two conference publications in IEEE Explore and one workshop paper

Secure Data Aggregation Mechanism based on Constrained Supervision for Wireless Sensor Network

The data aggregation process of wireless sensor networks faces serious security problems. In order to defend the internal attacks launched by captured nodes and ensure the reliability of data aggregation, a secure data aggregation mechanism based on constrained supervision is proposed for wireless sensor network, which uses the advanced LEACH clustering method to select cluster heads. Then the cluster heads supervise the behaviors of cluster members and evaluate the trust values of nodes according to the communication behavior, data quality and residual energy. Then the node with the highest trust value is selected as the supervisor node to audit the cluster head and reject nodes with low trust values. Results show that the proposed mechanism can effectively identify the unreliable nodes, guarantee the system security and prolong the network lifetime

Protocolo de enrutamiento de optimización TABU de bajo consumo de energía para WSN

Introduction: This article is the result of the research “Energy efficient routing protocols in wireless sensor network: Examine the impact of M-SEEC routing protocols on the lifetime of WSN with an energy efficient TABU optimization routing protocol”developed in the IKG, Punjab Technical University, India in 2019. Problem: The task of finding and maintaining routes in WSNs is non-trivialsince energy restrictions and sudden changes in node status cause frequent and unpredictable changes. Objective: The objective of this paper is to propose an energy efficient heterogeneous protocolwith the help of a hybrid meta-heuristic technique. Methodology: In the hybrid meta-heuristic technique, the shortest route has been selected and the data forwarded to the sink in a minimal time span,savingenergy and making the network more stable. To evaluate the technique, a new hybrid technique has been created where the data transmission is implemented from the beginning under MATLAB 2013a. Results: The proposed technique is better than the existing ones since the remaining energy in the network is increased by 62% compared to normal nodes in MSEEC, 65% compared to advanced nodes in MSEEC and 70% compared to super nodes in MSEEC. The network lifetime was also enhanced by 70.8% compared to MSEEC. Conclusion: The proposed protocol was found to be superior based on the average residual energy.This paper proposes an efficient routing mechanism towards the energy efficient network. Originality: Through this research, a novel version of MSEEC protocol is carried out using the TABU search mechanism to generate the functions of two neighbourhoods to detect the optimum path with the aim of maximizing the network lifetime in an area of 200×200m2. Limitations: The lack of other routing techniques falls under swarm intelligence.Introducción: Este artículo es el resultado de la investigación “Protocolos de enrutamiento energéticamente eficientes en la red de sensores inalámbricos: examine el impacto de los protocolos de enrutamiento M-SEEC en la vidaútil de WSN con un protocolo de enrutamiento de optimización TABU energéticamente eficiente” desarrolladoen el IKG, Punjab Technical University, India en 2019. Problema: La tarea de encontrar y mantene rrutas en WSN no es trivial ya que las restricciones de energía y los cambios repentinosen el estado de los nodos causan cambios frecuentes e impredecibles. Objetivo: El objetivo de este trabajo es proponer un protocoloheterogéneo de eficiencia energética con la ayuda de una técnica metaheurística híbrida. Metodología: en la técnica metaheurística híbrida, se seleccionó la ruta más corta y los datos se enviaron al sumidero en un período de tiempo mínimo, ahorrando energía y haciendo que la red sea más estable. Para evaluar la técnica, se ha creado una nueva técnica híbrida donde la transmisión de datos se implementa desde el principio en MATLAB 2013a. Resultados: La técnica propuesta es mejor que las existentes, ya que la energía restante en la red aumenta en un 62% encomparación con los nodos normales en MSEEC, el 65% encomparación con los nodos avanzados en MSEEC y el 70% encomparación con los nodos en MSEEC. La vidaútil de la red también se mejoróen un 70.8% encomparación con MSEEC. &nbsp

Metaheuristics Techniques for Cluster Head Selection in WSN: A Survey

In recent years, Wireless sensor communication is growing expeditiously on the capability to gather information, communicate and transmit data effectively. Clustering is the main objective of improving the network lifespan in Wireless sensor network. It includes selecting the cluster head for each cluster in addition to grouping the nodes into clusters. The cluster head gathers data from the normal nodes in the cluster, and the gathered information is then transmitted to the base station. However, there are many reasons in effect opposing unsteady cluster head selection and dead nodes. The technique for selecting a cluster head takes into factors to consider including residual energy, neighbors’ nodes, and the distance between the base station to the regular nodes. In this study, we thoroughly investigated by number of methods of selecting a cluster head and constructing a cluster. Additionally, a quick performance assessment of the techniques' performance is given together with the methods' criteria, advantages, and future directions