Cluster Based Optimization of Routing in Distributed Sensor Networks Using Bayesian Networks with Tabu Search

This paper proposes a cluster based optimizat ion of routing in Distributed Sensor Network (DSN) by employing aBayesian network with Tabu search approach. Bayesian Network based approach is used to select efficient clusterheads, as well as construction of Bayesian Networks for the proposed scheme. This approach incorporates energylevel of each node, bandwidth and link efficiency. Simulations have been conducted to compare the performance ofthe proposed approach and LEACH.The optimization of routing is considered as a design issue in DSNs due to lack of energy consumption, delayand maximum time required for data transmission between source nodes (cluster heads) to sink node. In this work,optimization of routing takes place through cluster head nodes by using Tabu search. This meta - heuristic techniqueis used to optimize the routing in the DSN environment that guides a local search procedure to explore the solutionspace beyond local optimality. The objective of the proposed work is to improve the performance of network interms of energy consumption, throughput, packet delivery ratio, and time efficiency of optimizat ion of routing. Theresults shows that the proposed approach perform better than LEACH protocol and proposed protocol utilizesminimum energy and latency for cluster formation, thereby reducing the overhead of the protocol

TABU Search Based Cluster Head Selection in Stable Election Protocol

The clustering in the Wireless Sensor Networks (WSN) is one of the most important investigation areas. There are many cluster head selection algorithms which were developed before today. Tabu search based algorithms is developed to reduce the energy consumption and enhance the WSN life-time. The comparison is done among the SEP ,D-SEP,M-SEP and TABU based SEP in the wireless sensor network. The planned technique has the flexibility to beat the constraints of the SEP routing protocol by pattern clump and TABU search. The comparison square measure drawn among the current and planned techniques. The comparisons has clearly shown that the planned technique outperforms over the on the market technique

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

Ant-Fuzzy Meta Heuristic Genetic Sensor Network System for Multi Sink Aggregated Data Transmission

Wireless sensor network with the hierarchical organization of sensors aggregate the tasks into groups. The sensor nodes broadcast the aggregated data directly to the distant base station. Existing Mixed Integer Programming (MIP) formulation obtain the good solutions for multi-action processes but not effectual in developing the hybrid genetic algorithms with the Tabu search meta-heuristics ant colony optimization. Another existing work developed for security purpose named as Dynamic secure end-to-end Data Aggregation with Privacy function (DyDAP) decrease the network load but topological configurations with multiple sinks are not addressed. To develop the hybrid genetic algorithm on ant-fuzzy system, Hybrid (i.e.,) ant-fuzzy Meta-heuristic Genetic method (HMG) based on the Tabu search is proposed in this paper. Ant-fuzzy Meta heuristic Genetic method carries out the classification process on the aggregated data. The classification based on the genetic method uses the Tabu search based mathematical operation to attain the feasible solution on multiple sinks. Initially, Ant-fuzzy Meta-heuristic Genetic method classifies the data record based on the weighted meta-heuristic distance. The classified records perform the Tabu search operation to transmit the aggregated data to the multiple sink nodes. HMG method achieves approximately 19 % improved transmitted message rate. Experiment is conducted in the network simulator on the factor such as classification time and transmission rate

Comparative Analysis of Energy Efficient Clustering Protocol in Wireless Sensor Networks

The clustering based protocols are the best for the heterogeneous wireless sensor networks because they perform the work on divide and conquer rule. In this study, the mainly focus is on the cluster head selection using tabu search in energy efficient clustering protocol. Due to limited energy in sensor nodes, the networkis not stable. For this, many protocols has been proposed so far to improve the energy efficiency .This paper presents the comparative analysis of REAC-IN protocol with Tabu based REAC-IN protocol in terms of alive nodes, energy variance and data received to the sink in bytes. The simulation results show that tabu based REAC-IN protocol performs better instead of REAC-IN protoco

A Cross-layer Framework for Multiobjective Performance Evaluation of Wireless Ad Hoc Networks

International audienceIn this paper we address the problem of finding the optimal performance region of a wireless ad hoc network when multiple performance metrics are considered. Our contribution is to propose a novel cross-layer framework for deriving the Pareto optimal performance bounds for the network. These Pareto bounds provide key information for understanding the network behavior and the performance trade-offs when multiple criteria are relevant. Our approach is to take a holistic view of the network that captures the cross-interactions among interference management techniques implemented at various layers of the protocol stack (e.g. routing and resource allocation) and determines the objective functions for the multiple criteria to be optimized. The resulting complex multiobjective optimization problem is then solved by multiobjective search techniques. The Pareto optimal sets for an example sensor network are presented and analyzed when delay, reliability and energy objectives are considered