Energy Consumption Techniques for Wireless Sensor Networks Using PSO and TSA Algorithm
Abstract
Optimizing energy consumption is the main concern for designing and planning the operation of the Wireless Sensor Networks (WSNs). Clustering technique is one of the methods utilized to extend lifetime of the network and balancing energy consumption among sensor nodes of the network. In this paper, we propose the recently developed, heuristic optimization algorithms like Particle Swarm Optimization (PSO) and Tabu Search Algorithm(TSA) as well as the traditional Fuzzy C-Means (FCM) clustering algorithms. A comparison is made with the well known cluster-based protocol approach developed for WSNs known as harmony search algorithm which is music based Meta heuristic optimization method. Simulation results demonstrate that the proposed protocol using hybrid can reduce energy consumption and improve the network lifetime
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Introduction
In Recent developments, wireless network plays a vital role in making advance technologies in science and social welfares. Micro-electronics has created immense level of producing cheap state of network implementation in wireless technology. Advancement in the field of science has created strong base in developments of various applications such as weapons technology, life saving medical trends, agricultural fields, monitoring/predicting systems in industrial applications and process control systems. Each sensor nodes used to sense the environmental changes of the network implementation and to calculate the processed data and to communicate with the global system. It also calculates the energy levels of various networks which is an important factor to be watched out while analyzing life time of the system.
Clustering is a standard process for implementing energy efficient networks and to improvise its system performance in WSN. Each sensor nodes are grouped by various clusters based on its energy level; these clusters are processed under a cluster head detection which can process data parameters locally before being sent to a base station. LEACH and HEED network protocols provide solutions to cluster head election and to reduce energy dissipation. Testline Timing for Cluster formation Algorithm [TTCA] improves the processing time required to connect various cluster nodes both locally and globally and to maximize the network lifetime by election of proper cluster heads. It is time based chain topology which improves the performance still better compared to other network topologies.
Conclusion
From the analysis and simulation results, we can conclude that Hybrid optimization [PSO-TS] Algorithm used for network implementation simplifies the structural analysis between the nodes and to minimize the total energy costs which indeed extend the network lifetime considerably. PSO-TS provide higher reliability compared to other algorithms. Future works can be carried out in this field of other optimization processes such as PSO-GA, PSO-HAS.