A Fuzzy Logic Approach by using Particle Swarm Optimization for Effective Energy Management in IWSNs

Abstract

Industrial Wireless Sensor Networks (IWSNs) allow the use of battery-operated nodes to provide an easy deployment, also in harsh environments, and low maintenance. The optimal network design can be a tough task because several constraints and requirements must be considered, among all the power consumption. For this reason, specific approaches, also based on soft computing methods, can be applied in such a way as to further decrease the energy consumption in IWSNs. To this end, this paper proposes a fuzzy logic based mechanism that according to the battery level and the ratio of Throughput to Workload defines the sleeping time of sensor devices in an IWSN based on IEEE 802.15.4 protocol. A Particle Swarm Optimization (PSO) algorithm is introduced to obtain the optimal values and parameters of the proposed Fuzzy Logic Controller (FLC), i.e. optimizing the membership functions, by varying their range, to achieve the best results regarding the battery life of sensor nodes.

Existing System

Modulation Scaling, Maximum Power Tracking Control.

Proposed System

In this work, a fuzzy-based approach to deal with the problem of energy consumption in Industrial Wireless Sensor Networks has been presented. The suggested solution provides the possibility to obtain the optimal values and parameters of the proposed Fuzzy Logic Controller, i.e. optimizing the membership functions, by varying their range, to achieve the best results concerning the battery life of sensor nodes, by using a Particle Swarm Optimization algorithm. The paper offered a deep analysis for the configuration of the FLC assisted by the PSO to obtain the one that achieves the best performance. This paper proposes a fuzzy logic based approach to coping with the power consumption problem in IWSNs. In the proposed smart solution, the sleeping time of network nodes is dynamically regulated by a FLC. Besides, a Particle Swarm Optimization (PSO) algorithm is introduced to obtain the optimal values and parameters of the proposed FLC. In detail, the PSO is used to optimize the membership functions, by varying their range to achieve the best results regarding the battery life of sensor nodes.

Architecture

Proposed FLC architecture