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ThinkMind // ICN 2013, The Twelfth International Conference on Networks // View article icn_2013_2_30_10157


A Fuzzy Inference System for Increasing of Survivability and Efficiency in Wireless Sensor Networks

Authors:
Jose Sobral
Aldir Sousa
Harilton Araujo
Rodrigo Baluz
Raimir Filho
Marcus Lemos
Ricardo Rabelo

Keywords: WSN; Energy; Routing; Fuzzy Inference Systems; Ant Colony Optimization; Sink Nodes.

Abstract:
The nodes of a Wireless Sensors Network (WSNs) are composed of small devices capable of sensing and transmitting data related to some phenomenon in the environment. These devices, named sensor nodes, have severe constraints, such as lower processing and storage capacity, and, mainly, they have severe constraints related to battery energy. Therefore, the developing of strategies to reduce the power consumption is one of the main challenges in WSNs, and thereby helping to increase the survivability and efficiency of these networks. This paper proposes a new approach to help multi-path routing protocols to choose the best route based on Fuzzy Inference Systems and ant colony Optimization (ACO). The Fuzzy System is used to estimate the degree of the route quality, based on the number of hops and the lowest energy level among the nodes that form the route. The Ant Colony Optimization (ACO) algorithm is used to adjust the rule base of the fuzzy system in order to improve the classification strategy of the route, and hence increasing the energy efficiency and the survivability of the network. The simulations showed that the proposal is effective from the point of view of the energy, the number of received messages, and the cost of received messages when compared against other approaches.

Pages: 34 to 41

Copyright: Copyright (c) IARIA, 2013

Publication date: January 27, 2013

Published in: conference

ISSN: 2308-4413

ISBN: 978-1-61208-245-5

Location: Seville, Spain

Dates: from January 27, 2013 to February 1, 2013

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