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A Fuzzy Inference System For Increasing Of Survivability And Efficiency In Wireless Sensor Networks

Discussion in 'Paper, Article, Thesis and Technical Report' started by Homaei, Nov 6, 2013.

  1. Homaei

    Homaei Administrator Staff Member

    A Fuzzy Inference System for Increasing of Survivability and Efficiency in Wireless Sensor Networks
    Abstract: The nodes of a WSNs (wireless sensors network) 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 survive ability 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 ACO (ant colony optimization). 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 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. Key words: WSN, energy, routing, fuzzy inference systems, ant colony optimization.

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    Referenced by: http://www.wsnlab.org
    Author: Mohammah Hossein Homaei
    Wireless Sensor Networks Laboratory of Iran

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