OPTIMIZATION OF NETWORK LIFETIME USING BALANCED ENERGY CONSUMPTION AND NODE SELFISHNESS IN WIRELESS SENSOR NETWORKS

  • Unique Paper ID: 144324
  • Volume: 3
  • Issue: 10
  • PageNo: 161-173
  • Abstract:
  • Wireless Sensor Networks are interconnection of sensor nodes that cooperatively work for sensing some physical quantity such as temperature, pressure, radiation, etc. These sensor node senses the data and then transmits them to some base station. As sensor nodes are battery driven, an optimal consumption of battery power is necessary so as to enable the network to operate for long duration. This is particularly important as in most of the cases, these networks are deployed in harsh and hostile environments and it is not feasible to replace the batteries frequently. As battery power is consumed in all the operations related to data transmission, it is needed to reduce data traffic inside sensor networks, thereby reducing the amount of data that is needed to send to base station. The main goal of data aggregation algorithms is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. However, data aggregation comes with a cost of latency or delay in the network, which is critical in the case of Real time wireless sensor network applications. Data aggregation has emerged as a basic approach in WSNs in order to reduce the number of transmissions of sensor nodes, and hence minimizing the overall power consumption in the network. In this paper, an analytical model of wireless sensor network is developed with an aim to extend network lifetime. The proposed technique inculcates selfishness in the nodes based on an objective function which calculates the data duplicity / similarity and the residual battery life of the node. This results in energy hole alleviation, thus enhancing the network lifetime. Proposed work extends the techniques proposed by Naeem Jan et. al., through complementing it with the redundancy removal and residual battery life computation. The overall performance of the proposed methods is evaluated using MATLAB simulator in terms of aggregation, average packet drops, transmission cost and network lifetime. Finally, simulation results establish the validity and efficiency of the approach.
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