DocumentCode :
1511132
Title :
A Hybrid Multiobjective Evolutionary Approach for Improving the Performance of Wireless Sensor Networks
Author :
Martins, Flávio V C ; Carrano, Eduardo G. ; Wanner, Elizabeth F. ; Takahashi, Ricardo H C ; Mateus, Geraldo R.
Author_Institution :
Dept. of Electr. Eng., Univ. Fed. de Minas Gerais, Belo Horizonte, Brazil
Volume :
11
Issue :
3
fYear :
2011
fDate :
3/1/2011 12:00:00 AM
Firstpage :
545
Lastpage :
554
Abstract :
The increasing in the demand for Wireless Sensor Networks (WSNs) has intensified studies which are dedicated to obtain more energy-efficient solutions, since the energy storage limitation is critical in those systems. Additionally, there are other aspects which usually must be ensured in order to get an acceptable performance of WSNs, such as area coverage and network connectivity. This paper proposes a procedure for enhancing the performance of WSNs: a multiobjective hybrid optimization algorithm is employed for solving the Dynamic Coverage and Connectivity Problem (DCCP) in flat WSNs subjected to node failures. This method combines a multiobjective global on-demand algorithm (MGoDA), which improves the current DCCP solution using a Genetic Algorithm, with a local on line algorithm (LoA), which is intended to restore the network coverage soon after any failure. The proposed approach is compared with an Integer Linear Programming (ILP)-based approach and a similar mono-objective approach with regard to coverage, network lifetime and required running time for achieving the optimal solution provided by each method. Results achieved for a test instance show that the hybrid approach presented can improve the performance of the WSN obtaining good solutions with a considerably smaller computational time than ILP. The multiobjective approach still provides a feasible method for extending WSNs lifetime with slight decreasing in the network mean coverage.
Keywords :
linear programming; wireless sensor networks; WSN; dynamic coverage and connectivity problem; hybrid multiobjective evolutionary approach; integer linear programming; wireless sensor network; Evolutionary algorithms; multiobjective optimization; performance evaluation; wireless sensor networks (WSNs);
fLanguage :
English
Journal_Title :
Sensors Journal, IEEE
Publisher :
ieee
ISSN :
1530-437X
Type :
jour
DOI :
10.1109/JSEN.2010.2048897
Filename :
5482092
Link To Document :
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