Hybrid Genetic Algorithm Using a Forward Encoding Scheme for Lifetime Maximization of Wireless Sensor Networks

Maximizing the lifetime of a sensor network by scheduling operations of sensors is an effective way to construct energy efficient wireless sensor networks. After the random deployment of sensors in the target area, the problem of finding the largest number of disjoint sets of sensors, with every set being able to completely cover the target area, is nondeterministic polynomial-complete. This paper proposes a hybrid approach of combining a genetic algorithm with schedule transition operations, termed STHGA, to address this problem. Different from other methods in the literature, STHGA adopts a forward encoding scheme for chromosomes in the population and uses some effective genetic and sensor schedule transition operations. The novelty of the forward encoding scheme is that the maximum gene value of each chromosome is increased consistently with the solution quality, which relates to the number of disjoint complete cover sets. By exerting the restriction on chromosomes, the forward encoding scheme reflects the structural features of feasible schedules of sensors and provides guidance for further advancement. Complying with the encoding requirements, genetic operations and schedule transition operations in STHGA cooperate to change the incomplete cover set into a complete one, while the other sets still maintain complete coverage through the schedule of redundant sensors in the sets. Applications for sensing a number of target points, termed point-coverage, and for the whole area, termed area-coverage, have been used for evaluating the effectiveness of STHGA. Besides the number of sensors and sensors' sensing ranges, the influence of sensors' redundancy on the performance of STHGA has also been analyzed. Results show that the proposed algorithm is promising and outperforms the other existing approaches by both optimization speed and solution quality.

[1]  Jennifer C. Hou,et al.  Maximising alpha-lifetime for wireless sensor networks , 2006, Int. J. Sens. Networks.

[2]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[3]  Jenn-Wei Lin,et al.  Improving the coverage of randomized scheduling in wireless sensor networks , 2008, IEEE Transactions on Wireless Communications.

[4]  Pei-Ling Chiu,et al.  A near-optimal sensor placement algorithm to achieve complete coverage-discrimination in sensor networks , 2005, IEEE Communications Letters.

[5]  Gaurav S. Sukhatme,et al.  An Incremental Self-Deployment Algorithm for Mobile Sensor Networks , 2002, Auton. Robots.

[6]  Michael de la Maza,et al.  Book review: Genetic Algorithms + Data Structures = Evolution Programs by Zbigniew Michalewicz (Springer-Verlag, 1992) , 1993 .

[7]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[8]  Mihaela Cardei,et al.  Coverage in Wireless Sensor Networks , 2004, Handbook of Sensor Networks.

[9]  Gustavo de Veciana,et al.  Minimizing energy consumption in large-scale sensor networks through distributed data compression and hierarchical aggregation , 2004, IEEE Journal on Selected Areas in Communications.

[10]  Shuang Wei,et al.  Distributed sensing based on intelligent sensor networks , 2008, IEEE Circuits and Systems Magazine.

[11]  Jun Zhang,et al.  Implementation of a decoupled optimization technique for design of switching regulators using genetic algorithms , 2001 .

[12]  Ian F. Akyildiz,et al.  A survey on wireless multimedia sensor networks , 2007, Comput. Networks.

[13]  Alhussein A. Abouzeid,et al.  Coverage by directional sensors in randomly deployed wireless sensor networks , 2006, J. Comb. Optim..

[14]  Di Tian,et al.  Connectivity maintenance and coverage preservation in wireless sensor networks , 2004, Canadian Conference on Electrical and Computer Engineering 2004 (IEEE Cat. No.04CH37513).

[15]  Pramod K. Varshney,et al.  Energy-efficient deployment of Intelligent Mobile sensor networks , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[16]  Yu-Chee Tseng,et al.  The Coverage Problem in a Wireless Sensor Network , 2003, WSNA '03.

[17]  Weifa Liang,et al.  Approximate coverage in wireless sensor networks , 2005, The IEEE Conference on Local Computer Networks 30th Anniversary (LCN'05)l.

[18]  A. Brabazon,et al.  An Introduction to Evolutionary Computation in Finance , 2008, IEEE Computational Intelligence Magazine.

[19]  Himanshu Gupta,et al.  Variable radii connected sensor cover in sensor networks , 2004, SECON.

[20]  Robert Jan. Williams,et al.  The Geometrical Foundation of Natural Structure: A Source Book of Design , 1979 .

[21]  Himanshu Gupta,et al.  Connected sensor cover: self-organization of sensor networks for efficient query execution , 2003, IEEE/ACM Transactions on Networking.

[22]  Jennifer C. Hou,et al.  Maintaining Sensing Coverage and Connectivity in Large Sensor Networks , 2005, Ad Hoc Sens. Wirel. Networks.

[23]  Ashish Goel,et al.  Set k-cover algorithms for energy efficient monitoring in wireless sensor networks , 2003, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[24]  Zbigniew Michalewicz,et al.  Genetic algorithms + data structures = evolution programs (3rd ed.) , 1996 .

[25]  Biswanath Mukherjee,et al.  Wireless sensor network survey , 2008, Comput. Networks.

[26]  M. N. Giriprasad,et al.  ENERGY EFFICIENT COVERAGE PROBLEMS IN WIRELESS Ad Hoc SENSOR NETWORKS , 2011 .

[27]  Miodrag Potkonjak,et al.  Power efficient organization of wireless sensor networks , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[28]  Andrea J. Goldsmith,et al.  Cross-Layer Energy and Delay Optimization in Small-Scale Sensor Networks , 2007, IEEE Transactions on Wireless Communications.

[29]  Guoliang Xing,et al.  Integrated coverage and connectivity configuration in wireless sensor networks , 2003, SenSys '03.

[30]  Jun Zhang,et al.  Clustering-Based Adaptive Crossover and Mutation Probabilities for Genetic Algorithms , 2007, IEEE Transactions on Evolutionary Computation.

[31]  Mario Di Francesco,et al.  Energy conservation in wireless sensor networks: A survey , 2009, Ad Hoc Networks.

[32]  Yu-Chee Tseng,et al.  Efficient Placement and Dispatch of Sensors in a Wireless Sensor Network , 2008, IEEE Transactions on Mobile Computing.

[33]  Mohamed F. Younis,et al.  Strategies and techniques for node placement in wireless sensor networks: A survey , 2008, Ad Hoc Networks.

[34]  Krishnendu Chakrabarty,et al.  Sensor placement for effective coverage and surveillance in distributed sensor networks , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[35]  Ding-Zhu Du,et al.  Improving Wireless Sensor Network Lifetime through Power Aware Organization , 2005, Wirel. Networks.

[36]  Yang Xiao,et al.  IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, PAPER ID: TPDS-0307-0605.R1 1 Random Coverage with Guaranteed Connectivity: Joint Scheduling for Wireless Sensor Networks , 2022 .

[37]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[38]  Elizabeth F. Wanner,et al.  A dynamic multiobjective hybrid approach for designing Wireless Sensor Networks , 2009, 2009 IEEE Congress on Evolutionary Computation.

[39]  S. Sitharama Iyengar,et al.  Biologically Inspired Cooperative Routing for Wireless Mobile Sensor Networks , 2007, IEEE Systems Journal.

[40]  Yang Xiao,et al.  A Survey of Energy-Efficient Scheduling Mechanisms in Sensor Networks , 2006, Mob. Networks Appl..

[41]  David K. Y. Yau,et al.  Coverage in Wireless Sensor Networks , 2009, Guide to Wireless Sensor Networks.

[42]  Youwei Shao Improved Clustering Algorithm for Energy Saving in Wireless Sensor Networks , 2010, 2010 International Conference on Multimedia Technology.

[43]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[44]  Mengjie Zhang,et al.  A New Crossover Operator in Genetic Programming for Object Classification , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[45]  Di Tian,et al.  A coverage-preserving node scheduling scheme for large wireless sensor networks , 2002, WSNA '02.

[46]  Ren-Song Ko,et al.  An effective genetic algorithm to improve wireless sensor network lifetime for large-scale surveillance applications , 2007, 2007 IEEE Congress on Evolutionary Computation.

[47]  G. Calinescu,et al.  EFFICIENT ENERGY MANAGEMENT IN SENSOR NETWORKS , 2004 .

[48]  Michael Segal,et al.  Improved approximation algorithms for connected sensor cover , 2004, ADHOC-NOW.

[49]  Deying Li,et al.  Wireless Sensor Networks with Energy Efficient Organization , 2002, J. Interconnect. Networks.

[50]  Jiang,et al.  Energy saving in wireless sensor networks , 2009 .

[51]  Viktor K. Prasanna,et al.  Energy Minimization for Real-Time Data Gathering in Wireless Sensor Networks , 2006, IEEE Transactions on Wireless Communications.

[52]  S. Sitharama Iyengar,et al.  Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks , 2002, IEEE Trans. Computers.

[53]  Chih-Yung Chang,et al.  Energy-aware node placement, topology control and MAC scheduling for wireless sensor networks , 2008, Comput. Networks.