Optimal Coverage Scheme based on QPSO in Wireless Sensor Networks

In order to solve the problem of monitor in mining and environment, the wireless sensor networks (WSN) is used. As one of the fundamental and important problems in WSN, coverage reflects the effect of monitoring and tracking. Because of the high density and complexity of distributing nodes in WSN, the coverage control algorithm for the optimal working sensor set is studied. On the other hand, especially recent years, quantum computing is attracted as one method which gives us suitable answers for optimization problems. This paper proposes a novel evolution algorithm, called a quantum particle swarm optimization algorithm (QPSO), which is based on the concept and principles of quantum computing. The proposed algorithm adopts quantum angle to express Q-bit and improved particle swarm optimization to update automatically. After the QPSO is described, the experiment result on the coverage scheme is given to show its efficiency.

[1]  Qian Zhang,et al.  Energy-Efficient Localized Topology Control Algorithms in IEEE 802.15.4-Based Sensor Networks , 2007, IEEE Transactions on Parallel and Distributed Systems.

[2]  Robert Tappan Morris,et al.  Span: An Energy-Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks , 2001, MobiCom '01.

[3]  Krishnendu Chakrabarty,et al.  Sensor deployment and target localization based on virtual forces , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[4]  Jie Zhu,et al.  Energy-efficient Mechanism Based on ACO for the Coverage Problem in Sensor Networks , 2007 .

[5]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[6]  Zhiyuan Ren,et al.  Sentry-Based Power Management in Wireless Sensor Networks , 2003, IPSN.

[7]  Mani B. Srivastava,et al.  Critical density thresholds for coverage in wireless sensor networks , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[8]  Ajit Narayanan,et al.  Quantum-inspired genetic algorithms , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[9]  Azzedine Boukerche,et al.  A Local Information Exchange Based Coverage-Preserving Protocol For Wireless Sensor Networks , 2006, 2006 IEEE International Conference on Communications.

[10]  Miodrag Potkonjak,et al.  Worst and best-case coverage in sensor networks , 2005, IEEE Transactions on Mobile Computing.

[11]  Azzedine Boukerche,et al.  A new energy efficient and fault-tolerant protocol for data propagation in Smart Dust networks using varying transmission range , 2004 .

[12]  Yu-Chee Tseng,et al.  The Coverage Problem in a Wireless Sensor Network , 2005, Mob. Networks Appl..

[13]  Jong-Hwan Kim,et al.  Quantum-inspired evolutionary algorithm for a class of combinatorial optimization , 2002, IEEE Trans. Evol. Comput..

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

[15]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[16]  Azzedine Boukerche,et al.  A new energy efficient and fault-tolerant protocol for data propagation in Smart Dust networks using varying transmission range , 2004, 37th Annual Simulation Symposium, 2004. Proceedings..

[17]  Lov K. Grover A fast quantum mechanical algorithm for database search , 1996, STOC '96.

[18]  Robert Tappan Morris,et al.  Span: An Energy-Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks , 2002, Wirel. Networks.

[19]  Miodrag Potkonjak,et al.  Coverage problems in wireless ad-hoc sensor networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[20]  Hakan Deliç,et al.  Finding sensing coverage and breach paths in surveillance wireless sensor networks , 2004, 2004 IEEE 15th International Symposium on Personal, Indoor and Mobile Radio Communications (IEEE Cat. No.04TH8754).

[21]  Deborah Estrin,et al.  ASCENT: adaptive self-configuring sensor networks topologies , 2004, IEEE Transactions on Mobile Computing.

[22]  Songwu Lu,et al.  PEAS: a robust energy conserving protocol for long-lived sensor networks , 2003, 23rd International Conference on Distributed Computing Systems, 2003. Proceedings..

[23]  Peter W. Shor,et al.  Algorithms for quantum computation: discrete logarithms and factoring , 1994, Proceedings 35th Annual Symposium on Foundations of Computer Science.