Lifetime enhancement in wireless sensor and actuator network using uniform energy consumption algorithm

This paper studies the moving path planning problem of mobile actuator in delay-constrained wireless sensor and actuator networks. We consider a real-time scenario for mission-critical applications, where the data gathering must be performed within a specified latency constraint. To maximise the network lifetime subject to the delay constraint, we construct an energy-efficient shortest path tree in which the sensors’ residual energy is taken into consideration. Then, based on the shortest path tree, we present a dynamic cost algorithm in which the sensor with more energy has higher possibility to be selected as polling point. Finally, the moving path of mobile actuator is determined by solving the travelling salesman problem including all the polling points. The effectiveness of our algorithm is validated by extensive simulations.

[1]  A. Manjeshwar,et al.  TEEN: a routing protocol for enhanced efficiency in wireless sensor networks , 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.

[2]  Samir Khuller,et al.  A coordinated data collection approach: design, evaluation, and comparison , 2004, IEEE Journal on Selected Areas in Communications.

[3]  Jie Wu,et al.  On Maximizing the Lifetime of Wireless Sensor Networks Using Virtual Backbone Scheduling , 2012, IEEE Transactions on Parallel and Distributed Systems.

[4]  Anna Scaglione,et al.  On the Interdependence of Routing and Data Compression in Multi-Hop Sensor Networks , 2002, MobiCom '02.

[5]  Guoliang Xing,et al.  Rendezvous design algorithms for wireless sensor networks with a mobile base station , 2008, MobiHoc '08.

[6]  Ossama Younis,et al.  Distributed clustering in ad-hoc sensor networks: a hybrid, energy-efficient approach , 2004, IEEE INFOCOM 2004.

[7]  Yuanyuan Yang,et al.  Data gathering in wireless sensor networks with mobile collectors , 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

[8]  R. K. Shyamasundar,et al.  Introduction to algorithms , 1996 .

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

[10]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[11]  Guoliang Xing,et al.  Efficient Rendezvous Algorithms for Mobility-Enabled Wireless Sensor Networks , 2012, IEEE Transactions on Mobile Computing.

[12]  Yuanyuan Yang,et al.  Bounded relay hop mobile data gathering in wireless sensor networks , 2009, 2009 IEEE 6th International Conference on Mobile Adhoc and Sensor Systems.

[13]  James M. Keller,et al.  A fuzzy K-nearest neighbor algorithm , 1985, IEEE Transactions on Systems, Man, and Cybernetics.