Abstract
In this paper, we develop a real-time adaptive task allocation algorithm based on parallel dynamic coalition in WSNs. The algorithm gives a priority level to each task according to the idea of EDF. And the task with relatively higher priority will be scheduled firstly. When coalitions are parallel generated through PSO algorithm, the corresponding task of coalition will be allocated according to the current load of sensors and the remaining energy balance degree. The experimental results show that the proposed algorithm has strong capability to meet deadline constraint and it can prolong the lifetime of the whole network significantly.
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References
Abdelhak, S., Gurram, C.S., Ghosh, S., Bayoumi, M.: Energy-balancing task allocation on wireless sensor networks for extending the lifetime. In: Proceedings of IEEE International 53rd Midwest Symposium on Circuits and Systems, Seattle, pp. 781–784 (2010)
Zeng, Z.W., Liu, A.F., Li, D., Long, J.: A highly efficient DAG task scheduling algorithm for wireless sensor networks. In: Proceedings of the 9th International Conference for Young Computer Scientists, Hunan, China, pp. 570–575 (2008)
Tian, Y., Boangoat, J., Ekici, E., Ozguner, F.: Real-time task mapping and scheduling for collaborative in-network processing in DVS-enabled wireless sensor networks. In: Proceedings of Parallel and Distributed Processing Symposium, Rhodes Island, Greece (2006)
Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H.: An Application Specific Protocol Architecture for Wireless Micro-sensor Networks. IEEE Transactions on Wireless Communications 1, 660–670 (2002)
Younis, M., Munshi, P., Al-Shaer, E.S.: Architecture for efficient monitoring and management of sensor networks. In: Marshall, A., Agoulmine, N. (eds.) MMNS 2003. LNCS, vol. 2839, pp. 488–502. Springer, Heidelberg (2003)
Zhang, G.F., Jiang, J.G., Xia, N., Su, Z.P.: Solutions of Complicated Coalition Generation Based on Discrete Particle Swarm Optimization. Acta Electronica Sinica 35 (2007)
Kennedy, J., Eberhart, R.C.: A discrete binary version of the particle swarm optimization algorithm. In: Proceedings of the IEEE Conference on Systems, Man, and Cybernetics, Orlando, vol. 5, pp. 4104–4109 (1997)
Guo, W.Z., Gao, H.L., Chen, G.L., Yu, L.: Particle Swarm Optimization for the Degree-constrained MST problem in WSN Topology Control. In: The International Conference on Machine Learning and Cybernetics, Baoding China, vol. 7, pp. 1793–1798 (2009)
Shi, Y., Eberhart, R.C.: A modified particle swarm optimizer. In: Proceedings of the IEEE International Conference on Evolutionary Computation, Piscataway, pp. 69–73 (1998)
Chetto, H., Chetto, M.: Some Results of the Earliest Deadline Scheduling Algorithm. IEEE Transaction on Software Engineering 15 (1989)
Lesser, V., Ortiz, C.L., Tambe, M.: Distributed sensor networks: a multiagent perspective. Kluwer Academic Publishers (2003)
Armstrong, R., Hensgen, D., Kidd, T.: The relative performance of various mapping algorithms is independent of sizable variances in run-time predictions. In: Proceedings of the 7th IEEE Heterogeneous Computing Workshop, pp. 79–87 (1998)
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Chen, C., Guo, W., Chen, G. (2011). Real-Time Adaptive Task Allocation Algorithm with Parallel Dynamic Coalition in Wireless Sensor Networks. In: Wang, Y., Li, T. (eds) Knowledge Engineering and Management. Advances in Intelligent and Soft Computing, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25661-5_4
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DOI: https://doi.org/10.1007/978-3-642-25661-5_4
Publisher Name: Springer, Berlin, Heidelberg
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