Efficient target tracking in directional sensor networks with selective target area’s coverage
- 73 Downloads
Wireless sensor networks (WSNs) are employed in a variety of applications. One of the key applications of WSNs, which gained much attention, is the target tracking. Directional sensor networks (DSNs) are a subset of WSNs with some unique characteristics. Since optimizing the tracking system under the energy and coverage constraints in DSNs is of paramount importance, in this paper, we introduce a reliable algorithm for tracking mobile targets using directional WSNs. First, by selecting a minimum set of boundary and borderline sensor nodes, we achieve the desired coverage for an incoming detection. Second, for both deterministic ordered and random node deployments, we propose an efficient mechanism for determining the minimal interior sensor nodes that should be activated. Doing so, the network lifetime can be maximized by the employment of much fewer sensor nodes. Third, we use a geometric method for collecting data using two active sensors at a time. Accordingly, target position is estimated using the extended Kalman filter (EKF). Finally, we compare the proposed algorithm with a genetic algorithm and present the comparative simulation results of the EKF and the random walk. The results demonstrate the effectiveness of our proposed scheme in terms of the energy efficiency, coverage, and tracking accuracy.
KeywordsAngle of view Coverage Directional sensor network Extended Kalman filter Target tracking
We would like to thank the editor and reviewers for their constructive and valuable remarks.
- 1.Akyildiz, I. F., Weilian, S., Sankarasubramaniam, Y., & Cayirci, E. (2002). A survey on sensor networks. IEEE Communications Magazine. doi: 10.1109/MCOM.2002.1024422.
- 2.Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks. doi: 10.1016/j.comnet.2008.04.002.
- 3.Wang, Z., Lou, W., Wang, Z., Ma, J., & Chen, H. (2013). A hybrid cluster-based target tracking protocol for wireless sensor networks. International Journal of Distributed Sensor Networks. doi: 10.1155/2013/494863.
- 4.Mohamadi, H., Ismail, A. S., & Salleh, S. (2013). Utilizing distributed learning automata to solve the connected target coverage problem in directional sensor networks. Sensors and Actuators A: Physical. doi: 10.1016/j.sna.2013.03.034.
- 5.Guvensan, M. A., & Yavuz, A. G. (2011). On coverage issues in directional sensor networks: A survey. Ad Hoc Networks. doi: 10.1016/j.adhoc.2011.02.003.
- 6.Zhao, L., Bai, G., Jiang, Y., Shen, H., & Tang, Z. (2014). Optimal deployment and scheduling with directional sensors for energy-efficient barrier coverage. International Journal of Distributed Sensor Networks. doi: 10.1155/2014/596983.
- 7.Zhu, C., Zheng, C., Shu, L., & Han, G. (2012). A survey on coverage and connectivity issues in wireless sensor networks. Journal of Network and Computer Applications. doi: 10.1016/j.jnca.2011.11.016.
- 8.Mishra, S., Sharma, R., & Saxena, S. (2015). The issues of coverage in directional sensor network. International Journal of Computer Applications. doi: 10.5120/20188-2412.
- 9.Guvensan, M. A., & Yavuz, A. G. (2013). Hybrid movement strategy in self-orienting directional sensor networks. Ad Hoc Networks. doi: 10.1016/j.adhoc.2012.11.011.
- 10.Wang, Y. C., & Hsu, S. E. (2015). Deploying R&D sensors to monitor heterogeneous objects and accomplish temporal coverage. Pervasive and Mobile Computing. doi: 10.1016/j.pmcj.2015.04.002.
- 11.Rossi, A., Singh, A., & Sevaux, M. (2013). Lifetime maximization in wireless directional sensor network. European Journal of Operational Research. doi: 10.1016/j.ejor.2013.05.033.
- 12.Tan, W. M., & Jarvis, S. A. (2016). Heuristic solutions to the target identifiability problem in directional sensor networks. Journal of Network and Computer Applications. doi: 10.1016/j.jnca.2016.02.011.
- 13.Tan, W. M., & Jarvis, S. A. (2015). A distributed heuristic solution to the target identifiability problem in directional sensor networks. In International conference on IEEE computing, networking and communications (ICNC). doi: 10.1109/ICCNC.2015.7069337.
- 14.Mohamadi, H., Salleh, S., & Razali, M. N. (2014). Heuristic methods to maximize network lifetime in directional sensor networks with adjustable sensing ranges. Journal of Network and Computer Applications. doi: 10.1016/j.jnca.2014.07.038.
- 15.Wang, B., Zhu, J., Yang, L. T., & Mo, Y. (2016). Sensor density for confident information coverage in randomly deployed sensor networks. IEEE Transactions on Wireless Communications. doi: 10.1109/TWC.2016.2518689.
- 17.Jiang, B., Ravindran, B., & Cho, H. (2013). Probability-based prediction and sleep scheduling for energy-efficient target tracking in sensor networks. IEEE Transactions on Mobile Computing. doi: 10.1109/TMC.2012.44.
- 18.Sahoo, P. K., Sheu, J. P., & Hsieh, K. Y. (2013). Target tracking and boundary node selection algorithms of wireless sensor networks for internet services. Information Sciences. doi: 10.1016/j.ins.2012.07.034.
- 19.Zheng, J., Bhuiyan, M. Z. A., Liang, S., Xing, X., & Wang, G. (2014). Auction-based adaptive sensor activation algorithm for target tracking in wireless sensor networks. Future Generation Computer Systems. doi: 10.1016/j.future.2013.12.014.
- 21.Hu, X., Hu, Y. H., & Xu, B. (2014). Energy-balanced scheduling for target tracking in wireless sensor networks. ACM Transactions on Sensor Networks. doi: 10.1145/2629596.
- 22.Pino-Povedano, S., & González-Serrano, F. J. (2014). Comparison of optimization algorithms in the sensor selection for predictive target tracking. Ad Hoc Networks. doi: 10.1016/j.adhoc.2014.04.004.
- 23.Shi, K., Chen, H., & Lin, Y. (2015). Probabilistic coverage based sensor scheduling for target tracking sensor networks. Information Sciences. doi: 10.1016/j.ins.2014.08.067.
- 24.Khedr, A. M., & Osamy, W. (2011). Effective target tracking mechanism in a self-organizing wireless sensor network. Journal of Parallel and Distributed Computing. doi: 10.1016/j.jpdc.2011.06.001.
- 25.Vilela, J., Kashino, Z., Ly, R., Nejat, G., & Benhabib, B. (2016). A dynamic approach to sensor network deployment for mobile-target detection in unstructured. IEEE Sensors Journal Expanding Search Areas. doi: 10.1109/JSEN.2016.2537331.
- 26.Macwan, A., Vilela, J., Nejat, G., & Benhabib, B. (2015). A multirobot path-planning strategy for autonomous wilderness search and rescue. IEEE Transactions on Cybernetics. doi: 10.1109/TCYB.2014.2360368.
- 27.Aeron, S., Saligrama, V., & Castanon, D. A. (2008). Efficient sensor management policies for distributed target tracking in multihop sensor networks. IEEE Transactions on Signal Processing. doi: 10.1109/TSP.2007.912891.
- 28.Shen, X., & Varshney, P. K. (2014). Sensor selection based on generalized information gain for target tracking in large sensor networks. IEEE Transactions on Signal Processing. doi: 10.1109/TSP.2013.2289881.
- 29.Li, X., Li, Y. A., Liu, W., & Bai, X. (2014). Dual-array tracking algorithm for underwater bearing-only target tracking based on EKF. In Mechatronics and automatic control systems. Lecture notes in electrical engineering. doi: 10.1007/978-3-319-01273-5_22.
- 30.Arienzo, L., & Longo, M. (2010). Energy-efficient target tracking in sensor networks. Ad Hoc Networks. Lecture Notes of the Institute for Computer Sciences. Social Informatics and Telecommunications Engineering. doi: 10.1007/978-3-642-17994-5_17.
- 31.Kim, J. H., Kim, K. B., Hussain, C. S., Cui, M. W., & Park, M. S. (2008). Energy-efficient tracking of continuous objects in wireless sensor networks. ubiquitous intelligence and computing. Lecture Notes in Computer Science. doi: 10.1007/978-3-540-69293-5_26.
- 32.Zhong, C., & Worboys, M. (2007). Energy-efficient continuous boundary monitoring in sensor networks. Technical report.Google Scholar
- 33.Rahman, A. A. U., Naznin, M., & Mollah, M. A. I. (2010). Energy-efficient multiple targets tracking using target kinematics in wireless sensor networks. In Fourth international conference on sensor technologies and applications. Venice. doi: 10.1109/SENSORCOMM.2010.101.
- 34.Fuemmeler, J. A., & Veeravalli, V. V. (2010). Energy efficient multi-object tracking in sensor networks. IEEE Transactions on Signal Processing. doi: 10.1109/TSP.2010.2046896.
- 35.Atia, G. K., Veeravalli, V. V., & Fuemmeler, J. A. (2011). Sensor scheduling for energy-efficient target tracking in sensor networks. IEEE Transactions on Signal Processing. doi: 10.1109/TSP.2011.2160055.
- 36.Demigha, O., Hidouci, W. K., & Ahmed, T. (2013). On energy efficiency in collaborative target tracking in wireless sensor network: A review. IEEE Communication Surveys and Tutorials. doi: 10.1109/SURV.2012.042512.00030.
- 37.Guo, M., Olule, E., Wang, G., & Guo, S. (2010). Designing energy efficient target tracking protocol with quality monitoring in wireless sensor networks. The Journal of Supercomputing. doi: 10.1007/s11227-009-0278-5.
- 38.Sengupta, S., Das, S., Nasir, M. D., & Panigrahi, B. K. (2013). Multi-objective node deployment in WSNs: In search of an optimal trade-off among coverage. Lifetime. energy consumption, and connectivity. Engineering Applications of Artificial Intelligence. doi: 10.1016/j.engappai.2012.05.018.
- 39.Kaplan, L. M. (2006). Global node selection for localization in a distributed sensor network. IEEE Transactions Aerospace and Electronic Systems. doi: 10.1109/TAES.2006.1603409.
- 40.Singh, A., & Rossi, A. (2013). A genetic algorithm based exact approach for lifetime maximization of directional sensor networks. Ad Hoc Networks. doi: 10.1016/j.adhoc.2012.11.004.