Abstract
Advances in directional sensors technology and impressive development of wireless sensor networks, created a new class of wireless sensor networks called directional sensor networks. According to the nature of directional nodes, the coverage problem in directional sensor networks is substantial. The coverage measurement in the directional sensor network can be positional or temporal. In temporal coverage, directional sensors periodically repeat rotating around themselves. Therefore in each period of time, targets that exist in the radius of sensor nodes are covered in the interval of time. In this model, when a target has not been covered by sensors in any interval of time, it is said that the target has remained in dark. Temporal coverage model is defined by minimizing dark time for all targets. This paper presents two solutions for solving the temporal coverage problem. The first solution formulates the problem of temporal coverage as an integer linear programming (ILP) optimization problem. By using this method, the optimal solution can be achieved for temporal coverage problem. Due to NP-Hardness of temporal coverage problem and since ILP is a centralized method, we develop a heuristics solution, namely distributed initial orientation algorithm (DIOA). This algorithm uses local information and tries to be near-optimal. Simulation results show that in ILP, we have up to 14.19% reduction on average sum of dark time and in DIOA we have up to 6.74%. Additionally, the number of perfect temporal coverage (0-dark time) in ILP method improves up to 69.29% and in DIOA we have up to 25.23% improvements compared to related algorithms.












Similar content being viewed by others
References
Akyildiz, I. F., Melodia, T., & Chowdhury, K. R. (2007). A survey on wireless multimedia sensor networks. Computer Networks, 51, 921–960.
Guvensan, M. A., & Yavuz, A. G. (2011). On coverage issues in directional sensor networks: A survey. Ad Hoc Networks, 9, 1238–1255.
Akyildiz, I. F., & Vuran, M. C. (2010). Wireless sensor networks (Vol. 4). New York: Wiley.
Soro, S., & Heinzelman, W. (2009). A survey of visual sensor networks. Advances in Multimedia, 2009, 1–22.
Yap, F. G., & Yen, H.-H. (2014). A survey on sensor coverage and visual data capturing/processing/transmission in wireless visual sensor networks. Sensors, 14, 3506–3527.
Wang, Y.-C., & Hsu, S.-E. (2015). Deploying R&D sensors to monitor heterogeneous objects and accomplish temporal coverage. Pervasive and Mobile Computing, 21, 30–46.
Wang, Y.-C., & Hsu, S.-E. (2014) An efficient deployment heuristic to support temporal coverage of heterogeneous objects in rotatable and directional (R&D) sensor networks. In 2014 IEEE 80th vehicular technology conference (VTC Fall) (pp. 1–5).
Fusco, G., & Gupta, H. (2010). Placement and orientation of rotating directional sensors. In 2010 7th annual IEEE communications society conference on sensor mesh and ad hoc communications and networks (SECON) (pp. 1–9).
Wang, Y.-C., Chen, Y.-F., & Tseng, Y.-C. (2012). Using rotatable and directional (R&D) sensors to achieve temporal coverage of objects and its surveillance application. IEEE Transactions on Mobile Computing, 11, 1358–1371.
Khanjary, M., Sabaei, M., & Meybodi, M. R. (2017). Critical Density in Adjustable-Orientation Directional Sensor Networks Using Continuum Percolation. Procedia Computer Science, 116, 548–555.
Aghdasi, H. S., & Abbaspour, M. (2016). Energy efficient area coverage by evolutionary camera node scheduling algorithms in visual sensor networks. Soft Computing, 20(3), 1191–1202.
Cheng, W., Li, S., Liao, X., Changxiang, S., & Chen, H. (2007). Maximal coverage scheduling in randomly deployed directional sensor networks. In International conference on parallel processing workshops, 2007. ICPPW 2007 (p. 68).
Liang, C.-K., Tsai, C.-H., & He, M.-C. (2011). On area coverage problems in directional sensor networks. In 2011 international conference on information networking (ICOIN) (pp. 182–187).
Hooshmand, M., Soroushmehr, S. M. R., Khadivi, P., Samavi, S., & Shirani, S. (2013). Visual sensor network lifetime maximization by prioritized scheduling of nodes. Journal of Network and Computer Applications, 36, 409–419.
Sharmin, S., Nur, F. N., Razzaque, M. A., Rahman, M. M., Alelaiwi, A., Hassan, M. M., et al. (2017). α-overlapping area coverage for clustered directional sensor networks. Computer Communications, 109, 89–103.
Munishwar, V. P., & Abu-Ghazaleh, N. B. (2013). Coverage algorithms for visual sensor networks. ACM Transactions on Sensor Networks (TOSN), 9, 45.
Ai, J., & Abouzeid, A. A. (2006). Coverage by directional sensors in randomly deployed wireless sensor networks. Journal of Combinatorial Optimization, 11, 21–41.
Aghdasi, H. S. (2013). Energy and Quality of information aware coverage in multitire visual sensor networks., Ph.D. Department of Electrical & Computer Engineering, Shahid Beheshti University.
Mostafavi, S. A., & Dehghan, M. (2011). Optimal visual sensor placement for coverage based on target location profile. Ad Hoc Networks, 9, 528–541.
Garcia, M. A., & Solanas, A. (2004). 3D simultaneous localization and modeling from stereo vision. In 2004 IEEE international conference on robotics and automation, 2004. Proceedings. ICRA’04 (pp. 847–853).
Barton-Sweeney, A., Lymberopoulos, D., & Savvides, A. (2006). Sensor localization and camera calibration in distributed camera sensor networks. In 3rd international conference on broadband communications, networks and systems, 2006. BROADNETS 2006 (pp. 1–10).
I. V. ILOG Inc., NV. https://www.ibm.com/products/ilog-cplex-optimization-studio. Accessed 26 Jan 2019.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Esmaeilzadeh, R., Abbaspour, M. Optimum Temporal Coverage with Rotating Directional Sensors. Wireless Pers Commun 105, 369–386 (2019). https://doi.org/10.1007/s11277-019-06117-3
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-019-06117-3