Abstract
In pervasive computing environments, it is often required to cover a certain service area by a given deployment of nodes or access points. In case of large inaccessible areas, often the node deployment is random. In this paper, given a random uniform node distribution over a 2-D region, we propose a simple distributed solution for self-organized node placement to satisfy coverage of the given region of interest using least number of active nodes. We assume that the nodes are identical and each of them covers a circular area. To ensure coverage we tessellate the area with regular hexagons, and attempt to place a node at each vertex and the center of each hexagon termed as target points. By the proposed distributed algorithm, unique nodes are selected to fill up the target points mutually exclusively with limited displacement. Analysis and simulation studies show that proposed algorithm with less neighborhood information and simpler computation solves the coverage problem using minimum number of active nodes, and with minimum displacement in 95 % cases. Also, the process terminates in constant number of rounds only.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bartolini, N., Calamoneri, T., Fusco, E., Massini, A., Silvestri, S.: Push and pull: autonomous deployment of mobile sensors for a complete coverage. Wireless Netw. 16(3), 607–625 (2010)
Brass, P.: Bounds on coverage and target detection capabilities for models of networks of mobile sensors. ACM Trans. Sens. Netw. (TOSN) 3(2), 9 (2007)
Cheng, P., Chuah, C.N., Liu, X.: Energy-aware node placement in wireless sensor networks. In: Global Telecommunications Conference, GLOBECOM, vol. 5, pp. 3210–3214. IEEE (2004)
Han, Y.H., Kim, Y.H., Kim, W., Jeong, Y.S.: An energy-efficient self-deployment with the centroid-directed virtual force in mobile sensor networks. Simulation 88(10), 1152–1165 (2012)
Heo, N., Varshney, P.K.: An intelligent deployment and clustering algorithm for a distributed mobile sensor network. IEEE Int. Conf. Syst. Man Cybernet. 5, 4576–4581 (2003)
Ke, W.C., Liu, B.H., Tsai, M.J.: The critical-square-grid coverage problem in wireless sensor networks is np-complete. Comput. Netw. 55(9), 2209–2220 (2011)
Kukunuru, N., Thella, B.R., Davuluri, R.L.: Sensor deployment using particle swarm optimization. Int. J. Eng. Sci. Technol. 2(10), 5395–5401 (2010)
Liao, W.H., Kao, Y., Li, Y.S.: A sensor deployment approach using glowworm swarm optimization algorithm in wireless sensor networks. Expert Syst. Appl. 38(10), 12180–12188 (2011)
Luo, C.J., Tang, B., Zhou, M.T., Cao, Z.: Analysis of the wireless sensor networks efficient coverage. In: International Conference on Apperceiving Computing and Intelligence Analysis (ICACIA), pp. 194–197 (2010)
Poe, W.Y., Schmitt, J.B.: Node deployment in large wireless sensor networks: coverage, energy consumption, and worst-case delay. In: Conference on Asian Internet Engineering. pp. 77–84. AINTEC, ACM, USA (2009)
Saha, D., Das, N., Bhattacharya, B.B.: Fast estimation of coverage area in a pervasive computing environment. In: Advanced Computing, Networking and Informatics, vols. 2, 28, pp. 19–27. Springer (2014)
Saha, D., Das, N., Pal, S.: A digital-geometric approach for computing area coverage in wireless sensor networks. In: 10th International Conference on Distributed Computing and Internet Technologies (ICDCIT), pp. 134–145. Springer (2014)
Saha, D., Das, N.: Distributed area coverage by connected set cover partitioning in wireless sensor networks. In: First International Workshop on Sustainable Monitoring through Cyber-Physical Systems (SuMo-CPS), ICDCN. India (2013)
Saha, D., Das, N.: A fast fault tolerant partitioning algorithm for wireless sensor networks. In: Third International Conference on Advances in Computing and Information Technology (ACITY). pp. 227–237. CSIT, India (2013)
Sheu, J.P., Yu, C.H., Tu, S.C.: A distributed protocol for query execution in sensor networks. In: IEEE Wireless Communications and Networking Conference, vol. 3, pp. 1824–1829 (2005)
Wang, G., Cao, G., Porta, T.L.: Movement-assisted sensor deployment. IEEE Trans. Mob. Comput. 5(6), 640–652 (2006)
Wang, X., Wang, S., Ma, J.J.: An improved co-evolutionary particle swarm optimization for wireless sensor networks with dynamic deployment. Sensors 7(3), 354–370 (2007)
Yu, X., Huang, W., Lan, J., Qian, X.: A van der Waals force-like node deployment algorithm for wireless sensor network. In: 8th International Conference on Mobile Ad-hoc and Sensor Networks (MSN), pp. 191–194. IEEE (2012)
Yu, X., Liu, N., Huang, W., Qian, X., Zhang, T.: A node deployment algorithm based on van der Waals force in wireless sensor networks. Distrib. Sens. Netw. 3, 1–8 (2013)
Zou, Y., Chakrabarty, K.: Sensor deployment and target localization based on virtual forces. In: Twenty-Second Annual Joint Conference of the IEEE Computer and Communications (INFOCOM). vol. 2, pp. 1293–1303 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer India
About this paper
Cite this paper
Saha, D., Das, N. (2016). Self-Organized Node Placement for Area Coverage in Pervasive Computing Networks. In: Nagar, A., Mohapatra, D., Chaki, N. (eds) Proceedings of 3rd International Conference on Advanced Computing, Networking and Informatics. Smart Innovation, Systems and Technologies, vol 43. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2538-6_38
Download citation
DOI: https://doi.org/10.1007/978-81-322-2538-6_38
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-2537-9
Online ISBN: 978-81-322-2538-6
eBook Packages: EngineeringEngineering (R0)