Dynamic Node Deployment and Cross Layer Opportunistic Robust Routing for PoI Coverage Using WSNs
- 70 Downloads
Point of interest (PoI) coverage is a potential application of mobile wireless sensor networks. The paper presents planar localised Delaunay triangulation (PLDT) based algorithm for self-deployment of sensor nodes for PoI coverage and optimise the data forwarding from PoI to sink. The deployment algorithm used to cover a PoI maintains connectivity all along the deployment. PLDT provides connectivity as well as path robustness compared to relative neighbourhood graphs (RNG) based straight line deployment strategy. But PLDT based path from PoI to sink has more number of hops as against RNG based path. To minimize the number of hops a cross-layer opportunistic robust routing protocol (CORRP) is designed and been used. CORRP uses request-to-send–clear-to-send (RTS–CTS) handshaking mechanism to select a forwarder amongst the contending nodes with minimal overheads. Performance of scheme is evaluated for PoI coverage with respect to time and distance.It is observed that the scheme adequately covers the PoI in finite time. The upper and lower bound on number of hops under zero loss and network failure conditions are estimated. Compared to RNG-based straight line deployment, simulation results show that PLDT deployment with CORRP exhibits better performance in the range of 40–10% for energy consumption and 12% for packet reception approximately for increasing value of node sleeping probability. Also the energy consumption under lossy links is less by 40% compared to RNG-based straight line deployment. Thus PLDT based deployment and forwarding with CORRP exhibits improvement for energy consumption, packet reception and ensures robustness.
KeywordsPoint of interest Mobile wireless sensor networks Robust opportunistic routing
This work is supported through a research grant from Rajiv Gandhi Science and Technology Commission (RGSTC) (Grant No. 2013), Government of Maharashtra, India for research project to establish a system for monitoring air quality for vehicular pollutant using wireless sensor networks. The authors are thankful for the support extended by RGSTC, Government of Maharashtra.
- 2.Batalin, M. A., & Sukhatme, G. S. (2002). Spreading out: A local approach to multi-robot coverage In Proceedings of sixth international symposium on distributed autonomous robotic systems (pp. 373–382).Google Scholar
- 3.Bose, P., Devroye, L., Evans, W., & Kirkpatrick, D. (2002). On the spanning ratio of gabriel graphs and beta-skeletons. In Proceedings of Latin American theoretical informatics conference.Google Scholar
- 4.Busse, M., Haenselmann, T., & Effelsberg, W. (2006). Energy-efficient forwarding schemes for wireless sensor networks. In: Mobile and multimedia networks (WoWMoM): Proceedings of international symposium on a world of wireless (pp. 125–133).Google Scholar
- 6.Cheng, W., Li, M., Liu, K., Liu, Y., Li, X., & Liao, X. (2008). Sweep coverage with mobile sensors. In Proceedings of IEEE international parallel and distributed processing symposium (IPDPS) (pp. 1–9).Google Scholar
- 7.Chew, P. L. (1986). There is a planar graph as good as the complete graph. In Proceedings of second symposium on computational geometry (pp. 169–177).Google Scholar
- 9.Dhilon, S. S., Chakrabarty, K., & Iyengar, S. S. (2002). Sensor placement for grid coverage under imprecise detections. In Proceedings of 5th international conference information fusion (FUSION02) (pp. 1–10), Annapolis, MD, July 2002.Google Scholar
- 12.Gage, D. W. (1992). Command control for many-robot systems. In Proceedings of 19th annual AUVS technical symposium. Reprinted in unmanned systems magazine (Vol. 10, No. 4, pp. 28–34).Google Scholar
- 13.Ghosh, A., & Das, S. K. (2006). Coverage and connectivity issues in wireless sensor networks. In R. Shorey, A. L. Ananda, M. C. Chan, & W. T. Ooi (Eds.), Mobile, Wireless and Sensor Networks: Technology, Applications and Future Directions (chap. 9, pp. 221–255). Wiley. doi: 10.1002/0471755591.
- 14.Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of 33rd Hawaii international conference system sciences (pp. 4–7).Google Scholar
- 16.Heo, N., & Varshney, P. K. (2003). A distributed self-spreading algorithm for mobile wireless sensor networks. In Proceedings of IEEE Wireless Communications and Networking Conference (WCNC03) (pp. 1597–1602). New Orleans, LA.Google Scholar
- 17.Howard, A., & Mataric, M. J. (2002). Cover me! A self-deployment algorithm for mobile sensor networks. In Proceedings of IEEE international conference robotics and automation (ICRA02) (pp. 80–91). Washington, DC.Google Scholar
- 20.Keil, J. M., & Gutwin, C. A. (1989). The delaunay triangulation closely approximates the complete euclidean graph. In Proceedings of first workshop algorithms data structure.Google Scholar
- 27.Mainwaring, A., Polastre, J., Szewczyk, R., Culler, D., & Anderson, J. (2002). Wireless sensor networks for habitat monitoring. In Proceedings of 1st ACM international workshop on wireless sensor networks and applications (WSNA02) (pp. 88–97). Atlanta, GA.Google Scholar
- 28.Meguerdichian, S., Koushanfar, F., Qu, G., & Potkonjak, M. (2001). Exposure in wire less ad-hoc sensor networks. In Proceedings of 7th annual international conference mobile computing and networking (pp. 139–150). Rome, Italy.Google Scholar
- 29.Meguerdifor, S. (2001). Improving network coverage in wireless sensor networks, chian, F. Koushanfar, M. Potkonjak, M. Srivastava, Coverage problems in wireless ad-hoc sensor networks. In Proceedings of IEEE InfoCom (InfoCom01) (pp. 115–121). Anchorage, AK.Google Scholar
- 30.Poduri, S., & Sukhatme, G. S. (2004). Constrained coverage in mobile sensor networks. In Proceedings IEEE International Conference Robotics and Automation (ICRA04) (pp. 40–50). New Orleans, LA.Google Scholar
- 31.Satyanarayana, D., & Rao, S. V. (2008). Constrained delaunay triangulation for ad hoc networks. Journal of Computer Systems, Networks, and Communications, 2008, Article ID 160453. doi: 10.1155/2008/160453.
- 32.Stemm, M., & Katz, R. H. (1997). Measuring and reducing energy consumption of network interfaces in hand-held devices. IEICE Transactions on Communications, E80-B(8), 1125–1131.Google Scholar
- 33.Veltri, G., Huang, Q., Qu, G., & Potkonjak, M. (2003). Minimal and maximal exposure path algorithms for wireless embedded sensor networks. In: Proceedings of 1st international conference embedded networked sensor systems (SenSys03) (pp. 40–50). Los Angeles.Google Scholar
- 34.Wang, G., Cao, G., & LaPorta, T. (2003). A bidding protocol for deploying mobile sensors. In Proceedings of 11th IEEE international conference network protocols (ICNP03) (pp. 80–91). Atlanta, GA.Google Scholar
- 35.Wang, G., Cao, G., & LaPorta, T. (2004). Movement-assisted sensor deployment. In Proceedings of IEEE InfoCom (InfoCom04) (pp. 80–91). Hong Kong.Google Scholar
- 38.Xi, M., Qi, Y., Wu, K., Zhao, J., & Li, M. (2011). Using potential to guide mobile nodes in wireless sensor networks. Ad Hoc and Sensor Wireless Networks, 12(3/4), 229–251.Google Scholar
- 42.Zou, Y. & Chakrabarty, K. (2003). Sensor deployment and target localization based on virtual forces. In Proceedings of IEEE InfoCom (InfoCom03) (pp. 1293–1303). San Francisco, CA.Google Scholar
- 43.Zou, Y., & Chakrabarty, K. (2003) Uncertainty-aware sensor deployment algorithms for surveillance applications. In Proceedings of IEEE global communications conference (GLOBECOM03).Google Scholar