Coverage-Enhancing Algorithm for Directional Sensor Networks
Adequate coverage is very important for sensor networks to fulfill the issued sensing tasks. In traditional sensor networks, the sensors are based on omni-sensing model. However, directional sensing sensors are with great application chances, typically in video sensor networks. Toward this end, this paper addresses the problem of enhancing coverage in a directional sensor network. First, based on a rotatable directional sensing model, we present a method to deterministically estimate the amount of directional nodes for a given coverage rate. We also employ Sensing Connected Sub-graph (SCSG) to divide a directional sensor network into several parts in a distributed manner, in order to decrease time complexity. Moreover, the concept of convex hull is introduced to model each sensing connected sub-graph. According to the characteristic of adjustable sensing directions of directional nodes, we study a coverage-enhancing algorithm to minimize the overlapping sensing area of directional sensors only with local topology information. Extensive simulation is conducted to verify the effectiveness of our solution and we give detailed discussions on the effects of different system parameters.
KeywordsSensor Network Wireless Sensor Network Convex Hull Area Coverage Coverage Rate
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- 2.Ma, H., Liu, Y.: Correlation Based Video Processing in Video Sensor Networks. In: IEEE WirelessCom 2005, Hawaii, June 13-15 (2005)Google Scholar
- 6.Feng, W., Code, B., Kaiser, E., Shea, M., Feng, W.: Panoptes: Scalable Low-power Video Sensor Networking Technologies. In: The 11th ACM International Conference on Multimedia, Berkeley, CA (November 2003)Google Scholar
- 7.Kulkarni, P., Ganesan, D., Shenoy, P., Lu, Q.: SensEye: A Multitier Camera Sensor Network. In: ACM MM 2005, Singapore (November 6-11, 2005)Google Scholar
- 9.Archana S., Manoj, B.S., Siva Ram Murthy, C.: Dynamic Coverage Maintenance Algorithms for Sensor Networks with Limited Mobility. In: The Third IEEE International Conference on Pervasive Computing and Communications, pp. 51–60 (2005) Google Scholar
- 10.Lu, J., Suda, T.: Coverage-aware Self-scheduling in Sensor Networks. In: 2003 IEEE 18th Annual Workshop on Computer Communications, pp. 117–123 (October 20-21, 2003) Google Scholar
- 11.Liu, B., Towsley, D.: A Study of the Coverage of Large-scale Sensor Networks. In: The Third IEEE International Conference on Mobile Ad-hoc and Sensor Systems, pp. 475–483 (2004)Google Scholar
- 12.Tian, D., Georganas, N.D.: A Coverage-preserving Node Scheduling Scheme for Large Wireless Sensor Networks. In: The First ACM International Workshop on Wireless Sensor Networks and Applications, pp. 32–41 (2002)Google Scholar
- 14.Ghosh, A.: Estimating Coverage Holes and Enhancing Coverage in Mixed Sensor Networks. In: The 29th Annual IEEE International Conference on Local Computer Networks, pp. 68–76 (November 16-18, 2004)Google Scholar
- 15.Howard, A., Mataric, M., Sukhatme, G.: Mobile Sensor Network Deployment using Potential Fields: A distributed scalable solution to the area coverage problem. In: The 6th International Conference on Distributed Autonomous Robotic Systems, Fukuoka, Japan, pp. 299–308 (June 2002)Google Scholar
- 16.Poduri, S., Sukhatme, G.S.: Constrained Coverage in Mobile Sensor Networks. In: IEEE International Conference on Robotics and Automation, New Orleans, LA, USA, pp. 40–50 (April/May 2004)Google Scholar
- 17.Kesidis, G., Konstantopoulos, T., Phoha, S.: Surveillance Coverage of Sensor Networks under a Random Mobility Strategy. IEEE Sensors (October 2003)Google Scholar
- 18.Graham, R.L.: An Efficient Algorithm for Determining the Convex Hull of a Planar Set. In: Info. Proc. Lett., pp. 132–133 (1972)Google Scholar