Next century challenges: mobile networking for “Smart Dust”
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Dynamic fine-grained localization in Ad-Hoc networks of sensors
Proceedings of the 7th annual international conference on Mobile computing and networking
Bio-Inspired Mobility in Environment Aware Wireless Sensor Networks
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Event-Based Motion Control for Mobile-Sensor Networks
IEEE Pervasive Computing
IEEE Communications Magazine
Restoration of coverage blind spots in wireless sensor networks based on ant colony algorithm
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
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Sensor networks consist of small wireless sensor nodes deployed randomly over an area to monitor the environment or detect intrusion. The coverage provided by sensor networks is very crucial to their effectiveness. Many of the important applications of sensor networks demand autonomous mobility for the sensor nodes. Early failure of sensor nodes can lead to coverage loss that requires coverage maintenance schemes. In this paper, we propose Dynamic Coverage Maintenance (DCM) schemes that exploit the limited mobility of the sensor nodes. The main objective of coverage maintenance is to compensate the loss of coverage with minimum expenditure of energy. Existing autonomous sensor deployment schemes such as the ''potential field approach'' are not useful for DCM because the nodes initially distribute themselves such that there is no redundancy in coverage. We propose a set of DCM schemes which can be executed on individual sensor nodes having a knowledge of only their local neighborhood topology. The process of moving a node to a new location for maintenance of coverage is termed ''migration''. We propose four algorithms to decide which neighbors to migrate, and to what distance, such that the energy expended is minimized and the coverage obtained for a given number of live nodes is maximized. The decision and movement are completely autonomous in the network, and involves movement of one-hop neighbors of a dead sensor node. We also propose an extension to these algorithms, called Cascaded DCM, which extends the migrations to multiple hops. We have developed a graphical simulator Java Sensor Simulator (JSS) to visually inspect the working of the algorithms. We have also compared the performance of the different algorithms in terms of the improvement in coverage, average migration distance of the nodes, and the lifetime of the network. Cascaded DCM was seen to offer the maximum network lifetime and coverage.