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Target tracking is one of the most popular applications of the wireless sensor networks. It can be accomplished using different approaches and algorithms, one of which is the spatiotemporal multicast protocol, called “mobicast”. In this protocol, it is assumed that the area around the moving target, called the delivery zone, is known at any given time during the operation of the network. The aim of the protocol is to awake sensor nodes, which will be within the delivery zone in the near future, to be prepared for tracking the approaching moving target. In this paper, we propose a novel mobicast algorithm, aiming at reducing the number of awakened sensor nodes. To this end, we equipped every sensor node with a learning automaton, which helps the node in determining the sensor nodes it must awaken. To evaluate the performance of the proposed algorithm, several experiments have been conducted. The results have shown that the proposed algorithm can significantly outperform other existing algorithms such as forward-zone constrained and FAR in terms of energy consumption, number of active nodes, number of exchanged packets and slack time.
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- Learning Automata Based Face-Aware Mobicast
S. M. Safavi
M. R. Meybodi
- Springer US
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