Abstract

Wireless sensor actor networks are composed of sensor and actor nodes wherein sensor nodes outnumber resource-rich actor nodes. Sensor nodes gather information and send them to a central node (sink) and/or to actors for proper actions. The short lifetime of energy-constrained sensor nodes can endanger the proper operation of the whole network when they run out of power and partition the network. Energy harvesting as well as minimizing sensor energy consumption had already been studied. We propose a different approach for recharging sensor nodes by mobile actor nodes that use only local information. Sensor nodes send their energy status along with their sensed information to actors in their coverage. Based on this energy information, actors coordinate implicitly to decide on the timings and the ordering of recharges of low energy sensor nodes. Coordination between actors is achieved by swarm intelligence and the replenishment continues during local learning of actor nodes. The number of actors required to keep up such networks is identified through simulation using VisualSense. It is shown that defining the appropriate number of actor nodes is critical to the success of recharging strategies in prolonging the network lifetime.

Highlights

  • Wireless sensor and actor networks (WSANs) are made of two types of nodes called sensor nodes and actors

  • Coordination between actors is achieved by swarm intelligence and the replenishment continues during local learning of actor nodes

  • In this paper we introduced a new approach for energy replenishment of sensor nodes by mobile actor nodes in wireless sensor and actor networks

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Summary

Introduction

Wireless sensor and actor networks (WSANs) are made of two types of nodes called sensor nodes and actors. In WSANs a large number of sensor nodes are randomly deployed in a target area, may be in the order of hundreds or thousands, to perform a coordinated sensing task. Such a dense deployment is usually not necessary for actor nodes because actors are sophisticated devices with higher capabilities that can act on wider areas. A sensor node without energy cannot do its duties unless the source of energy is recharged or changed Since such networks are usually deployed in large scales and for a long period of time, human intervention for replenishment of energy is not feasible.

Related Work
Energy Harvesting Through Actor Nodes
11 For each node Є EnergyList
Experimental Validation
Findings
Conclusions and Future Work
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