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Author(s):
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Neda Edalat, National University of Singapore ; Wendong Xiao, Institute for Infocomm Research; Chen-Khong Tham, National University of Singapore; Ehsan Keikha, National University of Singapore; Lee-Ling Ong, National University of Singapore
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Abstract:
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Applications for Wireless Sensor Networks may be decomposed into the deployment of tasks on different sensor nodes in the network. Task allocation algorithms assign these tasks to specific sensor nodes in the network for execution. Given the resource-constrained and distributed nature of Wireless Sensor Netwoks (WSNs), existing static (offline) task scheduling may not be practical. Therefore there is a need for an adaptive task allocation scheme that accounts for the characteristics of the WSN environment such as unexpected communication delay and node failure. In this paper, we focus on task allocation in WSNs which is performed with the aim of achieving a fair energy balance amongst the sensor nodes while minimizing delay using a marketbased architecture. In this architecture, nodes are modeled as sellers communicating a deployment price for a task to the consumers. To address this task allocation problem, proposed price formulation is used as it continuously adapts to changes of the availabilities of resources. This scheme also accommodates for the node failure during task assignment. Three message exchanged mechanisms between the nodes (sellers) and task allocator (consumer) are proposed with the goal of reducing overhead, energy consumption and latency response time of selecting the winning node. Simulation results show that, compared with a static scheduling scheme with an objective in energy balancing, the proposed scheme adapts to new environmental changes and uncertain network condition more dynamically and achieves a much better performance on energy balancing.
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