Affiliation:
1. School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0250, USA
Abstract
We present a Markovian decision process (MDP) framework for multihop wireless sensor networks (MHWSNs) to bound the network performance of both energy constrained (EC) networks and energy harvesting (EH) networks, both with and without relay cooperation. The model provides the fundamental performance limit that a MHWSN can theoretically achieve, under the general constraints from medium access control, routing, and energy harvesting. We observe that the analyses for EC and EH networks fall into two branches of MDP theory, which are finite-horizon process and infinite-horizon process, respectively. The performance metrics for EC and EH networks are different. For EC networks, an appropriate metric is the network lifetime; for EH networks, an appropriate metric is, for example, the network throughput. To efficiently solve the models with high dimension, for the EC networks, we propose a novel computational algorithm by taking advantage of the stochastic shortest path structure of the problem; for the EH networks, we propose a dual linear programming based algorithm by considering the sparsity of the transition matrix. Under the unified MDP framework, numerical results demonstrate the advantages of cooperation for the optimal performance, in both EC and EH networks.
Funder
National Science Foundation
Subject
Computer Networks and Communications,General Engineering
Cited by
3 articles.
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