DCOSS '09 Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems
Control-theoretic optimization of utility over mission lifetimes in multi-hop wireless networks
SECON'09 Proceedings of the 6th Annual IEEE communications society conference on Sensor, Mesh and Ad Hoc Communications and Networks
Control-theoretic, mission-driven, optimization techniques for wireless sensor networks
COMSNETS'09 Proceedings of the First international conference on COMmunication Systems And NETworks
An optimization based distributed algorithm for mobile data gathering in wireless sensor networks
INFOCOM'10 Proceedings of the 29th conference on Information communications
AINTEC'06 Proceedings of the Second Asian international conference on Technologies for Advanced Heterogeneous Networks
Control-theoretic utility maximization in multihop wireless networks under mission dynamics
IEEE/ACM Transactions on Networking (TON)
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In many energy-rechargeable wireless sensor net-works, sensor nodes must both sense data from the environment, and cooperativelyforward sensed data to data sinks. Both data sensing and data forwarding (including data transmission and reception) consumeenergy at sensor nodes. We present a distributed algorithm for optimal joint allocation of energy between sensing and communicationat each node to maximize overall system utility (i.e., the aggregate amount of information received at the data sinks). Weconsider this problem in the context of wireless sensor networks with directional, non-steerable antennas. We first formulatea joint data-sensing and data-routing optimization problem with both per-node energy-expenditure constraints, and traditionalflow routing/conservation constraints. We then simplify this problem by converting it to an equivalent routing problem, andpresent a distributed gradient-based algorithm that iteratively adjusts the per-node amount of energy allocated between sensingand communication to reach the system-wide optimum. We prove that our algorithm converges to the maximum system utility. Wequantitatively demonstrate the energy balance achieved by this algorithm in a network of small, energy-constrained X-bandradars, connected via point-to-point 802.11 links with non-steerable directional antennas.