Vibration-to-electric energy conversion
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special issue on low power electronics and design
Design considerations for solar energy harvesting wireless embedded systems
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Resource allocation and cross-layer control in wireless networks
Foundations and Trends® in Networking
The impact of imperfect scheduling on cross-layer congestion control in wireless networks
IEEE/ACM Transactions on Networking (TON)
Energy-aware routing in sensor networks: A large system approach
Ad Hoc Networks
Fidelity and yield in a volcano monitoring sensor network
OSDI '06 Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7
Power management in energy harvesting sensor networks
ACM Transactions on Embedded Computing Systems (TECS) - Special Section LCTES'05
Fairness and optimal stochastic control for heterogeneous networks
IEEE/ACM Transactions on Networking (TON)
Challenge: ultra-low-power energy-harvesting active networked tags (EnHANTs)
Proceedings of the 15th annual international conference on Mobile computing and networking
Control of wireless networks with rechargeable batteries
IEEE Transactions on Wireless Communications
Optimal energy management policies for energy harvesting sensor nodes
IEEE Transactions on Wireless Communications
Energy optimal control for time-varying wireless networks
IEEE Transactions on Information Theory
Optimal Energy and Delay Tradeoffs for Multiuser Wireless Downlinks
IEEE Transactions on Information Theory
Opportunistic networking: data forwarding in disconnected mobile ad hoc networks
IEEE Communications Magazine
LIFO-backpressure achieves near-optimal utility-delay tradeoff
IEEE/ACM Transactions on Networking (TON)
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In this paper, we show how to achieve close-to-optimal utility performance in energy harvesting networks with only finite capacity energy storage devices. In these networks, nodes are capable of harvesting energy from the environment. The amount of energy that can be harvested is time varying and evolves according to some probability law. We develop an online algorithm, called the Energy-limited Scheduling Algorithm (ESA), which jointly manages the energy and makes power allocation decisions for packet transmissions. ESA only has to keep track of the amount of energy left at the network nodes and does not require any knowledge of the harvestable energy process. We show that ESA achieves a utility that is within O(ε) of the optimal, for any ε 0, while ensuring that the network congestion and the required capacity of the energy storage devices are deterministically upper bounded by bounds of size O(1/ε). We then also develop the Modified-ESA algorithm (MESA) to achieve the same O(ε) close-to-utility performance, with the average network congestion and the required capacity of the energy storage devices being only O([log(1/ε)]2).