ESRT: event-to-sink reliable transport in wireless sensor networks
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
Utilizing Solar Power in Wireless Sensor Networks
LCN '03 Proceedings of the 28th Annual IEEE International Conference on Local Computer Networks
CODA: congestion detection and avoidance in sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Convex Optimization
Mitigating congestion in wireless sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Congestion control and fairness for many-to-one routing in sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
Heliomote: enabling long-lived sensor networks through solar energy harvesting
Proceedings of the 3rd international conference on Embedded networked sensor systems
Trio: enabling sustainable and scalable outdoor wireless sensor network deployments
Proceedings of the 5th international conference on Information processing in sensor networks
Perpetual environmentally powered sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Interference-aware fair rate control in wireless sensor networks
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Distributed self-tuning of sensor networks
Wireless Networks
Lexicographic Maxmin Fairness for Data Collection in Wireless Sensor Networks
IEEE Transactions on Mobile Computing
IEEE/ACM Transactions on Networking (TON)
Steady and fair rate allocation for rechargeable sensors in perpetual sensor networks
Proceedings of the 6th ACM conference on Embedded network sensor systems
Explicit and precise rate control for wireless sensor networks
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
A tutorial on decomposition methods for network utility maximization
IEEE Journal on Selected Areas in Communications
Joint mobile energy replenishment and data gathering in wireless rechargeable sensor networks
Proceedings of the 23rd International Teletraffic Congress
Maximum utility rate allocation for energy harvesting wireless sensor networks
Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
IEEE/ACM Transactions on Networking (TON)
Opportunistic energy trading between co-located energy-harvesting wireless sensor networks
Proceedings of the 1st International Workshop on Energy Neutral Sensing Systems
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Energy harvesting sensor platforms have opened up a new dimension to the design of network protocols. In order to sustain the network operation, the energy consumption rate cannot be higher than the energy harvesting rate, otherwise, sensor nodes will eventually deplete their batteries. In contrast to traditional network resource allocation problems where the resources are static, time variations in recharging rate presents a new challenge. In this paper, we first explore the performance of an efficient dual decomposition and subgradient method based algorithm, called QuickFix, for computing the data sampling rate and routes. However, fluctuations in recharging can happen at a faster time-scale than the convergence time of the traditional approach. This leads to battery outage and overflow scenarios, that are both undesirable due to missed samples and lost energy harvesting opportunities respectively. To address such dynamics, a local algorithm, called SnapIt, is designed to adapt the sampling rate with the objective of maintaining the battery at a target level. Our evaluations using the TOSSIM simulator show that QuickFix and SnapIt working in tandem can track the instantaneous optimum network utility while maintaining the battery at a target level. When compared with IFRC, a backpressure-based approach, our solution improves the total data rate by 42% on the average while significantly improving the network utility.