Data networks
Wireless sensor networks for habitat monitoring
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
An environmental energy harvesting framework for sensor networks
Proceedings of the 2003 international symposium on Low power electronics and design
Utilizing Solar Power in Wireless Sensor Networks
LCN '03 Proceedings of the 28th Annual IEEE International Conference on Local Computer Networks
On Generalized Max-Min Rate Allocation and Distributed Convergence Algorithm for Packet Networks
IEEE Transactions on Parallel and Distributed Systems
Performance aware tasking for environmentally powered sensor networks
Proceedings of the joint international conference on Measurement and modeling of computer systems
A wireless sensor network For structural monitoring
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Hardware design experiences in ZebraNet
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Invited Talk: Thermal Energy Harvesting with Thermo Life
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
Trio: enabling sustainable and scalable outdoor wireless sensor network deployments
Proceedings of the 5th international conference on Information processing in sensor networks
Design considerations for solar energy harvesting wireless embedded systems
IPSN '05 Proceedings of the 4th international symposium 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
Health monitoring of civil infrastructures using wireless sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Lexicographic Maxmin Fairness for Data Collection in Wireless Sensor Networks
IEEE Transactions on Mobile Computing
Power management in energy harvesting sensor networks
ACM Transactions on Embedded Computing Systems (TECS) - Special Section LCTES'05
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
Maximizing lifetime vector in wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Dimensioning self-sufficient networks of energy harvesting embedded devices
WiFlex'13 Proceedings of the First international conference on Wireless Access Flexibility
Achieving energy-synchronized communication in energy-harvesting wireless sensor networks
ACM Transactions on Embedded Computing Systems (TECS) - Special Section ESFH'12, ESTIMedia'11 and Regular Papers
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Renewable energy enables sensor networks with the capability to recharge and provide perpetual data services. Due to low recharging rates and the dynamics of renewable energy such as solar and wind power, providing services without interruptions caused by battery runouts is nontrivial. Most environment monitoring applications require data collection from all nodes at a steady rate. The objective of this paper is to design a solution for fair and high throughput data extraction from all nodes in the presence of renewable energy sources. Specifically, we seek to compute the lexicographically maximum data collection rate and routing paths for each node such that no node will ever run out of energy. We propose a centralized algorithm and two distributed algorithms. The centralized algorithm jointly computes the optimal data collection rate for all nodes along with the flows on each link, the first distributed algorithm computes the optimal rate when the routing structure is a given tree, and the second distributed algorithm, although heuristic, jointly computes a routing structure and a high lexicographic rate assignment that is nearly optimum. We prove the optimality for the centralized and the first distributed algorithm, and use real test-bed experiments and extensive simulations to evaluate both of the distributed algorithms.