Analysis of the increase and decrease algorithms for congestion avoidance in computer networks
Computer Networks and ISDN Systems
Equation-based congestion control for unicast applications
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
An environmental energy harvesting framework for sensor networks
Proceedings of the 2003 international symposium on Low power electronics and design
Performance aware tasking for environmentally powered sensor networks
Proceedings of the joint international conference on Measurement and modeling of computer systems
Dynamic node activation in networks of rechargeable sensors
IEEE/ACM Transactions on Networking (TON)
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
Introduction to Discrete Event Systems
Introduction to Discrete Event Systems
Challenge: ultra-low-power energy-harvesting active networked tags (EnHANTs)
Proceedings of the 15th annual international conference on Mobile computing and networking
Dual wake-up low power listening for duty cycled wireless sensor networks
EURASIP Journal on Wireless Communications and Networking
Rechargeable sensor activation under temporally correlated events
Wireless Networks
IEEE Wireless Communications
Performance analysis of TCP-friendly AIMD algorithms for multimedia applications
IEEE Transactions on Multimedia
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Upcoming sensor networks would be deployed with sensing devices with energy harvesting capabilities from renewable energy sources such as solar power. A key research question in such sensor systems is to maximize the asymptotic event detection probability achieved in the system, in the presence of energy constraints and uncertainties. This paper focuses on the design of adaptive algorithms for sensor activation in the presence of uncertainty in the event phenomena. Based upon the ideas from increase/decrease algorithms used in TCP congestion avoidance, we design an online and adaptive activation algorithm that varies the subsequent sleep interval according to additive increase and multiplicative decrease depending upon the sensor's current energy level. In addition, the proposed algorithm does not depend on global system parameters, or on the degree of event correlations, and hence can easily be deployed in practical scenarios. We analyze the performance of proposed algorithm for a single sensor scenario using Markov chains, and show that the proposed algorithm achieves near-optimal performance. Through extensive simulations, we demonstrate that the proposed algorithm not only achieves near-optimal performance, but also exhibits more stability with respect to sensor's energy level and sleep interval variations. We validate the applicability of our proposed algorithm in the presence of multiple sensors and multiple event processes through simulations.