A rate-adaptive MAC protocol for multi-Hop wireless networks
Proceedings of the 7th annual international conference on Mobile computing and networking
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Optimal power and retransmission control policies for random access systems
IEEE/ACM Transactions on Networking (TON)
Design challenges for energy-constrained ad hoc wireless networks
IEEE Wireless Communications
Energy-centric enabling tecumologies for wireless sensor networks
IEEE Wireless Communications
Energy concerns in wireless networks
IEEE Wireless Communications
Low-energy wireless communication network design
IEEE Wireless Communications
Optimal transmission scheduling over a fading channel with energy and deadline constraints
IEEE Transactions on Wireless Communications
IEEE Communications Magazine
New cross-Layer design approach to ad hoc networks under Rayleigh fading
IEEE Journal on Selected Areas in Communications
Study of an adaptive frame size predictor to enhance energy conservation in wireless sensor networks
IEEE Journal on Selected Areas in Communications
Near-optimal reinforcement learning framework for energy-aware sensor communications
IEEE Journal on Selected Areas in Communications
Localized policy-based target tracking using wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
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We propose an opportunistic transmission strategy for wireless sensor networks (WSNs) that operate in a strict energy-constrained environment. The WSNs of interest in thiswork are assumed to host delay-sensitive applications. Our proposed transmission strategy named binary-decision based transmission (BDT) attempts to transmit at good channel conditions while meeting the delay constraint, under time-varying wireless channel. The Markov decision process (MDP) is used to find optimum threshold for transmission decision. Our BDT scheme initiates transmission only when the channel quality exceeds the optimumthreshold, so that unsuccessful transmissions causing a waste of energy are avoided whenever possible. Extensive simulations are performed to verify the performance of our proposal over wireless fading channels. The simulation results show that the BDT scheme has 35% higher energy efficiency than its counterparts, thereby further prolonging the network lifetime.