Game-theoretic medium access control protocol for wireless sensor networks

Zhao, Liqiang; Guo, Le Jiang; Zhang, Jie; Zhang, Hailin

doi:10.1049/iet-com.2008.0383

Cited by 17 publications

(20 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Q-MAC [50] introduces the concept of a quorum to adapt the sleep schedules to improve the energy efficiency and delay performance. …”

Section: F Quorum-based Mac (Q-mac)mentioning

confidence: 99%

“…Based on SMAC, [50] proposes an incomplete cooperative game-theoretic heuristic-based constraint optimisation algorithm to adaptively adjust the duty cycle to the current traffic in the network, thereby achieving better energy efficiency, throughput and delay performance.…”

Section: G Game-theoretic Mac (G-mac)mentioning

confidence: 99%

“…In [50] a game-based optimisation algorithm is proposed to estimate the simultaneous competing nodes in the network. The algorithm requires complete schedule information and explicit cooperation of nodes.…”

Section: G Game-theoretic Mac (G-mac)mentioning

confidence: 99%

See 2 more Smart Citations

Application of reinforcement learning to medium access control for wireless sensor networks

Chu

Koşunalp

Mitchell

et al. 2015

Engineering Applications of Artificial Intelligence

View full text Add to dashboard Cite

This thesis investigates the application of Reinforcement Learning (RL) on Medium Access Control (MAC) for Wireless Sensor Networks (WSNs). RL is applied as an intelligent slot selection strategy to Framed ALOHA, along with analytical and experimental performance evaluation. Informed Receiving (IR) and ping packets are applied to multi-hop WSNs to avoid idle listening and overhearing, thereby further improving the energy efficiency.The low computational complexity and signalling overheads of the ALOHA schemes meet the design requirement of energy constraint WSNs, but suffer collisions from the random access strategy. RL is applied to solve this problem and to achieve perfect scheduling. Results show that the RL scheme achieves over 0.9 Erlangs maximum throughput in single-hop networks. For multi-hop WSNs, IR and ping packets are applied to appropriately switch the relay nodes between active and sleep state, to reserve as much energy as possible while ensuring no information loss.The RL algorithms require certain time to converge to steady state to achieve the optimum performance. The convergence behaviour is investigated in this thesis. A Markov model is proposed to describe a learning process, and the model produces the proof of the convergence of the learning process and the estimated convergence time. The channel performance before convergence is also evaluated.Contents

show abstract

“…Q-MAC [50] introduces the concept of a quorum to adapt the sleep schedules to improve the energy efficiency and delay performance. …”

Section: F Quorum-based Mac (Q-mac)mentioning

confidence: 99%

Section: G Game-theoretic Mac (G-mac)mentioning

confidence: 99%

See 1 more Smart Citation

Application of reinforcement learning to medium access control for wireless sensor networks

Chu

Koşunalp

Mitchell

et al. 2015

Engineering Applications of Artificial Intelligence

View full text Add to dashboard Cite

show abstract

“…Additionally, some contributions minimized the energy consumption by developing energyefficient cooperative MAC protocols, but these often remained oblivious of the associated throughput performance [64][65][66][67]. By contrast, both Zhao et al [68] and Shirazi et al [69] designed meritorious algorithms for improving the achievable throughput, while reducing the energy consumption imposed. However, the above-mentioned cooperative MAC protocols were developed on the basis of the common assumption that the relays agree to altruistically forward the data frames of the source.…”

Section: Cooperative Relaying In Ms Cooperation: Cross-layer Coopementioning

confidence: 99%

Advances in base- and mobile-station aided cooperative wireless communications: An overview

Zhang

Wang

Parr

et al. 2013

IEEE Veh. Technol. Mag.

View full text Add to dashboard Cite

Abstract-Albeit the conception of relaying dates back to the 1970s, in recent years there has been an upsurge of search interest in cooperative wireless communications in both academia and industry. This article presents an easy-reading overview of the pivotal topics in both mobile station (MS) and base station (BS) assisted cooperation in the context of cellular radio systems. Owing to the ever-increasing amount of literature in this particular field, this paper is by no means exhaustive, but intends to serve as a roadmap for this area by assembling a representative sample of recent results and to stimulate further research. The emphasis is initially on relay-base cooperation, relying on network coding, followed by the design of cross-layer cooperative protocols conceived for MS cooperation, as well as on the concept of coalition network element assisted BS cooperation. Then, a range of complexity and backhaul traffic reduction techniques that have been proposed for BS cooperation are reviewed. A more detailed discussion is provided in the context of MS cooperation concerning the pros and cons of dispensing with high-complexity, power-hungry channel estimation. Finally, generalized design guidelines, conceived for cooperative wireless communications, are presented.

show abstract

“…A game-theoretic MAC approach for WSNs is presented in (Zhao et al, 2009). The MAC of nodes in this technique is based on an incompletely cooperative game mode.…”

Section: Other Mac Approachesmentioning

confidence: 99%