CooperativeQ: Energy-efficient channel access based on cooperative reinforcement learning

Emre, Mehmet; Gûr, Gûrkan; Bayhan, Suzan; Alagöz, Fatíh

doi:10.1109/iccw.2015.7247603

Cited by 6 publications

(3 citation statements)

References 16 publications

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“…Therefore, application performance and energy achieve a better trade-off. Emre et al 32 introduced the so-called cooperative Q method which makes radios learn and adapt to their environment by sharing their information. Its proposal aimed to maximize energy efficiency while ensuring buffer occupancy below the predetermined level.…”

Section: Rl Applied In Power Managementmentioning

confidence: 99%

Maximizing network throughput by cooperative reinforcement learning in clustered solar-powered wireless sensor networks

Nan

Guo

2021

International Journal of Distributed Sensor Networks

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Power management in wireless sensor networks is very important due to the limited energy of batteries. Sensor nodes with harvesters can extract energy from environmental sources as supplemental energy to break this limitation. In a clustered solar-powered sensor network where nodes in the network are grouped into clusters, data collected by cluster members are sent to their cluster head and finally transmitted to the base station. The goal of the whole network is to maintain an energy neutrality state and to maximize the effective data throughput of the network. This article proposes an adaptive power manager based on cooperative reinforcement learning methods for the solar-powered wireless sensor networks to keep harvested energy more balanced among the whole clustered network. The cooperative strategy of Q-learning and SARSA( λ) is applied in this multi-agent environment based on the node residual energy, the predicted harvested energy for the next time slot, and cluster head energy information. The node takes action accordingly to adjust its operating duty cycle. Experiments show that cooperative reinforcement learning methods can achieve the overall goal of maximizing network throughput and cooperative approaches outperform tuned static and non-cooperative approaches in clustered wireless sensor network applications. Experiments also show that the approach is effective in response to changes in the environment, changes in its parameters, and application-level quality of service requirements.

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Section: Rl Applied In Power Managementmentioning

confidence: 99%

Maximizing network throughput by cooperative reinforcement learning in clustered solar-powered wireless sensor networks

Nan

Guo

2021

International Journal of Distributed Sensor Networks

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“…To reduce the cost of heating the buildings on the basis of data on gas consumption, a study was made of the energy efficiency of a private house based on the average gas consumption figures for the heating season on the basis of the initial data [2]. In light of the most famous researchers who dealt with energy efficiency and energy conservation, [3][4][5][6][7], as well as the widespread Internet resources Consumption of energy [8], Shedding light on energy in the EU [9].…”

Section: The Object Of Research and Its Technological Auditmentioning

confidence: 99%

“…The paper [1] proposes an algorithm for conducting energy audits and measures to reduce the energy consumption of industrial enterprises in heating systems. General issues of energy efficiency and gas consumption in the heating season are considered by users of Internet resources [2][3][4][5][8][9][10]. The economic efficiency of the use of network solar power plants in private households is calculated and presented in a scientific study of authors [11].…”

Section: Research Of Existing Solutions Of the Problemmentioning

confidence: 99%

Sustainable development economy: determination of energy efficiency of private houses on the basis of data on heat gas consumption

Klyon

Yefremenko

Tochonov

2017

TAPR

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Проаналізовані статистичні дані про витрати газу на опалення приватними домогосподарствами країн СНД. Запропонована методика оцінки енергоефективності приватного будинку на підставі середніх показників витрати газу за опалювальний сезон. Визначені питання кількісної оцінки теплової енергії та енергоресурсів, які витрачаються на опалення приватного будинку. ключові слова: енергоефективність приватного будинку, витрати газу на опалення, кількісна оцінка теплової енергії та енергоресурсів. Klyon a., yefremenko v., tochonov i.

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Reinforcement Learning-Based Spectrum Management for Cognitive Radio Networks: A Literature Review and Case Study

Felice

Bedogni

Bononi

2018

Handbook of Cognitive Radio

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CooperativeQ: Energy-efficient channel access based on cooperative reinforcement learning

Cited by 6 publications

References 16 publications

Maximizing network throughput by cooperative reinforcement learning in clustered solar-powered wireless sensor networks

Maximizing network throughput by cooperative reinforcement learning in clustered solar-powered wireless sensor networks

Sustainable development economy: determination of energy efficiency of private houses on the basis of data on heat gas consumption

Reinforcement Learning-Based Spectrum Management for Cognitive Radio Networks: A Literature Review and Case Study

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