Data-driven stochastic scheduling for solar-powered sensor communications

Meng Lin Ku; Yan Chen; K. J.Ray Liu

doi:10.1109/GlobalSIP.2014.7032083

Data-driven stochastic scheduling for solar-powered sensor communications

Meng Lin Ku, Yan Chen, K. J.Ray Liu

Department of Communication Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

This paper presents a data-driven approach of finding optimal scheduling policies for a solar-powered sensor node that attempts to maximize net bit rates by adapting its transmission to the changes of channel fading and battery recharge. The problem is formulated as a discounted Markov decision process (MDP) framework, whereby the energy harvesting process is stochastically quantized into several representative solar states with distinct energy arrivals and is totally driven by historical data records at a sensor node. We evaluate the average net bit rate of the optimal transmission scheduling policy, and computer simulations show that the proposed policy significantly outperforms other schemes with or without the knowledge of short-term energy harvesting and channel fading patterns.

Original language	English
Title of host publication	2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	83-87
Number of pages	5
ISBN (Electronic)	9781479970889
DOIs	https://doi.org/10.1109/GlobalSIP.2014.7032083
State	Published - 5 Feb 2014
Event	2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 - Atlanta, United States Duration: 3 Dec 2014 → 5 Dec 2014

Publication series

Name	2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014

Conference

Conference	2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
Country/Territory	United States
City	Atlanta
Period	3/12/14 → 5/12/14

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10.1109/GlobalSIP.2014.7032083

Cite this

Ku, M. L., Chen, Y., & Liu, K. J. R. (2014). Data-driven stochastic scheduling for solar-powered sensor communications. In 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 (pp. 83-87). Article 7032083 (2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2014.7032083

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abstract = "This paper presents a data-driven approach of finding optimal scheduling policies for a solar-powered sensor node that attempts to maximize net bit rates by adapting its transmission to the changes of channel fading and battery recharge. The problem is formulated as a discounted Markov decision process (MDP) framework, whereby the energy harvesting process is stochastically quantized into several representative solar states with distinct energy arrivals and is totally driven by historical data records at a sensor node. We evaluate the average net bit rate of the optimal transmission scheduling policy, and computer simulations show that the proposed policy significantly outperforms other schemes with or without the knowledge of short-term energy harvesting and channel fading patterns.",

author = "Ku, {Meng Lin} and Yan Chen and Liu, {K. J.Ray}",

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Ku, ML, Chen, Y & Liu, KJR 2014, Data-driven stochastic scheduling for solar-powered sensor communications. in 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014., 7032083, 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014, Institute of Electrical and Electronics Engineers Inc., pp. 83-87, 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014, Atlanta, United States, 3/12/14. https://doi.org/10.1109/GlobalSIP.2014.7032083

Data-driven stochastic scheduling for solar-powered sensor communications. / Ku, Meng Lin; Chen, Yan; Liu, K. J.Ray.
2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 83-87 7032083 (2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - This paper presents a data-driven approach of finding optimal scheduling policies for a solar-powered sensor node that attempts to maximize net bit rates by adapting its transmission to the changes of channel fading and battery recharge. The problem is formulated as a discounted Markov decision process (MDP) framework, whereby the energy harvesting process is stochastically quantized into several representative solar states with distinct energy arrivals and is totally driven by historical data records at a sensor node. We evaluate the average net bit rate of the optimal transmission scheduling policy, and computer simulations show that the proposed policy significantly outperforms other schemes with or without the knowledge of short-term energy harvesting and channel fading patterns.

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Ku ML, Chen Y, Liu KJR. Data-driven stochastic scheduling for solar-powered sensor communications. In 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 83-87. 7032083. (2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014). doi: 10.1109/GlobalSIP.2014.7032083

Data-driven stochastic scheduling for solar-powered sensor communications

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