Scheduling Policies for Age Minimization in Wireless Networks with Unknown Channel State

Rajat Talak; Igor Kadota; Sertac Karaman; Eytan Modiano

doi:10.1109/ISIT.2018.8437688

Scheduling Policies for Age Minimization in Wireless Networks with Unknown Channel State

Rajat Talak, Igor Kadota, Sertac Karaman, Eytan Modiano

Electrical and Computer Engineering

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

52 Scopus citations

Abstract

Age of information (AoI) is a recently proposed metric that measures the time elapsed since the generation of the last received information update. We consider the problem of AoI minimization for a network under general interference constraints, and time varying channel. We study the case where the channel statistics are known, but the current channel state is unknown. We propose two scheduling policies, namely, the virtual queue based policy and age-based policy. In the virtual queue based policy, the scheduler schedules links with maximum weighted sum of the virtual queue lengths, while in the age-based policy, the scheduler schedules links with maximum weighted sum of a function of link AoI. We prove that the virtual queue based policy is peak age optimal, up to an additive constant, while the age-based policy is at most factor 4 away from the optimal age. Numerical results suggest that both the proposed policies are, in fact, very close to the optimal.

Original language	English (US)
Title of host publication	2018 IEEE International Symposium on Information Theory, ISIT 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2564-2568
Number of pages	5
ISBN (Print)	9781538647806
DOIs	https://doi.org/10.1109/ISIT.2018.8437688
State	Published - Aug 15 2018
Event	2018 IEEE International Symposium on Information Theory, ISIT 2018 - Vail, United States Duration: Jun 17 2018 → Jun 22 2018

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
Volume	2018-June
ISSN (Print)	2157-8095

Other

Other	2018 IEEE International Symposium on Information Theory, ISIT 2018
Country/Territory	United States
City	Vail
Period	6/17/18 → 6/22/18

Funding

The authors are with the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology (MIT), Cambridge, MA. {talak, kadota, sertac, modiano}@mit.edu This work was supported by NSF Grants AST-1547331, CNS-1713725, and CNS-1701964, and by Army Research Office (ARO) grant number W911NF-17-1-0508. This work was supported by NSF Grants AST-1547331, CNS-1713725, and CNS-1701964, and by Army Research Office (ARO) grant number W911NF- 17-1-0508.

ASJC Scopus subject areas

Theoretical Computer Science
Information Systems
Modeling and Simulation
Applied Mathematics

Access to Document

10.1109/ISIT.2018.8437688

Cite this

Talak, R., Kadota, I., Karaman, S., & Modiano, E. (2018). Scheduling Policies for Age Minimization in Wireless Networks with Unknown Channel State. In 2018 IEEE International Symposium on Information Theory, ISIT 2018 (pp. 2564-2568). Article 8437688 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2018-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2018.8437688

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title = "Scheduling Policies for Age Minimization in Wireless Networks with Unknown Channel State",

abstract = "Age of information (AoI) is a recently proposed metric that measures the time elapsed since the generation of the last received information update. We consider the problem of AoI minimization for a network under general interference constraints, and time varying channel. We study the case where the channel statistics are known, but the current channel state is unknown. We propose two scheduling policies, namely, the virtual queue based policy and age-based policy. In the virtual queue based policy, the scheduler schedules links with maximum weighted sum of the virtual queue lengths, while in the age-based policy, the scheduler schedules links with maximum weighted sum of a function of link AoI. We prove that the virtual queue based policy is peak age optimal, up to an additive constant, while the age-based policy is at most factor 4 away from the optimal age. Numerical results suggest that both the proposed policies are, in fact, very close to the optimal.",

author = "Rajat Talak and Igor Kadota and Sertac Karaman and Eytan Modiano",

note = "Funding Information: The authors are with the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology (MIT), Cambridge, MA. {talak, kadota, sertac, modiano}@mit.edu This work was supported by NSF Grants AST-1547331, CNS-1713725, and CNS-1701964, and by Army Research Office (ARO) grant number W911NF-17-1-0508. Funding Information: This work was supported by NSF Grants AST-1547331, CNS-1713725, and CNS-1701964, and by Army Research Office (ARO) grant number W911NF- 17-1-0508. Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Symposium on Information Theory, ISIT 2018 ; Conference date: 17-06-2018 Through 22-06-2018",

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doi = "10.1109/ISIT.2018.8437688",

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Talak, R, Kadota, I, Karaman, S & Modiano, E 2018, Scheduling Policies for Age Minimization in Wireless Networks with Unknown Channel State. in 2018 IEEE International Symposium on Information Theory, ISIT 2018., 8437688, IEEE International Symposium on Information Theory - Proceedings, vol. 2018-June, Institute of Electrical and Electronics Engineers Inc., pp. 2564-2568, 2018 IEEE International Symposium on Information Theory, ISIT 2018, Vail, United States, 6/17/18. https://doi.org/10.1109/ISIT.2018.8437688

Scheduling Policies for Age Minimization in Wireless Networks with Unknown Channel State. / Talak, Rajat; Kadota, Igor; Karaman, Sertac et al.
2018 IEEE International Symposium on Information Theory, ISIT 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 2564-2568 8437688 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2018-June).

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

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AU - Talak, Rajat

AU - Kadota, Igor

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N1 - Funding Information: The authors are with the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology (MIT), Cambridge, MA. {talak, kadota, sertac, modiano}@mit.edu This work was supported by NSF Grants AST-1547331, CNS-1713725, and CNS-1701964, and by Army Research Office (ARO) grant number W911NF-17-1-0508. Funding Information: This work was supported by NSF Grants AST-1547331, CNS-1713725, and CNS-1701964, and by Army Research Office (ARO) grant number W911NF- 17-1-0508. Publisher Copyright: © 2018 IEEE.

PY - 2018/8/15

Y1 - 2018/8/15

N2 - Age of information (AoI) is a recently proposed metric that measures the time elapsed since the generation of the last received information update. We consider the problem of AoI minimization for a network under general interference constraints, and time varying channel. We study the case where the channel statistics are known, but the current channel state is unknown. We propose two scheduling policies, namely, the virtual queue based policy and age-based policy. In the virtual queue based policy, the scheduler schedules links with maximum weighted sum of the virtual queue lengths, while in the age-based policy, the scheduler schedules links with maximum weighted sum of a function of link AoI. We prove that the virtual queue based policy is peak age optimal, up to an additive constant, while the age-based policy is at most factor 4 away from the optimal age. Numerical results suggest that both the proposed policies are, in fact, very close to the optimal.

AB - Age of information (AoI) is a recently proposed metric that measures the time elapsed since the generation of the last received information update. We consider the problem of AoI minimization for a network under general interference constraints, and time varying channel. We study the case where the channel statistics are known, but the current channel state is unknown. We propose two scheduling policies, namely, the virtual queue based policy and age-based policy. In the virtual queue based policy, the scheduler schedules links with maximum weighted sum of the virtual queue lengths, while in the age-based policy, the scheduler schedules links with maximum weighted sum of a function of link AoI. We prove that the virtual queue based policy is peak age optimal, up to an additive constant, while the age-based policy is at most factor 4 away from the optimal age. Numerical results suggest that both the proposed policies are, in fact, very close to the optimal.

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M3 - Conference contribution

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SN - 9781538647806

T3 - IEEE International Symposium on Information Theory - Proceedings

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BT - 2018 IEEE International Symposium on Information Theory, ISIT 2018

PB - Institute of Electrical and Electronics Engineers Inc.

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Talak R, Kadota I, Karaman S, Modiano E. Scheduling Policies for Age Minimization in Wireless Networks with Unknown Channel State. In 2018 IEEE International Symposium on Information Theory, ISIT 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 2564-2568. 8437688. (IEEE International Symposium on Information Theory - Proceedings). doi: 10.1109/ISIT.2018.8437688

Scheduling Policies for Age Minimization in Wireless Networks with Unknown Channel State

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