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Resource-sharing in a single server with time-varying capacity

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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Resource-sharing in a single server with time-varying capacity. / Ayesta, Urtzi; Erausquin, Martin; Jacko, Peter.
Communication, Control, and Computing (Allerton), 2011 49th Annual Allerton Conference on. New York: IEEE, 2011. p. 377-383.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Ayesta, U, Erausquin, M & Jacko, P 2011, Resource-sharing in a single server with time-varying capacity. in Communication, Control, and Computing (Allerton), 2011 49th Annual Allerton Conference on. IEEE, New York, pp. 377-383, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton), United Kingdom, 28/09/11. https://doi.org/10.1109/Allerton.2011.6120192

APA

Ayesta, U., Erausquin, M., & Jacko, P. (2011). Resource-sharing in a single server with time-varying capacity. In Communication, Control, and Computing (Allerton), 2011 49th Annual Allerton Conference on (pp. 377-383). IEEE. https://doi.org/10.1109/Allerton.2011.6120192

Vancouver

Ayesta U, Erausquin M, Jacko P. Resource-sharing in a single server with time-varying capacity. In Communication, Control, and Computing (Allerton), 2011 49th Annual Allerton Conference on. New York: IEEE. 2011. p. 377-383 doi: 10.1109/Allerton.2011.6120192

Author

Ayesta, Urtzi ; Erausquin, Martin ; Jacko, Peter. / Resource-sharing in a single server with time-varying capacity. Communication, Control, and Computing (Allerton), 2011 49th Annual Allerton Conference on. New York : IEEE, 2011. pp. 377-383

Bibtex

@inproceedings{527ff5ea859c436380b1ad4909b12de2,
title = "Resource-sharing in a single server with time-varying capacity",
abstract = "We investigate the problem of sharing the resources of a single server with time-varying capacity with the objective of minimizing the mean delay. We formulate the resource allocation problem as a Markov Decision Process. The problem is not solvable analytically in full generality, and we thus set out to obtain an approximate solution. In our main contribution, we extend the framework of multi-armed bandits to develop a heuristic solution of index type. At every given time, the heuristic assigns an index to every user that depends solely on its current state, and serves the user with highest current index value. We show that in the case of constant capacity, the heuristic policy is equivalent to the so-called Gittins index rule, which is known to be optimal under the assumption of constant capacity.",
author = "Urtzi Ayesta and Martin Erausquin and Peter Jacko",
year = "2011",
month = sep,
doi = "10.1109/Allerton.2011.6120192",
language = "English",
isbn = "9781457718175",
pages = "377--383",
booktitle = "Communication, Control, and Computing (Allerton), 2011 49th Annual Allerton Conference on",
publisher = "IEEE",
note = "2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton) ; Conference date: 28-09-2011 Through 30-09-2011",

}

RIS

TY - GEN

T1 - Resource-sharing in a single server with time-varying capacity

AU - Ayesta, Urtzi

AU - Erausquin, Martin

AU - Jacko, Peter

PY - 2011/9

Y1 - 2011/9

N2 - We investigate the problem of sharing the resources of a single server with time-varying capacity with the objective of minimizing the mean delay. We formulate the resource allocation problem as a Markov Decision Process. The problem is not solvable analytically in full generality, and we thus set out to obtain an approximate solution. In our main contribution, we extend the framework of multi-armed bandits to develop a heuristic solution of index type. At every given time, the heuristic assigns an index to every user that depends solely on its current state, and serves the user with highest current index value. We show that in the case of constant capacity, the heuristic policy is equivalent to the so-called Gittins index rule, which is known to be optimal under the assumption of constant capacity.

AB - We investigate the problem of sharing the resources of a single server with time-varying capacity with the objective of minimizing the mean delay. We formulate the resource allocation problem as a Markov Decision Process. The problem is not solvable analytically in full generality, and we thus set out to obtain an approximate solution. In our main contribution, we extend the framework of multi-armed bandits to develop a heuristic solution of index type. At every given time, the heuristic assigns an index to every user that depends solely on its current state, and serves the user with highest current index value. We show that in the case of constant capacity, the heuristic policy is equivalent to the so-called Gittins index rule, which is known to be optimal under the assumption of constant capacity.

U2 - 10.1109/Allerton.2011.6120192

DO - 10.1109/Allerton.2011.6120192

M3 - Conference contribution/Paper

SN - 9781457718175

SP - 377

EP - 383

BT - Communication, Control, and Computing (Allerton), 2011 49th Annual Allerton Conference on

PB - IEEE

CY - New York

T2 - 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

Y2 - 28 September 2011 through 30 September 2011

ER -