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Optimal content replication and request matching in large caching systems
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Mukhopadhyay, Arpan, Hegde, Nidhi and Lelarge, Marc (2018) Optimal content replication and request matching in large caching systems. In: INFOCOM 2018, Honolulu, HI, USA, 16-19 Apr 2018. Published in: IEEE INFOCOM 2018 - IEEE Conference on Computer Communications ISBN 9781538641286. doi:10.1109/INFOCOM.2018.8486229
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WRAP-optimal-content-replication-request-matching-large-caching-systems-Mukhopadhyay-2018.pdf - Accepted Version - Requires a PDF viewer. Download (558Kb) | Preview |
Official URL: https://doi.org/10.1109/INFOCOM.2018.8486229
Abstract
We consider models of content delivery networks in which the servers are constrained by two main resources: memory and bandwidth. In such systems, the throughput crucially depends on how contents are replicated across servers and how the requests of specific contents are matched to servers storing those contents. In this paper, we first formulate the problem of computing the optimal replication policy which if combined with the optimal matching policy maximizes the throughput of the caching system in the stationary regime. It is shown that computing the optimal replication policy for a given system is an NP-hard problem. A greedy replication scheme is proposed and it is shown that the scheme provides a constant factor approximation guarantee. We then propose a simple randomized matching scheme which avoids the problem of interruption in service of the ongoing requests due to re-assignment or repacking of the existing requests in the optimal matching policy. The dynamics of the caching system is analyzed under the combination of proposed replication and matching schemes. We study a limiting regime, where the number of servers and the arrival rates of the contents are scaled proportionally, and show that the proposed policies achieve asymptotic optimality. Extensive simulation results are presented to evaluate the performance of different policies and study the behavior of the caching system under different service time distributions of the requests.
| Item Type: | Conference Item (Paper) | ||||||
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
| Journal or Publication Title: | IEEE INFOCOM 2018 - IEEE Conference on Computer Communications | ||||||
| Publisher: | IEEE | ||||||
| ISBN: | 9781538641286 | ||||||
| Official Date: | 11 October 2018 | ||||||
| Dates: |
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| DOI: | 10.1109/INFOCOM.2018.8486229 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Reuse Statement (publisher, data, author rights): | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Date of first compliant deposit: | 6 August 2019 | ||||||
| Date of first compliant Open Access: | 6 August 2019 | ||||||
| Conference Paper Type: | Paper | ||||||
| Title of Event: | INFOCOM 2018 | ||||||
| Type of Event: | Conference | ||||||
| Location of Event: | Honolulu, HI, USA | ||||||
| Date(s) of Event: | 16-19 Apr 2018 | ||||||
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