Saino, L;
Psaras, I;
Pavlou, G;
(2016)
Understanding Sharded Caching Systems.
In: Song, M and Westphal, C and Striegel, AD and Yu, S, (eds.)
IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.
IEEE
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Abstract
Sharding is a method for allocating data items to nodes of a distributed caching or storage system based on the result of a hash function computed on the item identifier. It is ubiquitously used in key-value stores, CDNs and many other applications. Despite considerable work has focused on the design and the implementation of such systems, there is limited understanding of their performance in realistic operational conditions from a theoretical standpoint. In this paper we fill this gap by providing a thorough modeling of sharded caching systems, focusing particularly on load balancing and caching performance aspects. Our analysis provides important insights that can be applied to optimize the design and configuration of sharded caching systems.
Type: | Proceedings paper |
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Title: | Understanding Sharded Caching Systems |
Event: | IEEE INFOCOM 2016: 35th IEEE Annual International Conference on Computer Communications, 10-14 April 2016, San Francisco, USA |
Location: | San Francisco, CA |
Dates: | 10 April 2016 - 14 April 2016 |
ISBN-13: | 9781467399531 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1109/INFOCOM.2016.7524442 |
Publisher version: | https://doi.org/10.1109/INFOCOM.2016.7524442 |
Language: | English |
Additional information: | Copyright © 2016 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. |
Keywords: | Load modeling, Load management, Random variables, Games, Databases, Analytical models, Harmonic analysis |
UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
URI: | https://discovery.ucl.ac.uk/id/eprint/1536098 |




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