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Cost-based Memory Partitioning and Management in Memcached

Authors:

Pietro MichiardiAuthors Info & Claims

IMDM '15: Proceedings of the 3rd VLDB Workshop on In-Memory Data Mangement and Analytics

Article No.: 6, Pages 1 - 8

https://doi.org/10.1145/2803140.2803146

Published: 31 August 2015 Publication History

Abstract

In this work we present a cost-based memory partitioning and management mechanism for Memcached, an in-memory key-value store used as Web cache, that is able to dynamically adapt to user requests and manage the memory according to both object sizes and costs. We then present a comparative analysis of the vanilla memory management scheme of Memcached and our approach, using real traces from a major content delivery network operator. Our results indicate that our scheme achieves near-optimal performance, striking a good balance between the performance perceived by end-users and the pressure imposed on back-end servers.

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Cited By

Raj PSingh KPandey MRajput S(2023)An Implementation of Memcached Data Partitioning and Sharding Optimization using Apache Benchmark2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS)10.1109/ICACRS58579.2023.10404608(1751-1756)Online publication date: 11-Dec-2023
https://doi.org/10.1109/ICACRS58579.2023.10404608
Kamiyama NNakano YShiomoto K(2016)Cache Replacement Based on Distance to Origin ServersIEEE Transactions on Network and Service Management10.1109/TNSM.2016.260024013:4(848-859)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1109/TNSM.2016.2600240

Cost-based Memory Partitioning and Management in Memcached
1. Software and its engineering
  1. Software organization and properties
    1. Contextual software domains
      1. Operating systems

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cover image ACM Other conferences

IMDM '15: Proceedings of the 3rd VLDB Workshop on In-Memory Data Mangement and Analytics

August 2015

63 pages

ISBN:9781450337137

DOI:10.1145/2803140

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SAMSUNG: SAMSUNG
VLDB Endowment: Very Large Database Endowment
Microsoft: Microsoft

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 31 August 2015

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IMDM '15

IMDM '15: VLDB Workshop on In-Memory Data Mangement and Analytics

August 31, 2015

HI, Kohala Coast, USA

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Cited By

Raj PSingh KPandey MRajput S(2023)An Implementation of Memcached Data Partitioning and Sharding Optimization using Apache Benchmark2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS)10.1109/ICACRS58579.2023.10404608(1751-1756)Online publication date: 11-Dec-2023
https://doi.org/10.1109/ICACRS58579.2023.10404608
Kamiyama NNakano YShiomoto K(2016)Cache Replacement Based on Distance to Origin ServersIEEE Transactions on Network and Service Management10.1109/TNSM.2016.260024013:4(848-859)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1109/TNSM.2016.2600240

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