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ElMem: Towards an elastic memcached system

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

22 Scopus citations

Abstract

Memory caches, such as Memcached, are a critical component of online applications as they help maintain low latencies by alleviating the load at the database. However, memory caches are expensive, both in terms of power and operating costs. It is thus important to dynamically scale such caches in response to workload variations. Unfortunately, stateful systems, such as Memcached, are not elastic in nature. The performance loss that follows a scaling action can severely impact latencies and lead to SLO violations. This paper proposes ElMem, an elastic Memcached system that mitigates post-scaling performance loss by proactively migration hot data between nodes. The key enabler of our work is an efficient algorithm, FuseCache, that migrates the optimal amount of hot data to minimize performance loss. Our experimental results on OpenStack, across several workload traces, show that ElMem elastically scales Memcached while reducing the postscaling performance degradation by about 90%.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE 38th International Conference on Distributed Computing Systems, ICDCS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages278-289
Number of pages12
ISBN (Electronic)9781538668719
DOIs
StatePublished - Jul 19 2018
Event38th IEEE International Conference on Distributed Computing Systems, ICDCS 2018 - Vienna, Austria
Duration: Jul 2 2018Jul 5 2018

Publication series

NameProceedings - International Conference on Distributed Computing Systems
Volume2018-July

Conference

Conference38th IEEE International Conference on Distributed Computing Systems, ICDCS 2018
Country/TerritoryAustria
CityVienna
Period07/2/1807/5/18

Keywords

  • Auto Scaling
  • Data Migration
  • Elastic
  • Memcached

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