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Author Bugnion, Edouard ♦ Grot, Boris ♦ Daglis, Alexandros ♦ Falsafi, Babak ♦ Novakovic, Stanko
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Replication ♦ Load imbalance
Abstract Despite the natural parallelism across lookups, performance of distributed key-value stores is often limited due to load imbalance induced by heavy skew in the popularity distribution of the dataset. To avoid violating service level objectives expressed in terms of tail latency, systems tend to keep server utilization low and organize the data in micro-shards, which in turn provides units of migration and replication for the purpose of load balancing. These techniques reduce the skew, but incur additional monitoring, data replication and consistency maintenance overheads. This work shows that the trend towards extreme scale-out will further exacerbate the skew-induced load imbalance, and hence the overhead of migration and replication.
Description Affiliation: EPFL, Lausanne, Switzerland (Novakovic, Stanko; Daglis, Alexandros; Bugnion, Edouard; Falsafi, Babak) || University of Edinburgh, Edinburgh, United Kingdom (Grot, Boris)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-01-10
Publisher Place New York
Journal ACM SIGMETRICS Performance Evaluation Review (PERV)
Volume Number 44
Issue Number 1
Page Count 2
Starting Page 367
Ending Page 368


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Source: ACM Digital Library