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Fast and accurate load balancing for geo-distributed storage systems
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS.ORCID iD: 0000-0001-7642-6591
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS.
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS.ORCID iD: 0000-0002-6066-746X
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS.ORCID iD: 0000-0002-1256-1070
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2018 (English)In: SoCC 2018 - Proceedings of the 2018 ACM Symposium on Cloud Computing, Association for Computing Machinery (ACM), 2018, p. 386-400Conference paper, Published paper (Refereed)
Abstract [en]

The increasing density of globally distributed datacenters reduces the network latency between neighboring datacenters and allows replicated services deployed across neighboring locations to share workload when necessary, without violating strict Service Level Objectives (SLOs). We present Kurma, a practical implementation of a fast and accurate load balancer for geo-distributed storage systems. At run-time, Kurma integrates network latency and service time distributions to accurately estimate the rate of SLO violations for requests redirected across geo-distributed datacenters. Using these estimates, Kurma solves a decentralized rate-based performance model enabling fast load balancing (in the order of seconds) while taming global SLO violations. We integrate Kurma with Cassandra, a popular storage system. Using real-world traces along with a geo-distributed deployment across Amazon EC2, we demonstrate Kurma’s ability to effectively share load among datacenters while reducing SLO violations by up to a factor of 3 in high load settings or reducing the cost of running the service by up to 17%.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2018. p. 386-400
Keywords [en]
Cloud Computing, Distributed Systems, Server Load Balancing, Service Level Objectives, Wide Area Networks
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-241481DOI: 10.1145/3267809.3267820Scopus ID: 2-s2.0-85059006718ISBN: 9781450360111 (print)OAI: oai:DiVA.org:kth-241481DiVA, id: diva2:1281722
Conference
2018 ACM Symposium on Cloud Computing, SoCC 2018, Carlsbad, United States, 11 October 2018 through 13 October 2018
Funder
EU, Horizon 2020, 770889Swedish Foundation for Strategic Research
Note

QC 20190123

Available from: 2019-01-23 Created: 2019-01-23 Last updated: 2019-04-29Bibliographically approved

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fulltext(1175 kB)34 downloads
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Bogdanov, KirillMaguire Jr., Gerald Q.Kostic, Dejan

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