LEGOStore: A Linearizable Geo-Distributed Store Combining Replication and Erasure Coding

Hamidreza Zare, Viveck Ramesh Cadambe, Bhuvan Urgaonkar, Nader Alfares, Praneet Soni, Chetan Sharma, Arif A. Merchant

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

We design and implement LEGOStore, an erasure coding (EC) based linearizable data store over geo-distributed public cloud data centers (DCs). For such a data store, the confluence of the following factors opens up opportunities for EC to be latency-competitive with replication: (a) the necessity of communicating with remote DCs to tolerate entire DC failures and implement linearizability; and (b) the emergence of DCs near most large population centers. LEGOStore employs an optimization framework that, for a given object, carefully chooses among replication and EC, as well as among various DC placements to minimize overall costs. To handle workload dynamism, LEGOStore employs a novel agile reconfiguration protocol. Our evaluation using a LEGOStore prototype spanning 9 Google Cloud Platform DCs demonstrates the efficacy of our ideas. We observe cost savings ranging from moderate (5-20%) to significant (60%) over baselines representing the state of the art while meeting tail latency SLOs. Our reconfiguration protocol is able to transition key placements in 3 to 4 inter-DC RTTs (< 1s in our experiments), allowing for agile adaptation to dynamic conditions.

Original languageEnglish (US)
Pages (from-to)2201-2215
Number of pages15
JournalProceedings of the VLDB Endowment
Volume15
Issue number10
DOIs
StatePublished - 2022
Event48th International Conference on Very Large Data Bases, VLDB 2022 - Sydney, Australia
Duration: Sep 5 2022Sep 9 2022

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • General Computer Science

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