Scaling Up The Performance of Distributed Key-Value Stores With In-Switch Coordination

Hebatalla Eldakiky, David Hung Chang Du

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The power and flexibility of software-defined networks lead to a programmable network infrastructure in which in-network computation can help accelerating the performance of applications. This can be achieved by offloading some computational tasks to the network. In this paper, we propose TurboKV, an efficient distributed key-value store architecture that utilizes programmable switches as: 1) partition management nodes to store the key-value store partitions and replicas information; and 2) monitoring stations to measure and balance the load among storage nodes. We also propose a key-based routing protocol to route the queries of clients based on the requested keys to targeted storage nodes. Our experimental results of an initial prototype show that our proposed architecture improves the throughput and reduces the latency of distributed key-value stores when compared to the existing architectures.

Original languageEnglish (US)
Title of host publicationProceedings - 29th International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2021
PublisherIEEE Computer Society
ISBN (Electronic)9781665458382
DOIs
StatePublished - 2021
Externally publishedYes
Event29th International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2021 - Houston, United States
Duration: Nov 3 2021Nov 5 2021

Publication series

NameProceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS
ISSN (Print)1526-7539

Conference

Conference29th International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2021
Country/TerritoryUnited States
CityHouston
Period11/3/2111/5/21

Bibliographical note

Funding Information:
X. ACKNOWLEDGMENT This work was supported by NSF I/UCRC Center Research in Intelligent Storage and the NSF awards 1439662 and 1812537.

Publisher Copyright:
© 2021 IEEE.

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