Joint Latency and Cost Optimization for Erasure-coded Data Center Storage

Abstract

Modern distributed storage systems offer large capacity to satisfy the exponentially increasing need of storage space. They often use erasure codes to protect against disk and node failures to increase reliability, while trying to meet the latency requirements of the applications and clients. This paper provides an insightful upper bound on the average service delay of such erasure-coded storage with arbitrary service time distribution and consisting of multiple heterogeneous files. Not only does the result supersede known delay bounds that only work for a single file or homogeneous files, it also enables a novel problem of joint latency and storage cost minimization over three dimensions: selecting the erasure code, placement of encoded chunks, and optimizing scheduling policy. The problem is efficiently solved via the computation of a sequence of convex approximations with provable convergence. We further prototype our solution in an open-source, cloud storage deployment over three geographically distributed data centers. Experimental results validate our theoretical delay analysis and show significant latency reduction, providing valuable insights into the proposed latency-cost tradeoff in erasure-coded storage.

14 pages, presented in part at IFIP Performance, Oct 2014

References in corpus (1)

• When Queueing Meets Coding: Optimal-Latency Data Retrieving Scheme in Storage Clouds

Cited by in corpus (5)

• Optimal Server Selection for Straggler Mitigation
• Straggler Mitigation with Tiered Gradient Codes
• Differentiated latency in data center networks with erasure coded files through traffic engineering
• Latency optimal storage and scheduling of replicated fragments for memory-constrained servers
• Latency-Redundancy Tradeoff in Distributed Read-Write Systems