Simplex Queues for Hot-Data Download

TL;DR

This paper analyzes data access times in cloud storage systems using simplex codes, focusing on how code locality and availability influence performance under different request assignment strategies.

Contribution

It provides an approximate analysis of data access times for simplex codes and compares three request assignment strategies in hot-data download scenarios.

Findings

Simplex codes are effective for hot-data storage with high availability.

Different request assignment strategies impact download times and system efficiency.

The analysis offers insights into optimizing storage and retrieval in cloud systems.

Abstract

In cloud storage systems, hot data is usually replicated over multiple nodes in order to accommodate simultaneous access by multiple users as well as increase the fault tolerance of the system. Recent cloud storage research has proposed using availability codes, which is a special class of erasure codes, as a more storage efficient way to store hot data. These codes enable data recovery from multiple, small disjoint groups of servers. The number of the recovery groups is referred to as the availability and the size of each group as the locality of the code. Until now, we have very limited knowledge on how code locality and availability affect data access time. Data download from these systems involves multiple fork-join queues operating in-parallel, making the analysis of access time a very challenging problem. In this paper, we present an approximate analysis of data access time in storage systems that employ simplex codes, which are an important and in certain sense optimal class of availability codes. We consider and compare three strategies in assigning download requests to servers; first one aggressively exploits the storage availability for faster download, second one implements only load balancing, and the last one employs storage availability only for hot data download without incurring any negative impact on the cold data download.