Tackling Heterogeneous Traffic in Multi-access Systems via Erasure Coded Servers

07/08/2022
by   Tuhinangshu Choudhury, et al.
0

Most data generated by modern applications is stored in the cloud, and there is an exponential growth in the volume of jobs to access these data and perform computations using them. The volume of data access or computing jobs can be heterogeneous across different job types and can unpredictably change over time. Cloud service providers cope with this demand heterogeneity and unpredictability by over-provisioning the number of servers hosting each job type. In this paper, we propose the addition of erasure-coded servers that can flexibly serve multiple job types without additional storage cost. We analyze the service capacity region and the response time of such erasure-coded systems and compare them with standard uncoded replication-based systems currently used in the cloud. We show that coding expands the service capacity region, thus enabling the system to handle variability in demand for different data types. Moreover, we characterize the response time of the coded system in various arrival rate regimes. This analysis reveals that adding even a small number of coded servers can significantly reduce the mean response time, with a drastic reduction in regimes where the demand is skewed across different job types.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/20/2020

Zero Queueing for Multi-Server Jobs

Cloud computing today is dominated by multi-server jobs. These are jobs ...
research
07/06/2018

Faster Data-access in Large-scale Systems: Network-scale Latency Analysis under General Service-time Distributions

In cloud storage systems with a large number of servers, files are typic...
research
10/01/2017

Asymptotic response time analysis for multi-task parallel jobs

The response time of jobs with multiple parallel tasks is a critical per...
research
09/19/2022

Capacity Allocation for Clouds with Parallel Processing, Batch Arrivals, and Heterogeneous Service Requirements

Problem Definition: Allocating sufficient capacity to cloud services is ...
research
07/25/2019

MDS coding is better than replication for job completion times

In a multi-server system, how can one get better performance than random...
research
08/08/2020

Achievable Stability in Redundancy Systems

We consider a system with N parallel servers where incoming jobs are imm...
research
09/03/2020

Service Rate Region: A New Aspect of Coded Distributed System Design

Erasure coding has been recently employed as a powerful method to mitiga...

Please sign up or login with your details

Forgot password? Click here to reset