Heavy traffic optimal resource allocation algorithms for cloud computing clusters

Siva Theja Maguluri; R. Srikant; Lei Ying

doi:10.1016/j.peva.2014.08.002

Heavy traffic optimal resource allocation algorithms for cloud computing clusters

Siva Theja Maguluri, R. Srikant, Lei Ying

Research output: Contribution to journal › Article › peer-review

34 Scopus citations

Abstract

Cloud computing is emerging as an important platform for business, personal and mobile computing applications. In this paper, we study a stochastic model of cloud computing, where jobs arrive according to a stochastic process and request resources like CPU, memory and storage space. We consider a model where the resource allocation problem can be separated into a routing or load balancing problem and a scheduling problem. We study the join-the-shortest-queue routing and power-of-two-choices routing algorithms with the MaxWeight scheduling algorithm. It was known that these algorithms are throughput optimal. In this paper, we show that these algorithms are queue length optimal in the heavy traffic limit.

Original language	English (US)
Pages (from-to)	20-39
Number of pages	20
Journal	Performance Evaluation
Volume	81
DOIs	https://doi.org/10.1016/j.peva.2014.08.002
State	Published - Nov 2014

Keywords

Cloud computing
Load balancing
Resource allocation
Scheduling

ASJC Scopus subject areas

Software
Modeling and Simulation
Hardware and Architecture
Computer Networks and Communications

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title = "Heavy traffic optimal resource allocation algorithms for cloud computing clusters",

abstract = "Cloud computing is emerging as an important platform for business, personal and mobile computing applications. In this paper, we study a stochastic model of cloud computing, where jobs arrive according to a stochastic process and request resources like CPU, memory and storage space. We consider a model where the resource allocation problem can be separated into a routing or load balancing problem and a scheduling problem. We study the join-the-shortest-queue routing and power-of-two-choices routing algorithms with the MaxWeight scheduling algorithm. It was known that these algorithms are throughput optimal. In this paper, we show that these algorithms are queue length optimal in the heavy traffic limit.",

keywords = "Cloud computing, Load balancing, Resource allocation, Scheduling",

author = "Maguluri, {Siva Theja} and R. Srikant and Lei Ying",

note = "Funding Information: Research was funded in part by ARO MURIs W911NF-08-1-0233 and W911NF-12-1-0385 and NSF Grants ECCS-1255425 , CNS-1261429 and ECCS-1202065 . ",

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AU - Srikant, R.

AU - Ying, Lei

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