DocumentCode
1817587
Title
Heavy traffic optimal resource allocation algorithms for cloud computing clusters
Author
Maguluri, Siva Theja ; Srikant, R. ; Ying, Lei
Author_Institution
Dept. of ECE & CSL, Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
fYear
2012
fDate
4-7 Sept. 2012
Firstpage
1
Lastpage
8
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 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; queueing theory; resource allocation; scheduling; stochastic processes; telecommunication network routing; telecommunication traffic; MaxWeight scheduling algorithm; cloud computing clusters; heavy traffic optimal resource allocation algorithms; join-the-shortest-queue routing algorithms; load balancing problem; power-of-two-choices routing algorithms; request resources; stochastic model; stochastic process; Cloud computing; Routing; Scheduling algorithms; Servers; Steady-state; Upper bound; Vectors; Scheduling; cloud computing; load balancing; resource allocation;
fLanguage
English
Publisher
ieee
Conference_Titel
Teletraffic Congress (ITC 24), 2012 24th International
Conference_Location
Krakow
Print_ISBN
978-1-4673-1292-9
Electronic_ISBN
978-0-9836283-3-0
Type
conf
Filename
6331819
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