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
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;
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