Title :
Autonomous Decentralized Mechanisms for Generating Global Order in Large-Scale System: Using Metropolis-Hastings Algorithm and Applying to Virtual Machine Placement
Author :
Sakumoto, Yusuke ; Aida, Masaki ; Shimonishi, Hideyuki
Author_Institution :
Grad. Sch. of Syst. Design, Tokyo Metropolitan Univ., Hino, Japan
Abstract :
Since an autonomous decentralized mechanism needs not gather state information for all subsystems, it would have high feasibility for large-scale systems. One of the challenges for leading a property of a large-scale system in desirable direction (i.e., generating global order) by using an autonomous decentralized mechanism is to connect global behavior in a large- scale system and an autonomous action rule of each subsystem. In this paper, based on a statistical mechanics methodology (i.e., Metropolis- Hastings algorithm), we propose a framework of autonomous decentralized mechanisms for generating global order in a system despite each node behaving autonomously. Then, in this paper, we apply the proposed framework to the placement control of virtual machines in data center networks. Thorough experiment, we confirm whether the proposed frame- work generates expected global order, and the performance of the proposed framework.
Keywords :
Markov processes; Monte Carlo methods; computer centres; data communication; large-scale systems; multivariable systems; statistical mechanics; virtual machines; Metropolis-Hastings algorithm; autonomous decentralized mechanism; data center network; global behavior; global order generation; large-scale system; placement control; state information; statistical mechanics methodology; subsystem autonomous action rule; virtual machine placement; Algorithm design and analysis; Large-scale systems; Load management; Load modeling; Network topology; System performance; Virtual machining;
Conference_Titel :
Information and Telecommunication Technologies (APSITT), 2012 9th Asia-Pacific Symposium on
Conference_Location :
Santiago and Valparaiso
Print_ISBN :
978-1-4673-2434-2