Title :
OCPA: An Algorithm for Fast and Effective Virtual Machine Placement and Assignment in Large Scale Cloud Environments
Author :
Zhenyun Zhuang ; Chun Guo
Author_Institution :
Salesforce.com, Inc., San Francisco, CA, USA
Abstract :
Cloud Computing is increasingly being deployed as a fast and economic solution to various requests that require instantiating computing resources to serve customers´ need. Despite the distinctions among the three commonly accepted service models (i.e., IaaS, PaaS, and SaaS), any large scale cloud computing deployment requires the instantiation of multiple VMs (Virtual Machines) in a coordinated manner. These VMs may further need to be placed in multiple geographically distributed data centers, and users that are closer to a VM enjoy the benefits of smaller response time, higher bandwidth, hence better performance. Thus, how to appropriately place VMs and assign them to cloud users can have significant impact on the latter´s performance. In this work, we consider the problems of VM placement and assignment. Based on a set of unique design principles, we propose an effective and efficient solution which is referred to as OCPA (Opportunity Cost based VM Placement and Assignment). OCPA can achieve much better performance and the running time complexity is kept linear.
Keywords :
cloud computing; computer centres; virtual machines; OCPA; cloud computing; large scale cloud environments; linear time complexity; multiple VMs; multiple geographically distributed data centers; opportunity cost based VM placement and assignment; virtual machine assignment; virtual machine placement; Bandwidth; Cloud computing; Distributed databases; Measurement; Sociology; Statistics; Virtual machining; Cloud Computing; Opportunity Cost; Virtual Machine Placement;
Conference_Titel :
Cloud Computing and Big Data (CloudCom-Asia), 2013 International Conference on
Conference_Location :
Fuzhou
Print_ISBN :
978-1-4799-2829-3
DOI :
10.1109/CLOUDCOM-ASIA.2013.81