DocumentCode :
246333
Title :
Autonomic Resource Allocation for Cloud Data Centers: A Peer to Peer Approach
Author :
Sedaghat, Mina ; Hernandez-Rodriguez, Francisco ; Elmroth, Erik
Author_Institution :
Dept. of Comput. Sci., Umea Univ., Umea, Sweden
fYear :
2014
fDate :
8-12 Sept. 2014
Firstpage :
131
Lastpage :
140
Abstract :
We address the problem of resource management for large scale cloud data centers. We propose a Peer to Peer (P2P) resource management framework, comprised of a number of agents, overlayed as a scale-free network. The structural properties of the overlay, along with dividing the management responsibilities among the agents enables the management framework to be scalable in terms of both the number of physical servers and incoming Virtual Machine (VM) requests, while it is computationally feasible. While our framework is intended for use in different cloud management functionalities, e.g. Admission control or fault tolerance, we focus on the problem of resource allocation in clouds. We evaluate our approach by simulating a data center with 2500 servers, striving to allocate resources to 20000 incoming VM placement requests. The simulation results indicate that by maintaining an efficient request propagation, we can achieve promising levels of performance and scalability when dealing with large number of servers and placement requests.
Keywords :
cloud computing; complex networks; computer centres; fault tolerant computing; peer-to-peer computing; resource allocation; virtual machines; P2P resource management framework; VM placement requests; autonomic resource allocation; cloud management functionalities; large scale cloud data centers; peer to peer resource management framework; scale-free network; virtual machine placement requests; Mathematical model; Optimization; Peer-to-peer computing; Power demand; Resource management; Robustness; Servers; Cloud computing; Peer to Peer; Resource management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud and Autonomic Computing (ICCAC), 2014 International Conference on
Conference_Location :
London
Type :
conf
DOI :
10.1109/ICCAC.2014.16
Filename :
7024054
Link To Document :
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