DocumentCode
267058
Title
Divide the Task, Multiply the Outcome: Cooperative VM Consolidation
Author
Sedaghat, Mina ; Hernandez-Rodriguez, Francisco ; Elmroth, Erik ; Girdzijauskas, Sarunas
Author_Institution
Dept. of Comput. Sci., Umea Univ., Umea, Sweden
fYear
2014
fDate
15-18 Dec. 2014
Firstpage
300
Lastpage
305
Abstract
Efficient resource utilization is one of the main concerns of cloud providers, as it has a direct impact on energy costs and thus their revenue. Virtual machine (VM) consolidation is one the common techniques, used by infrastructure providers to efficiently utilize their resources. However, when it comes to large-scale infrastructures, consolidation decisions become computationally complex, since VMs are multi-dimensional entities with changing demand and unknown lifetime, and users often overestimate their actual demand. These uncertainties urges the system to take consolidation decisions continuously in a real time manner. In this work, we investigate a decentralized approach for VM consolidation using Peer to Peer (P2P) principles. We investigate the opportunities offered by P2P systems, as scalable and robust management structures, to address VM consolidation concerns. We present a P2P consolidation protocol, considering the dimensionality of resources and dynamicity of the environment. The protocol benefits from concurrency and decentralization of control and it uses a dimension aware decision function for efficient consolidation. We evaluate the protocol through simulation of 100,000 physical machines and 200,000 VM requests. Results demonstrate the potentials and advantages of using a P2P structure to make resource management decisions in large scale data centers. They show that the P2P approach is feasible and scalable and produces resource utilization of 75% when the consolidation aim is 90%.
Keywords
cloud computing; groupware; peer-to-peer computing; protocols; resource allocation; virtual machines; P2P consolidation protocol; P2P systems; VM requests; cloud providers; control concurrency; control decentralization; cooperative VM consolidation; decentralized approach; dimension aware decision function; efficient resource utilization; energy costs; large scale data centers; multidimensional entities; peer-to-peer principles; physical machines; resource management decisions; robust management structures; virtual machine consolidation; Equations; Mathematical model; Memory management; Monitoring; Power demand; Protocols; Resource management; Cloud computing; Gossip protocols; Peer to Peer; Resource management; VM consolidation;
fLanguage
English
Publisher
ieee
Conference_Titel
Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on
Conference_Location
Singapore
Type
conf
DOI
10.1109/CloudCom.2014.81
Filename
7037681
Link To Document