DocumentCode :
267056
Title :
Energy-Efficient Data Center Networks Planning with Virtual Machine Placement and Traffic Configuration
Author :
Ting Yang ; Young Choon Lee ; Zomaya, Albert Y.
Author_Institution :
Sch. of Electr. Eng. & Autom., Tianjin Univ., Tianjin, China
fYear :
2014
fDate :
15-18 Dec. 2014
Firstpage :
284
Lastpage :
291
Abstract :
Data Center (DC), the underlying infrastructure of cloud computing, becomes startling large with more powerful computing and communication capability to satisfy the wide spectrum of composite applications. In a large scale DC, a great number of switches connect servers into one complex network. The energy consumption of this communication network has skyrocketed and become the same league as the computing servers´ costs. More than one-third of the total energy in DCs is consumed by communication links, switching and aggregation elements. Saving Data Center Network (DCN) energy to improve data center efficiency (power usage effectiveness or PUE) become the key technique in green computing. In this paper, we present VPTCA as an energy-efficient data center network planning solution that collectively deals with virtual machine placement and communication traffic configuration. VPTCA aims to reduce the DCN´s energy consumption. In particular, interrelated VMs are assigned into the same server or pod, which effectively helps to reduce the amount of transmission load. In the layer of traffic message, VPTCA optimally uses switch ports and link bandwidth to balance the load and avoid congestions, enabling DCN to increase its transmission capacity, and saving a significant amount of network energy. In our evaluation via NS-2 simulations, the performance of VPTCA is measured and compared with two well-known DCN management algorithms, Global First Fit and Elastic Tree. Based on our experimental results, VPTCA outperforms existing algorithms in providing DCN more transmission capacity with less energy consumption.
Keywords :
cloud computing; computer centres; green computing; power aware computing; switching networks; telecommunication power management; telecommunication traffic; virtual machines; DCN energy Saving; DCN energy consumption; DCN management algorithms; ElasticTree algorithms; NS-2 simulations; PUB; VPTCA; VPTCA performance; aggregation elements; cloud computing; communication links; communication network; complex network; computing server costs; data center network energy saving; energy consumption; energy-efficient data center network planning; global first fit algorithms; green computing; large scale DC; network energy; power usage effectiveness; switching elements; traffic configuration; transmission load; virtual machine placement; virtual machine placement communication traffic configuration; Encoding; Energy consumption; Energy efficiency; Heuristic algorithms; Planning; Routing; Servers; Data Center Network; Energy Efficiency; Traffic Configuration; Virtual Machine Placement;
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.2014.135
Filename :
7037679
Link To Document :
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