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A cost-effective scheme supporting adaptive service migration in cloud data center |
Bing YU1,Yanni HAN1,*(),Hanning YUAN2,Xu ZHOU1,Zhen XU1 |
1. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China 2. International School of Software, Beijing Institute of Technology, Beijing 100081, China |
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Abstract Cloud computing as an emerging technology promises to provide reliable and available services on demand. However, offering services for mobile requirements without dynamic and adaptive migration may hurt the performance of deployed services. In this paper, we propose MAMOC, a cost-effective approach for selecting the server and migrating services to attain enhanced QoS more economically. The goal of MAMOC is to minimize the total operating cost while guaranteeing the constraints of resource demands, storage capacity, access latency and economies, including selling price and reputation grade. First, we devise an objective optimal model with multi-constraints, describing the relationship among operating cost and the above constraints. Second, a normalized method is adopted to calculate the operating cost for each candidate VM. Then we give a detailed presentation on the online algorithm MAMOC, which determines the optimal server. To evaluate the performance of our proposal, we conducted extensive simulations on three typical network topologies and a realistic data center network. Results show that MAMOC is scalable and robust with the larger scales of requests and VMs in cloud environment. Moreover, MAMOC decreases the competitive ratio by identifying the optimal migration paths, while ensuring the constraints of SLA as satisfying as possible.
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Keywords
cloud computing
software-defined networking
data center
service migration
QoS
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Corresponding Author(s):
Yanni HAN
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Just Accepted Date: 20 May 2015
Issue Date: 10 November 2015
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