LUO Haoyu, LIU Jin, LIU Xiao, “A Two-Stage Service Replica Strategy for Business Process Efficiency Optimization in Community Cloud,” Chinese Journal of Electronics, vol. 26, no. 1, pp. 80-87, 2017, doi: 10.1049/cje.2016.10.014
Citation: LUO Haoyu, LIU Jin, LIU Xiao, “A Two-Stage Service Replica Strategy for Business Process Efficiency Optimization in Community Cloud,” Chinese Journal of Electronics, vol. 26, no. 1, pp. 80-87, 2017, doi: 10.1049/cje.2016.10.014

A Two-Stage Service Replica Strategy for Business Process Efficiency Optimization in Community Cloud

doi: 10.1049/cje.2016.10.014
Funds:  This work is supported by the National Natural Science Foundation of China (No.61572374, No.61300042, No.U1135005).
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  • Corresponding author: LIU Jin (corresponding author) was born in 1977. He received the Ph.D. degree in computer science from Wuhan University in 2005. He is a professor in State Key Laboratory of Software Engineering, Computer School, Wuhan University. His research interests include software service engineering and software repository mining. (Email:jinliu@whu.edu.cn)
  • Received Date: 2014-12-11
  • Rev Recd Date: 2016-07-11
  • Publish Date: 2017-01-10
  • Business process that facilitates the organization cooperation and resource sharing plays an important role in Community cloud (Comc). The nature of applications and decentralized infrastructure in Comc make it a big challenge in ensuring the execution efficiency of business process, especially when the business requests are in high concurrency. We present a two-stage service replica strategy to improve the execution efficiency of business process by shortening the response time of request to single service and reducing interaction time among distributed services. We initially utilize the social network property of services to pre-allocate the replicas of key services. After that, queueing model is adopted to determine the required additional replicas according to the quantity and frequency of user requests, then schedule service replicas and requests dynamically. Experiments demonstrate the effectiveness of the proposed strategy.
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