Scaling Service-oriented Applications into Geo-distributed Clouds
Refereed conference paper presented and published in conference proceedings


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摘要With the significant prevalence of cloud computing, more and more data centers are built to host and deliver various online services. However, a key challenge faced by service providers is how to scale their applications into geo-distributed data centers to improve application performance as well as minimizing the operational cost. While most existing deployment methods ignore the service dependencies in an application, this paper proposes a general dynamic service deployment framework to bridge this gap, in which a deployment manager and a local scheduler are designed to optimize data center selection and auto-scale the service instances in each data center respectively. More specifically, we formulate the deployment problem across multiple data centers as a compact minimization model, which can be solved efficiently by a genetic algorithm. To evaluate the performance of our approach, extensive experiments are conducted based on a large-scale real-world latency dataset. The experimental results show that our approach substantially outperforms the other existing methods.
著者Zhu JM, Zheng ZB, Zhou YF, Lyu MR
會議名稱IEEE 7th International Symposium on Service-Oriented System Engineering (SOSE)
會議開始日25.03.2013
會議完結日28.03.2013
會議地點Redwood City
會議國家/地區美國
出版年份2013
月份1
日期1
出版社IEEE
頁次335 - 340
國際標準書號978-1-4673-5659-6
電子國際標準書號978-0-7695-4944-6
語言英式英語
關鍵詞Dynamic deployment; genetic algorithm; geo-distributed clouds; service-oriented application
Web of Science 學科類別Computer Science; Computer Science, Hardware & Architecture; Engineering; Engineering, Electrical & Electronic

上次更新時間 2020-27-10 於 00:50