By a News Reporter-Staff News Editor at Computer Weekly News -- Research findings on Cluster Computing are discussed in a new report. According to news originating from Hangzhou, People's Republic of China, by VerticalNews correspondents, research stated, "With the development of web technologies and cloud computing, more and more services which provide similar functionality but differ in QoS are deployed on the Internet via cloud platforms. Recently, skyline analysis is adopted to select candidate services with better QoS to facilitate the process of QoS-aware service composition."
Our news journalists obtained a quote from the research from Hangzhou Normal University, "However, the fast increasing number of services, multiple QoS attributes to be considered, and dynamic service environment pose a big challenge to skyline service selection. In this paper, we present a parallel skyline service selection method to improve the efficiency by upgrading the MapReduce paradigm. An angle-based dataspace partitioning approach is employed in our MapReduce based skyline service selection. In particular, we explore the dominance power of local skyline services to improve the efficiency of selection, and present two detailed algorithms. To handle the dynamic nature of service environment, we employ Paper-Tape (PT) model which is used to rapidly locate varying services, and present a dynamic skyline service selection algorithm based on PT model."
According to the news editors, the research concluded: "By experimenting over both real and synthetical datasets, we demonstrate the efficiency of our proposed methods."
For more information on this research see: Selecting skyline services for QoS-aware composition by upgrading MapReduce paradigm. Cluster Computing-The Journal of Networks Software Tools and Applications, 2013;16(4):693-706. Cluster Computing-The Journal of Networks Software Tools and Applications can be contacted at: Springer, 233 Spring St, New York, NY 10013, USA.
The news correspondents report that additional information may be obtained from J. Wu, Hangzhou Normal Univ, Hangzhou Inst Serv Engn, Hangzhou, Zhejiang, People's Republic of China. Additional authors for this research include L. Chen, Q. Yu, L. Kuang, Y.L. Wang and Z.H. Wu.
Keywords for this news article include: Asia, Hangzhou, Cluster Computing, People's Republic of China
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