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AuthorZhang, Fan
AuthorHwang, Kai
AuthorKhan, Samee U.
AuthorMalluhi, Qutaibah M.
Available date2021-09-08T06:49:45Z
Publication Date2016
Publication NameIEEE Transactions on Services Computing
AbstractA cloud mashup is composed of multiple services with shared datasets and integrated functionalities. For example, the elastic compute cloud (EC2) provided by Amazon Web Service (AWS), the authentication and authorization services provided by Facebook, and the Map service provided by Google can all be mashed up to deliver real-time, personalized driving route recommendation service. To discover qualified services and compose them with guaranteed quality of service (QoS), we propose an integrated skyline query processing method for building up cloud mashup applications. We use a similarity test to achieve optimal localized skyline. This mashup method scales well with the growing number of cloud sites involved in the mashup applications. Faster skyline selection, reduced composition time, dataset sharing, and resources integration assure the QoS over multiple clouds. We experiment with the quality of web service (QWS) benchmark over 10,000 web services along six QoS dimensions. By utilizing block-elimination, data-space partitioning, and service similarity pruning, the skyline process is shortened by three times, when compared with two state-of-the-art methods.
SponsorAcknowledgments: The authors would like to thank the support by China's 973 Basic Research Grant 2011CB302505, awarded through Tsinghua University, Beijing. This work was also supported by the Guangdong Innovation R/D Team under funding No.201001D0104726115. The work was also partially supported by China's 863 Research Grant No. 2008AA01Z141 and the NSFC Grant No. 61173176.
PublisherInstitute of Electrical and Electronics Engineers
SubjectCloud mashup
MapReduceand quality of services
skyline query processing
web services
TitleSkyline Discovery and Composition of Multi-Cloud Mashup Services
Issue Number1
Volume Number9

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