NDLI: Towards minimizing cost for composite data-intensive services

Content Provider	IEEE Xplore Digital Library
Author	Lijuan Wang Jun Shen Changyan Di Yan Li Qingguo Zhou
Copyright Year	2013
Description	Author affiliation: Sch. of Inf. Syst. & Technol., Univ. of Wollongong, Wollongong, NSW, Australia (Lijuan Wang; Jun Shen) \|\| Sch. of Inf. Sci. & Eng., Lanzhou Univ., Lanzhou, China (Changyan Di; Yan Li; Qingguo Zhou)
Abstract	Service-oriented architecture provides a scalable and flexible framework to implement loosely-coupled, standards-based, and protocol-independent distribute computing. One of its goals is to make use of the distributed services with different functions to build powerful composite services. Service composition is an active research area in service computing. Existing research is endeavoring to achieve desirable quality levels of composite services and improve customer satisfaction. The service-oriented approach using Web services is also of great interest for the implementation of data-intensive processes such as data mining, image processing and so on. The applications based on data-intensive services have become the most challenging type of applications in service-oriented architecture. The service-based strategy provides maximal flexibility when designing data-intensive applications. Huge data sets that may each be replicated in different data centers have to be exchanged between several services. The movement of mass data influences the performance of the whole application process. Especially, the price of services will be different when considering the data center's locations and the amount of data transferred. It is desirable to find the cost minimized service composition solution in service computing. Therefore, how to select appropriate data centers for accessing data replicas and how to select services with lowest associated costs are emerging problems when deploying and executing data-intensive service applications. In this paper, a cost minimizing service composition model for data-intensive applications is proposed. Furthermore, how bio-inspired algorithms offer advantages to solve such problems will be presented.
Starting Page	293
Ending Page	298
File Size	155527
Page Count	6
File Format	PDF
ISBN	9781467360845
e-ISBN	9781467360852
DOI	10.1109/CSCWD.2013.6580978
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimization Abstracts Concrete Quality of service Heuristic algorithms Biological systems Business data-intensive application bio-inspired algorithms service composition quality of service
Content Type	Text
Resource Type	Article

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