GRID SERVICE DISCOVERY WITH ROUGH SETS

[mohanasundaram]

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Grid Service Discovery with Rough Sets

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Maozhen Li, Member, IEE, Bin Yu, Omer Rana, and Zidong Wang, Senior Member, IEE

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Abstract\

The computational grid is rapidly evolving into a service-oriented computing infrastructure that facilitates resource sharing
and large-scale problem solving over the Internet. Service discovery becomes an issue of vital importance in utilizing grid facilities. This
paper presents ROSSE, a Rough sets-based search engine for grid service discovery. Building on the Rough sets theory, ROSSE is
novel in its capability to deal with the uncertainty of properties when matching services. In this way, ROSSE can discover the services
that are most relevant to a service query from a functional point of view. Since functionally matched services may have distinct
nonfunctional properties related to the quality of service (QoS), ROSSE introduces a QoS model to further filter matched services with
their QoS values to maximize user satisfaction in service discovery. ROSSE is evaluated from the aspects of accuracy and efficiency in
discovery of computing services

Abstract: A rough set is a formal approximation of a crisp set (conventional set) in terms of a pair of sets which give the lower and the upper approximation of the original set. The lower and upper approximation sets themselves are crisp sets in the standard version of rough set theory, but in other variations, the approximating sets may be fuzzy sets as well. The computational grid is rapidly evolving into a service-oriented computing infrastructure that facilitates resource sharing and large-scale problem solving over the Internet. Service discovery becomes an issue of vital importance in utilizing grid facilities. This paper presents ROSSE, a Rough sets-based search engine for grid service discovery. Building on the Rough sets theory, ROSSE is novel in its capability to deal with the uncertainty of properties when matching services. In this way, ROSSE can discover the services that are most relevant to a service query from a functional point of view. Since functionally matched services may have distinct nonfunctional properties related to the quality of service (QoS), ROSSE introduces a QoS model to further filter matched services with their QoS values to maximize user satisfaction in service discovery.
Technology to use:.NET

Reference: http://seminarsprojects.net/Thread-grid-...z11BMhDpp3

[kira_]

GRID SERVICE DISCOVERY WITH ROUGH SETS
Abstract: A rough set is a formal approximation of a crisp set (conventional set) in terms of a pair of sets which give the lower and the upper approximation of the original set. The lower and upper approximation sets themselves are crisp sets in the standard version of rough set theory, but in other variations, the approximating sets may be fuzzy sets as well. The computational grid is rapidly evolving into a service-oriented computing infrastructure that facilitates resource sharing and large-scale problem solving over the Internet. Service discovery becomes an issue of vital importance in utilizing grid facilities. This paper presents ROSSE, a Rough sets-based search engine for grid service discovery. Building on the Rough sets theory, ROSSE is novel in its capability to deal with the uncertainty of properties when matching services. In this way, ROSSE can discover the services that are most relevant to a service query from a functional point of view. Since functionally matched services may have distinct nonfunctional properties related to the quality of service (QoS), ROSSE introduces a QoS model to further filter matched services with their QoS values to maximize user satisfaction in service discovery.