Service-associative-index-map-based quality of service (QoS) perception Top-k service combination system

Abstract

The invention discloses a service-associative-index-map-based quality of service (QoS) perception Top-k service combination system. A first layer is a system initialization and index construction layer, and mainly comprises a service description information extraction module, a semantic information extraction module and a QoS information extraction module. A second layer is a service request processing and solution construction layer, and mainly comprises a Web service combination available parameter list establishment module, a service-information-and-index-based service discovery module, a QoS-perception-based service filtering module, a service associative index map updating module and a QoS-based service combination solution judgment module. Compared with the prior art, the system can simultaneously output a plurality of combination schemes meeting QoS requirements, effectively save a service combination solution space by means of a service associative index map, reduce backtracking times, improve service combination efficiency and ensure the accuracy of a service combination result, and is more applicable to automatic massive network service combination meeting the individual requirements of a large number of users in a cloud computing environment.

Description

technical field [0001] The invention relates to a QoS-aware Top-k service composition system, in particular to a QoS-aware Top-k service composition method based on a service association index graph. Background technique [0002] The service composition method based on the service association index graph proposed by the present invention is an extension focusing on the following problems exposed by the traditional graph planning method: [0003] (1) The traditional graph planning method solves the service composition scheme, the search space is large, and the efficiency is low. When the traditional graph planning method performs service composition, after the planning graph is established, a reverse search is required to determine the final composite service. If the number of candidate services is slightly larger, the search space for solutions will expand rapidly, and it is difficult to improve the combination efficiency. [0004] (2) Traditional graph planning methods ar...

AI Technical Summary

Problems solved by technology

If the number of candidate services is slightly larger, the search space of the solution solution will expand rapidly, and it is difficult to improve the combination efficiency

[0004] (2) It is difficult for the traditional graph planning method to support solving the Top-k service composition scheme

If you need to solve Top-k combined services, since each combined service needs to perform a reverse search at the end, the search space for the solution solution will explode and the efficiency will be greatly reduced.

[0005] (3) The traditional graph planning method solves the service composition scheme, and the semantic support is not enough

[0013] But in summary, the effect of these methods on the above three problems is not obvious

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