QSynth: A Tool for QoS-aware Automatic Service Composition

Abstract

With the proliferation of Web services, service engineers demand good automatic service composition algorithms that not only synthesize the correct work plans from thousands of services but also satisfy the quality requirements of the users. Our observation is that conventional approaches suffer from serious limitations in scalability and accuracy when addressing both requirements simultaneously. We have designed and implemented a tool QSynth to use QoS objectives of service requests as the search directives. This approach effectively prunes the search space and significantly improves the accuracy of the search results. Evaluations show that, compared to the state of the art, QSynth achieves superior scalability and accuracy with respect to a large variety of composition scenarios. Our design of QSynth won the performance championship of Web Services Challenge 2009.

Scaling Up Web Service Composition with the Skyline Operator

“…We use plug-in matching degree to match services: two services can be connected if the input of a service is a subset of the output of the other service. This semantic model, borrowed from [12], is consistent with many proposed web service composition approaches, e.g., [13]- [15].…”

QoS-aware automatic syntactic service composition problem: Complexity and resolution

“…This algorithm is more efficient on WSC-09 instances than already published algorithms [12], [13], [16].…”

“…That's why these two criteria, maxmin-type (or equivalently minmax-type) criteria, can be similarly processed by computing optimal path. Polynomial-time algorithm has been proposed in [12], [13], [16] for solving the service composition problem with a maxmin-type criterion. This composition problem is the subject of the WSC-09 and a lot of papers have proposed different approaches to solve it.…”

“…In [11] and [13], the WSC-09 first run-up winners propose a polynomial-time algorithm to solve the minimal ESC and maximal TSC problems. Its worst case complexity, given in [13], is O(a|S| 2 ), with a the average number of services' input data.…”

“…Its worst case complexity, given in [13], is O(a|S| 2 ), with a the average number of services' input data. This algorithm proceeds in two steps: in the first one, a forward search aims to eliminate useless services for satisfying the user's query and, at the same time, computing optimal QoS values of useful services; in the second stage, a backtrack search is executed to determine the optimal composite service.…”