- title = "A Genetic Programming Approach to Distributed {QoS}-Aware Web Service Composition",
- author = "Yang Yu and Hui Ma and Mengjie Zhang",
- pages = "1840--1846",
- booktitle = "Proceedings of the 2014 IEEE Congress on Evolutionary Computation",
- year = "2014",
- month = "6-11 " # jul,
- editor = "Carlos A. {Coello Coello}",
- address = "Beijing, China",
- ISBN = "0-7803-8515-2",
- keywords = "genetic algorithms, Genetic programming, Parallel and Distributed Evolutionary Computation in the Cloud Era",
-
DOI = "
doi:10.1109/CEC.2014.6900416",
- abstract = "Web service composition has emerged as a promising technique for building complex web applications, thus supporting business-to-business and enterprise application integration. Nowadays there are increasing numbers of web services are distributed across the Internet. For a given service request there are many ways of service composition that can meet the service functional requirements (inputs and outputs) but have different qualities of Services (QoS), like response time or execution cost. QoS-aware web service composition seeks to find a service composition with optimised QoS properties. Genetic Programming is an efficient tool for tacking such optimisation problems efficiently. This paper proposes a novel GP-based approach for distributed web service composition where multiple QoS constraints are considered simultaneously. A series of experiments have been conducted to evaluate the proposed approach with test data. The results show that our approach is efficient and effective to find a near-optimal service composition solution in the context of distributed service environment.",
-
notes = "Estimates response time (latency) using GNP global
network positioning of of web server. GP tree composed
of sequence, choice, parallel loop with leafs being
atomic web services. Pop 50, generations
500.
WCCI2014",
