A New Method to QoS Global Optimal Service Selection Driven by Credit

DOI

10.2991/meita-15.2015.144How to use a DOI?

Keywords

Credit level, MILP, Global optimization, Service selection.

Abstract

Aiming at the current Web service selection methods do not take into full consideration the effect of service component’s dynamic on the performance of service-oriented application system, a credit-aware per-service method to service selection is proposed in our paper, which introduces credit level into service selection model and is considered as Mixed Integer Linear Programming (MILP) problem. Composite system at run time can constrain service selection according to the high-availability of service components perceived by itself and the service level requirements of users, and then dynamically bind the best of a set of services. Simulation experimental results show that the new approach can effectively lower the extra time overhead caused by repeated selection that arises from the service component’s dynamic, and then enhance the QoS (Quality of Service) of composite system. Meanwhile, our method is superior to the other traditional Web service selection approaches because it improves the efficiency of CPU usage.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Xiaohua Guo
AU  - Jing Jiang
AU  - Xuefei Li
PY  - 2015/08
DA  - 2015/08
TI  - A New Method to QoS Global Optimal Service Selection Driven by Credit
BT  - Proceedings of the 2015 International Conference on Materials Engineering and Information Technology Applications
PB  - Atlantis Press
SP  - 785
EP  - 792
SN  - 2352-5401
UR  - https://doi.org/10.2991/meita-15.2015.144
DO  - 10.2991/meita-15.2015.144
ID  - Guo2015/08
ER  -