Details
| Original language | English |
|---|---|
| Article number | 7 |
| Journal | ACM transactions on the web |
| Volume | 6 |
| Issue number | 2 |
| Publication status | Published - 4 Jun 2012 |
Abstract
Dynamic selection of Web services at runtime is important for building flexible and loosely-coupled serviceoriented applications. An abstract description of the required services is provided at design-time, and matching service offers are located at runtime. With the growing number of Web services that provide the same functionality but differ in quality parameters (e.g., availability, response time), a decision needs to be made on which services should be selected such that the user's end-to-end QoS requirements are satisfied. Although very efficient, local selection strategy fails short in handling global QoS requirements. Solutions based on global optimization, on the other hand, can handle global constraints, but their poor performance renders them inappropriate for applications with dynamic and realtime requirements. In this article we address this problem and propose a hybrid solution that combines global optimization with local selection techniques to benefit from the advantages of both worlds. The proposed solution consists of two steps: first, we use mixed integer programming (MIP) to find the optimal decomposition of global QoS constraints into local constraints. Second, we use distributed local selection to find the best Web services that satisfy these local constraints. The results of experimental evaluation indicate that our approach significantly outperforms existing solutions in terms of computation time while achieving close-to-optimal results.
Keywords
- Optimization, QoS, Service composition, Web services
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
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In: ACM transactions on the web, Vol. 6, No. 2, 7, 04.06.2012.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - A Hybrid Approach for Efficient Web Service Composition with End-to-End QoS Constraints
AU - Alrifai, Mohammad
AU - Risse, Thomas
AU - Nejdl, Wolfgang
PY - 2012/6/4
Y1 - 2012/6/4
N2 - Dynamic selection of Web services at runtime is important for building flexible and loosely-coupled serviceoriented applications. An abstract description of the required services is provided at design-time, and matching service offers are located at runtime. With the growing number of Web services that provide the same functionality but differ in quality parameters (e.g., availability, response time), a decision needs to be made on which services should be selected such that the user's end-to-end QoS requirements are satisfied. Although very efficient, local selection strategy fails short in handling global QoS requirements. Solutions based on global optimization, on the other hand, can handle global constraints, but their poor performance renders them inappropriate for applications with dynamic and realtime requirements. In this article we address this problem and propose a hybrid solution that combines global optimization with local selection techniques to benefit from the advantages of both worlds. The proposed solution consists of two steps: first, we use mixed integer programming (MIP) to find the optimal decomposition of global QoS constraints into local constraints. Second, we use distributed local selection to find the best Web services that satisfy these local constraints. The results of experimental evaluation indicate that our approach significantly outperforms existing solutions in terms of computation time while achieving close-to-optimal results.
AB - Dynamic selection of Web services at runtime is important for building flexible and loosely-coupled serviceoriented applications. An abstract description of the required services is provided at design-time, and matching service offers are located at runtime. With the growing number of Web services that provide the same functionality but differ in quality parameters (e.g., availability, response time), a decision needs to be made on which services should be selected such that the user's end-to-end QoS requirements are satisfied. Although very efficient, local selection strategy fails short in handling global QoS requirements. Solutions based on global optimization, on the other hand, can handle global constraints, but their poor performance renders them inappropriate for applications with dynamic and realtime requirements. In this article we address this problem and propose a hybrid solution that combines global optimization with local selection techniques to benefit from the advantages of both worlds. The proposed solution consists of two steps: first, we use mixed integer programming (MIP) to find the optimal decomposition of global QoS constraints into local constraints. Second, we use distributed local selection to find the best Web services that satisfy these local constraints. The results of experimental evaluation indicate that our approach significantly outperforms existing solutions in terms of computation time while achieving close-to-optimal results.
KW - Optimization
KW - QoS
KW - Service composition
KW - Web services
UR - http://www.scopus.com/inward/record.url?scp=84863617430&partnerID=8YFLogxK
U2 - 10.1145/2180861.2180864
DO - 10.1145/2180861.2180864
M3 - Article
AN - SCOPUS:84863617430
VL - 6
JO - ACM transactions on the web
JF - ACM transactions on the web
SN - 1559-1131
IS - 2
M1 - 7
ER -