Name
Abstract | ||
|---|---|---|
Service selection is crucial to service composition in determining the composite Quality of Service (QoS). The proliferation of composable services on the Internet and the practical need for timely delivering optimized composite solutions motivate the adoption of population-based algorithms for QoS-aware service selection. However, existing population-based algorithms are generally complicated to ... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TSC.2016.2612663 | IEEE Transactions on Services Computing |
Keywords | Field | DocType |
Quality of service,Optimization,Approximation algorithms,Search problems,Web services,Artificial bee colony algorithm | Population,Approximation algorithm,Artificial bee colony algorithm,Computer science,Swarm intelligence,Quality of service,Algorithm,Artificial intelligence,Local search (optimization),Optimization problem,Machine learning,Metaheuristic | Journal |
Volume | Issue | ISSN |
12 | 2 | 1939-1374 |
Citations | PageRank | References |
3 | 0.37 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xianzhi Wang | 1 | 276 | 40.32 |
| Xiaofei Xu | 2 | 408 | 70.26 |
| Quan Z. Sheng | 3 | 3520 | 301.77 |
| Zhong-Jie Wang | 4 | 356 | 64.60 |
| Lina Yao | 5 | 981 | 93.63 |