Authors
Tian Huat Tan, Manman Chen, Jun Sun, Yang Liu, Étienne André, Yinxing Xue, Jin Song Dong
Publication date
2016/5/14
Book
Proceedings of the 38th International Conference on Software Engineering
Pages
85-95
Description
Recently, many large enterprises (e.g., Netflix, Amazon) have decomposed their monolithic application into services, and composed them to fulfill their business functionalities. Many hosting services on the cloud, with different Quality of Service (QoS) (e.g., availability, cost), can be used to host the services. This is an example of competing services. QoS is crucial for the satisfaction of users. It is important to choose a set of services that maximize the overall QoS, and satisfy all QoS requirements for the service composition. This problem, known as optimal service selection, is NP-hard. Therefore, an effective method for reducing the search space and guiding the search process is highly desirable. To this end, we introduce a novel technique, called Probabilistic Hierarchical Refinement (ProHR). ProHR effectively reduces the search space by removing competing services that cannot be part of the selection. ProHR …
Total citations
201620172018201920202021202220232365421
Scholar articles
TH Tan, M Chen, J Sun, Y Liu, É André, Y Xue… - Proceedings of the 38th International Conference on …, 2016