Abstract
Web service composition is widely used to extend the function of web services. Different users have different requirements of QoSs (Quality of Services) making them face many problems. The requirement of a special QoS may be a hard requirement or a soft requirement. The hard requirement refers to the QoS which must be satisfied to the user, and the soft one means that the requirement is flexible. This paper tries to solve the service composition problem when there are two kinds of requirements of QoSs. To satisfy various kinds of requirement of the QoS, we propose a composition method based on our proposed framework. We give an analysis from composition models of services and from related QoE (Quality of Experience) of web services. Then, we rank the service candidates and the service requests together. Based on the ranking, a heuristics is proposed for service selection and composition-GLLB (global largest number of service requests first, local best fit service candidate first), which uses “lost value” in the scheduling to denote the QoE. Comparisons are used to evaluate our method. Comparisons show that GLLB reduces the value of NUR (Number of Unfinished service Requests), FV (Failure Value), and AFV (Average Failure Value).
Highlights
In recent years, high-performance hardware and software resources make the Cloud widely used by companies and departments
We select the “Largest First” because if the service request has a larger value in aggregation function, it always has more difficult to find a service candidate that satisfies the requirement of the QoS attributes
If we cannot get a service candidate between the left position and the right position, we will search from the end of the right position until we find a service candidate which can satisfy all the requirements of the QoS under the assumption that every requirements of the QoS attribute which belongs to the hard requirement (Step 11, in Algorithm 2) have been satisfied
Summary
High-performance hardware and software resources make the Cloud widely used by companies and departments. A successful web service in service-oriented Cloud computing, tries to provide functionality as request, and ensures to satisfy the requirement of QoSs [3]. When users have many service composition requests, the selection order of web services influences the scheduling result of others, which have diverse value in QoE. Complexity proposing an improvised QoS mathematical model; (7) revenue maximization; (8) optimization of the service discovery process; (9) proposing new frameworks and structures Most of time, those nine targets are influenced by each other, such that (3) algorithm improvements always influence (5) selfadaptability. The main problem of this paper is to schedule the web services when (1) the web service has different QoS attributes; (2) the service composition request has various requirements to diverse QoS attributes (hard or soft); (3) there are different functions for QoE to QoS for various kinds of requirements.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
