Content area

Abstract

Service Oriented Architecture (SOA) approaches are presently getting to be appropriate to embedded devices that feature embedded processing and communication. As a result these services get the ability to be hosted on high end machines to wireless resource constrained devices and on any physical object supported with communication ability. This creates the Internet of Services (IoS) environment. Services from multiple owners can be assembled into a composite service irrespective of their specific Quality of Service (QoS) and related properties for implementing a complex business process. In this context service consumer comes against the problem of selecting best service and for which providing QoS relevant guarantees leads to many challenging issues. One among them is determining a feasible service composition that fulfils a set of conditions while maintaining a good Quality of User Experience (QoUE). The last goal suggests the requirement to enforce an extra optimality prerequisite on the feasibility problem. In this paper, an optimization strategy oriented to efficient composite service selection for IoS model is designed through use of Particle Swarm Optimization (PSO) technique. Furthermore, prior to optimization, the services are assured of rich QoUE, especially trustworthiness in terms of reputation. The proposed work evaluates QoUE using the fuzzy based inference algorithm for identifying QoUE satisfied composite service. Experimental evaluation on a set of real world web services demonstrates the effectiveness of our proposed methodology.

Details

Title
Integrated QoUE and QoS approach for optimal service composition selection in internet of services (IoS)
Author
Balakrishnan, Senthil Murugan 1 ; Sangaiah, Arun Kumar 2 

 School of Information Technology and Engineering, VIT University, Vellore, Tamil Nadu, India 
 School of Computing Science and Engineering, VIT University, Vellore, Tamil Nadu, India 
Pages
22889-22916
Publication year
2017
Publication date
Nov 2017
Publisher
Springer Nature B.V.
ISSN
13807501
e-ISSN
15737721
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1949953211
Copyright
Multimedia Tools and Applications is a copyright of Springer, 2017.