A Reliable Web Services Selection Method for Concurrent Requests
Abstract: Current methods of
service selection based on quality of service (QoS) usually focus on a single service request at a time, or let the users
in a waiting queue wait for Web services when the same functional Web service
has more than one requests, and then choose the Web service with the best QoSfor
the current request according to its own needs. However, there are multiple
service requests for thesame functional web service at a time in practice and
we cannot choose the best service for users everytime because of the service’s
load. This paper aims at solving the Web Services selection for concurrent requests
and developing a global optimal selection method for multiple similar service
requesters to optimize the system resources. It proposes the improved social
cognitive (ISCO) algorithm which uses genetic algorithm for observational
learning and uses deviating degree to evaluate the solution.Furthermore, to
enhance the efficiency of ISCO, the elite strategy is used in ISCO algorithm.
We evaluateperformance of the ISCO algorithm and the selection method through
simulations. The simulation results demonstrate that the ISCO is valid for
optimization problems with discrete data and more effective than ACO and GA.
Author: Guiming Lu, Yan Hai,
Yaoyao Sun
Journal Code: jptkomputergg140129
