An effective method for service components selection based on micro-canonical annealing considering dependability assurance

Abstract

Distributed virtualization changes the pattern of building software systems. However, it brings some problems on dependability assurance owing to the complex social relationships and interactions between service components. The best way to solve the problems in a distributed virtualized environment is dependable service components selection. Dependable service components selection can be modeled as finding a dependable service path, which is a multiconstrained optimal path problem. In this paper, a service components selection method that searches for the dependable service path in a distributed virtualized environment is proposed from the perspective of dependability assurance. The concept of Quality of Dependability is introduced to describe and constrain software system dependability during dynamic composition. Then, we model the dependable service components selection as a multiconstrained optimal path problem, and apply the Adaptive Bonus-Penalty Microcanonical Annealing algorithm to find the optimal dependable service path. The experimental results show that the proposed algorithm has high search success rate and quick converges.