|
Abstract
|
Article Information:
A Formal Modeling and Implementation of Particle Swarm Optimizer for QoS-Aware Service Selection with an Extended Pi Calculus
Desheng Li and Na Deng
Corresponding Author: Desheng Li
Submitted: June 09, 2012
Accepted: July 09, 2012
Published: November 15, 2012 |
Abstract:
|
For past years, Particle Swarm Optimization (PSO), one of the evolutionary computational
techniques, has been intensively studied and applied in both academia and industry. Recently there has
been a shift from consideration of design of concrete algorithms to a consideration of the formalization
models of optimization approaches. However, the meta-search procedure is not the primitive of the algebra,
which not participates in the derivation of the inference of expressions. For this reason, the models above
could not be seen as a unity in a strict mathematics form. Moreover, the operators of traditional algebra
limit the express of complicated processes, such as concurrent patterns. As a result, the cost calculation of
the whole process is not an easy thing only according to the algebraic form itself. Attempting to solve these
issues, a new formal modeling of particle swarm optimizer from a perspective of an extend version of Pi
calculus is proposed in this study, which treats the whole operations in PSO as a kind of meta-search
procedure and owns the cost operator and other operators supporting concurrent patterns. On the basis of
this algebra, the QoS-aware service selection problem can be seen as a particular cost derivation under the
LTS semantics. Based on the theoretical model, a simulator with a core of Pi calculus compiler is
developed to verify our theory and also show the practical applicability in a real scenario.
Key words: Particle swarm optimization , pi calculus QoS, service selection, , , ,
|
|
Abstract
|
PDF
|
HTML |
|
Cite this Reference:
Desheng Li and Na Deng, . A Formal Modeling and Implementation of Particle Swarm Optimizer for QoS-Aware Service Selection with an Extended Pi Calculus. Research Journal of Applied Sciences, Engineering and Technology, (22): 4905-4913.
|
|
|
|
 |
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
 |
| Information |
|
|
|
|
| Sales & Services |
|
|
|
|
