Load Distribution Composite Design Pattern for Genetic Algorithm-Based Autonomic Computing Systems

摘要

Current autonomic computing systems are ad hoc solutions that are designedand implemented from the scratch. When designing software, in most cases two ormore patterns are to be composed to solve a bigger problem. A composite designpatterns shows a synergy that makes the composition more than just the sum ofits parts which leads to ready-made software architectures. As far as we know,there are no studies on composition of design patterns for autonomic computingdomain. In this paper we propose pattern-oriented software architecture forself-optimization in autonomic computing system using design patternscomposition and multi objective evolutionary algorithms that software designersand/or programmers can exploit to drive their work. Main objective of thesystem is to reduce the load in the server by distributing the population toclients. We used Case Based Reasoning, Database Access, and Master Slave designpatterns. We evaluate the effectiveness of our architecture with and withoutdesign patterns compositions. The use of composite design patterns in thearchitecture and quantitative measurements are presented. A simple UML classdiagram is used to describe the architecture.