An Adaptive Design Pattern for Genetic Algorithm Based Autonomic Computing System

Abstract

The need for adaptability in software is growing, driven in part by the emergence of pervasive and Autonomic computing. In many cases, it is desirable to enhance existing programs with adaptive behavior, enabling them to execute effectively in dynamic environments. Increasingly, software systems should self adapts to satisfy new requirements and environmental conditions that may arise after deployment. Due to their high complexity, adaptive programs are difficult to specify, design, verify, and validate. In this paper we propose an approach for Genetic Algorithm based Autonomic System using Design Patterns. The proposed pattern satisfies the properties of Autonomic System. This pattern is an amalgamation of different Design Patterns like Observer, Strategy, Singleton, Adapter and Thread per connection. For monitoring we use Observer pattern, Decision making we use Strategy Design Pattern. Adapter, Singleton and Thread per Connection pattern are used for execution of Genetic Algorithm population. Proposed pattern distribute population of Genetic Algorithm to different clients for execution. Main objective of the proposed system is to reduce the load of the server. This design pattern solve multi objective optimization problem using Genetic Algorithm.The pattern is described using a java-like notation for the classes and interfaces. A simple UML class and Sequence diagrams are depicted.KeywordsDesign Patternsdistributed systemGenetic Algorithms and Autonomic System