An Optimized Task Duplication Based Scheduling in Parallel System

By the inherent nature of solving enormous number of problems with the concurrent execution, parallel process methods grow to be a popular technique. The challenges of parallel computing are dealing with the computing resources for the number of tasks and complexity, dependency, resource starvation, load balancing and efficiency. In this paper, the brief discussion about the parallel computation is carried out, and numerous performance issues are also discovered as an open issue. The risk encountered in parallel computing is the motivation to analyze different optimization techniques to accomplish the tasks without risky environment. Genetic Algorithm (GA) is another approach to make the concept of scheduling easy and fast. Here the paper presents a Task Duplication based Genetic Algorithm with Load Balance (TD-GA) approach on parallel processing for effective scheduling of multiple tasks with less schedule length and load balance. TD-GA algorithm truly handles the issues very well and the results show that complexity, load balance and resource utilization are finely managed when compared to the other optimization approaches.