Ant Colony Optimization Algorithm For Dynamic Scheduling For Jobs In Computational Grid

Ant Colony Optimization Algorithm for Dynamic Scheduling for Jobs in Computational Grid

Ant Colony Optimization Algorithm for Load Balancing in Grid Computing (UUM Press)

Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources. This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. The proposed algorithm is known as the enhance Ant Colony Optimization (EACO). The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism. The resource allocation problem is modelled as a graph that can be used by the ant to deliver its pheromone. This graph consists of four types of vertices which are job, requirement, resource and capacity that are used in constructing the grid resource management element. The proposed EACO algorithm takes into consideration the capacity of resources and the characteristics of jobs in determining the best resource to process a job. EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form. The initial pheromone value of each resource for each job is calculated based on the estimated transmission time and execution time of a given job. Resources with high pheromone value are selected to process the submitted jobs. Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization. Experimental results show that EACO produced better grid resource management solution.

Proceedings of the 1st International Conference on Smart Innovation, Ergonomics and Applied Human Factors (SEAHF)

This book addresses a range of real-world issues including industrial activity, energy management, education, business and health. Today, technology is a part of virtually every human activity, and is used to support, monitor and manage equipment, facilities, commodities, industry, business, and individuals’ health, among others. As technology evolves, new applications, methods and techniques arise, while at the same time citizens’ expectations from technology continue to grow. In order to meet the nearly insatiable demand for new applications, better performance and higher reliability, trustworthiness, security, and power consumption efficiency, engineers must deliver smart innovations, i.e., must develop the best techniques, technologies and services in a way that respects human beings and the environment. With that goal in mind, the key topics addressed in this book are: smart technologies and artificial intelligence, green energy systems, aerospace engineering/robotics and IT, information security and mobile engineering, IT in bio-medical engineering and smart agronomy, smart marketing, management and tourism policy, technology and education, and hydrogen and fuel-cell energy technologies.