Job scheduling based on reliability, time and cost constraints under Grid environment

The advent of Grid environments made feasible the solution of computational intensive problems in a reliable and cost-effective way. As scheduling carry out more complex and mission-critical applications, Quality of Service (QoS) analysis serves to ensure that each application meets user requirements. In that frame, author presents a novel Ant colony algorithm with a quick convergence of ant to move from source to destination which allows the mapping of job processes to Grid provided services assuring at the same time end-to-end provision of QoS (cost, makespan and reliability) based on user-defined parameters and preferences. Paper also demonstrate the operation of the implemented algorithm using three different heuristics and evaluate its effectiveness using a Grid scenario.