Mining knowledge for NP-complete scheduling problems

In this paper for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the mean tardiness (lateness of due date) with utilizing maximum resources. Performance of algorithm evaluated with three examples with 40 number of tasks and processors Cloud computing is the most popular technology to improve system performance with efficient task scheduling algorithm. To perform multiple goals in task scheduling it is an important way to arrange customer needs with an order. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the mean tardiness (lateness of due date) with utilizing maximum resources. Performance of algorithm evaluated with three examples with 120 number of tasks and processors.