1A Deadline and Budget Constrained Cost -Time Optimisation

Title: 1A Deadline and Budget Constrained Cost -Time Optimisation

Abstract: This research aimed to develop a new scheduling algorithm for task farming applications on global grids. The algorithm, called DBC cost-time optimisation, extends the existing DBC cost-optimisation algorithm to optimise for time while keeping the cost of computation at a minimum. The algorithm's effectiveness was demonstrated through simulations using the World -Wide Grid and various deadline and budget scenarios.

Research Question: How can we develop an efficient scheduling algorithm for task farming applications on global grids that optimises for time while keeping the cost of computation minimal?

Methodology: The study used a computational economy framework for regulating the supply and demand for resources and allocating them to applications based on users' quality of service requirements. The research team developed a new scheduling algorithm, called DBC cost-time optimisation, to optimise for time and cost. The algorithm was simulated on the World -Wide Grid with different deadline and budget scenarios to evaluate its performance.

Results: The simulations demonstrated that the DBC cost-time optimisation algorithm achieved lower job completion times compared to the existing DBC cost-optimisation algorithm. This result suggests that the new algorithm is more effective in meeting users' quality of service requirements while keeping the cost of computation at a minimum.

Implications: The DBC cost-time optimisation algorithm can significantly improve the efficiency of task farming applications on global grids. By optimising for time and cost, the algorithm can help users meet their quality of service requirements more effectively, making global grid computing more accessible and useful for a wide range of applications.

Link to Article: https://arxiv.org/abs/0203020v1 Authors: arXiv ID: 0203020v1