Scheduling bag-of-tasks applications to optimize computation time and cost

Bag-of-tasks applications consist of independent tasks that can be performed in parallel. Although such problems are well known in classical scheduling theory, the distinctive feature of Grid and cloud applications is the importance of the cost factor: in addition to the traditional scheduling criterion of minimizing computation time, in Grids and clouds it also important to minimize the cost of using resources. We study the structural properties of the time/cost model and explore how the existing scheduling techniques can be extended to handle the additional cost criterion. Due to the dynamic nature of distributed systems, one of the major requirements to scheduling algorithms is related to their speed. The heuristics we propose are fast and, as we show in our experiments, they compare favourably with the existing scheduling algorithms for distributed systems.