A COST EFFICIENT TWO-LEVEL MARKET MODEL FOR TASK SCHEDULING PROBLEM IN GRID ENVIRONMENT

This paper investigates the scheduling problem of independent tasks in market-basedgrids . The heterogeneity and autonomy of resources in grids highlight the need for more flexiblemodels and approaches to be exploited in these environments. To address this issue, a two-levelmarket model is presented in this paper to schedule tasks to the grid resources. In the proposedmodel , users submit their own tasks to a centralized resource manager named meta-scheduler .Meta-scheduler knows general information about each of the administrative domains , called sites ,existing in the low-level part of the model. Using the information gathered from all of the sites ,meta-scheduler selects more suitable sites to execute the tasks with the aim of minimizing theoverall cost of tasks execution . In this model, meta-scheduler not only targets the minimization ofoverall cost of the tasks execution, but also achieves this objective without any presumption aboutthe policies and algorithms implemented in the lower layers of the system which addresses thedynamicity of environment. In addition to the two-level market model , a new task schedulingalgorithm called GA-VNS which is an enhanced version of genetic algorithm is presented to beapplied in market-based grids. GA-VNS can be used by local schedulers in each site with thepolicy of cost minimization considering the makespan of the system as a second criterion. Theresults obtained from performance evaluation of GA-VNS and other well-known algorithms in thiscontext show that GA-VNS outperforms other algorithms in terms of the overall cost of tasksexecution .