Authors : A.C. Kaladevi and M.V. Srinath
Abstract: Grid computing enables synchronization of shared distributed resources and supplement collaboration via virtual learning environment. Server management is essential in this research work with the intention of formulating consistent and harmonized use of ubiquitous and heterogeneous grids. Thus, reducing the server virtualization problems like receding the number of servers for too little research minimizing the high infrastructure requirements and the inadequate flexibility in shared environments. In this study an approach called Inclusive Bee Colony Optimization (IBCO) is developed for scheduling that gathers the learner’s requests initially. By estimating the intrinsic attributes of the grid nodes and task intrinsic rate, the observed node cost is acquired. Subsequently the random cost is evaluated following the hypothesis and finally applying the Chi-square distribution for ascertaining the fitness value. Scheduling prolongs according to the fitness function until the stopping criterion is met. Experimental results forecast that server can efficiently schedule the learners request on demand at sustaining moment. Moreover, this research perpetuates the possibility in reducing the cost constraint in time for scheduling the learner’s demands.
A.C. Kaladevi and M.V. Srinath, 2013. IBCO Based Task Scheduling for E-Learning Environments in Grid. International Journal of Soft Computing, 8: 63-71.