TY  - JOUR
T1  - IBCO Based Task Scheduling for E-Learning Environments in Grid
AU - Kaladevi, A.C. AU - Srinath, M.V. 
JO  - International Journal of Soft Computing
VL  - 8
IS  - 1
SP  - 63
EP  - 71
PY  - 2013
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2013.63.71
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2013.63.71
KW  - Swarm intelligence
KW  -scheduling
KW  -Chi-square distribution
KW  -ACO
KW  -BCO
KW  -poisson distribution
AB  - 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.
ER  -