Fuzzy logic based task allocation in ant colonies under grid computing

Extensive data analysis and a huge computational power is required in every computational grid application such as distributed supercomputing, high-throughput computing etc. Task Allocation strategy plays a vital role in the grid environment in terms of assigning the task to the appropriate ants of the colonies within a satisfactory allocation time. The uncertainty of available supply energy for completion of a task makes the allocation policy for grid computing more challenging. In this paper, we propose a fuzzy-based method for allocating the task among the members of an ant colony under grid computing and try to minimize the time consumption of task allocation. We believed and observed, our proposed model offers an improving performance comparable with traditional approach of allocating task in full assigning or no assigning. Our proposed method, based on the task and energy available from the grid and ants respectively, chooses the distribution of a task in full, half or no task assigning to ants by using fuzzy logic. During arriving of a task, ants will perform and execute the assigned task by using first in first out method. Successful task allocation, as reaching to equilibrium state will be achieved by allocating the task with half supply energy available from the colony. We show that with the use of fuzzy logic under grid environment task allocation problem shows an enhanced efficiency for assignment of tasks among the members of an ant colony.