A Pollination Based Optimization for Load Balancing Task Scheduling in Cloud Computing
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Abstract
Load Balancing in Task Scheduling is a process of managing different tasks on the basis of their priority or job execution order. Jobs have to be acquired on different processors and load needs to be maintained for the execution. Task scheduling is considered to be one of the critical issues on the cloud environment as various users requests to access the data on the cloud environment. The jobs have to be allocated to the processors in such a manner so as to minimize the makespan and computation time. To achieve this objective various optimization techniques have been proposed which includes Genetic Algorithm in which initially dependency between the tasks are removed which are further executed using shortest job first and makespan is created. A new approach Pollination Based Optimization (PBO) is used to optimize the results of GA(Genetic Algorithm).The performance of these two techniques are then compared that will prove the effectiveness of the optimization methods.
Index Terms: Cloud Computing, Task Scheduling, Load Balancing, Genetic Algorithm, Pollination Based Optimization
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