Efficient Scheduling of tasks in Cloud
Sunitha Guruprasad, Deeshma Shetty
Abstract
Sunitha Guruprasad, Deeshma Shetty
Abstract
Wireless Cloud Infrastructure provides a pay-for-use basis data and infrastructure services over the internet. This enables the user to upgrade the software automatically. Only the space required for the server can be used, thus minimizing the carbon footprint. The main problem with cloud computing is task scheduling which reduces system performance. An efficient task-scheduling algorithm is required to improve the performance of the system. Existing task-scheduling algorithms concentrate on memory of the CPU, resource requirements of the task, run time and cost of execution. Bandwidth of the network is not considered in most of the researches. In this paper, an efficient algorithm for task scheduling has been introduced that performs scheduling of the tasks based on network bandwidth. By doing this, the tasks can be allocated based on the availability of the bandwidth of the network. In addition, the algorithm assigns the right number of tasks to each virtual machine. The results shows that the execution time is reduced to a greater extent when the bandwidth factor is included in the algorithm.
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Wireless Cloud Infrastructure provides a pay-for-use basis data and infrastructure services over the internet. This enables the user to upgrade the software automatically. Only the space required for the server can be used, thus minimizing the carbon footprint. The main problem with cloud computing is task scheduling which reduces system performance. An efficient task-scheduling algorithm is required to improve the performance of the system. Existing task-scheduling algorithms concentrate on memory of the CPU, resource requirements of the task, run time and cost of execution. Bandwidth of the network is not considered in most of the researches. In this paper, an efficient algorithm for task scheduling has been introduced that performs scheduling of the tasks based on network bandwidth. By doing this, the tasks can be allocated based on the availability of the bandwidth of the network. In addition, the algorithm assigns the right number of tasks to each virtual machine. The results shows that the execution time is reduced to a greater extent when the bandwidth factor is included in the algorithm.
Key concepts: Computer science, Distributed computing, Cloud computing, Scheduling (production processes), Fair-share scheduling, Dynamic priority scheduling, Two-level scheduling, Fixed-priority pre-emptive scheduling