Bandwidth‐aware divisible task scheduling for cloud computing

Abstract

SUMMARYTask scheduling is a fundamental issue in achieving high efficiency in cloud computing. However, it is a big challenge for efficient scheduling algorithm design and implementation (as general scheduling problem is NP-complete). Most existing task-scheduling methods of cloud computing only consider task resource requirements for CPU and memory, without considering bandwidth requirements. In order to obtain better performance, in this paper, we propose a bandwidth-aware algorithm for divisible task scheduling in cloudcomputing environments. A nonlinear programming model for the divisible task-scheduling problem under the bounded multi-port model is presented. By solving this model, the optimized allocation scheme that determines proper number of tasks assigned to each virtual resource node is obtained. On the basis of the optimized allocation scheme, a heuristic algorithm for divisible load scheduling, called bandwidth-aware task-scheduling (BATS) algorithm, is proposed. The performance of algorithm is evaluated using CloudSim toolkit. Experimental result shows that, compared with the fair-based task-scheduling algorithm, the bandwidthonly task-scheduling algorithm, and the computation-only task-scheduling algorithm, the proposed algorithm (BATS) has better performance.

Task scheduling and resource allocation in cloud computing using a heuristic approach

“…6 the Cybershake tasks are shown on the X axix, whereas time shown on the Y axis. When we compare our proposed heuristic approach with the existing BATS [7] and IDEA [4] frameworks, we find that our approach displays reduced turnaround time. Fig.…”

“…This methodology does not show the proper utilization of resources. Lin et al [7] proposed the scheduling of tasks while considering bandwidth as a resource. A nonlinear programming model has been formed to allocate resources to tasks.…”

“…Here, we improve upon the BATS algorithm, which was originally proposed by Weiwei Lin [7]. Independent tasks of equal size are considered in the design of this system.…”

The scheduler for the grid­system based on the parameters monitoring of the computer components

“…The resource management mechanisms, based on this approach are becoming more common. So, in [3] task scheduling in Cloud considering the channel capacity has been presented. In [4] heuristic task scheduling algorithms in Grid considering network communication have been provided.…”

Intelligence VM Allocation and Selection Policy based on Local Linear Regression (LR)

“…al. [34] has proposed the imbalanced metrics for the optimization of the task clustering on the scientific workflow data executions. The authors have examined the imbalanced nature of the task clustering during the runtime evaluation for the purpose of task clustering in depth.…”