Bandwidth-aware multi round task scheduling algorithm for cloud computing

Abstract

Task scheduling is an important component of parallel and distributed computing. Therefore, it is of theoretical significance and practical value to develop an effective task scheduling algorithm and implement it. For the task scheduling in cloud computing environment, it means that a group of tasks consisting a working load are distributed to a number of computational nodes as per certain implementing time sequence based on scheduling discipline and strategy to short the time needed by the whole task scheduling and to achieve good implementation performance. Divisible task scheduling is one of the important roles in the parallel computation and distributed computation. In this paper, we studies on a classical algorithm: Uniform Multi-Round (UMR), based on which an improved multi-path divisible task scheduling algorithm: MSUMR (Master Service Uniform Multi-Round) Algorithm is proposed. Such an algorithm could not only ensure the scheduling efficiency when the bandwidth is sufficient but also maximizes the computing efficiency of working node when the available bandwidth is limited. According to the experimental result, this algorithm, compared with such scheduling algorithms as UMR, MultiInstallment (MI) and eXtended Multi-Installment (XMI), is improved in the two aspects of dividing algorithm and task allocation principles, thus short down the number of unused computing nodes during task implementation and making full use of computing resources, indicating batter practical application value.