A video-on-demand video streaming task scheduling strategy based on Ant colony optimization algorithm in cloud environment

A video-on-demand video streaming task scheduling strategy based on Ant colony optimization algorithm in cloud environment

Wang Qingfeng Liu Zhiqin Huang Wang Yaobin

Aiming at the problem of low resource utilization and uneven load in large-scale concurrent video stream scheduling in cloud environment, a video VOD (VOD) cluster video streaming task scheduling strategy Vodaco based on Ant colony Optimization (ACO) algorithm is proposed. Based on the analysis of the correlation between the expected performance of the video stream and the idle performance of the server, and the definition of the comprehensive capability matching, the mathematic model is established, and the optimal scheduling scheme is searched by Ant Colony optimization method. The experiment of cloud simulation software shows that compared with polling (RR) and greedy (greedy) algorithm, the proposed algorithm has obvious advantages in task completion time, platform resource share and performance load balance index of each node Cloudsim.

A video-on-demand video streaming task scheduling strategy based on Ant colony optimization algorithm in cloud environment