摘要： 針對當前流媒體的大量視頻資源從而帶來的云計算的負載均衡和任務分配問題,，在Cloudsim云環(huán)境下實現(xiàn)了任務調度的GAAC算法(Greedy And Ant Colony Algorithm，GAAC),。GAAC算法具有迭代學習機制,、局部最優(yōu)和負載均衡的特點。并在Cloudsim的環(huán)境下,，完成了對GAAC算法,、輪轉算法(Round Roll Algorithm，RR),、貪心算法和蟻群算法的仿真比較,。實驗驗證，GAAC算法從總體上而言,，任務調度所用的時間明顯較低于貪心算法和傳統(tǒng)的輪轉算法和蟻群算法,，即其任務執(zhí)行的時間更短，效率更高,。
中圖分類號： TN949.2 文獻標識碼： A DOI：10.16157/j.issn.0258-7998.200770 中文引用格式： 楊戈,，吳俊言. 基于云計算的流媒體任務調度算法[J].電子技術應用，2021,，47(8)：97-100,，105. 英文引用格式： Yang Ge，Wu Junyan. Task scheduling algorithm based on cloud computing for streaming media[J]. Application of Electronic Technique,，2021,，47(8)：97-100，105.
Task scheduling algorithm based on cloud computing for streaming media
Yang Ge1,，2,，Wu Junyan1
1.Key Laboratory of Intelligent Multimedia Technology，Beijing Normal University(Zhuhai Campus),，Zhuhai 519087,，China,； 2.Engineering Lab on Intelligent Perception for Internet of Things(ELIP)，Shenzhen Graduate School,， Peking University,，Shenzhen 518055，China
Abstract： Aiming at the problem of cloud computing load balancing and task allocation brought about by a large number of video resources in the current streaming media, the task scheduling GAAC algorithm(Greedy And Ant Colony Algorithm,，GAAC) is implemented in the Cloudsim cloud environment. GAAC algorithm has the characteristics of iterative learning mechanism, local optimization and load balancing. In the context of cloudsim, simulations of GAAC algorithm, Round Roll Algorithm(RR), greedy algorithm and ant colony algorithm were completed. The experimental verification shows that GAAC algorithm is generally lower in the time spent on task scheduling than greedy algorithm, traditional rotation algorithm and ant colony algorithm.
Key words : Cloud computing,；task scheduling；Greedy algorithm
