本文選題：混合算法 + 云計算��； 參考：《現(xiàn)代電子技術(shù)》2016年12期

【摘要】：目前針對任務(wù)調(diào)度方法的研究中,為了降低研究難度,通常只針對某一個考量任務(wù)調(diào)度方法好壞的尺度進行研究,經(jīng)常會出現(xiàn)優(yōu)化后的方法以較高的計算成本為代價換來較短的任務(wù)完成時間,有時是得不償失的。因此該文將任務(wù)完成時間和計算成本均作為優(yōu)化的目標,對任務(wù)調(diào)度方法進行研究,平衡任務(wù)完成時間和計算成本,提高云計算的效率。該文使用遺傳優(yōu)化算法對上述提出的任務(wù)調(diào)度問題進行求解,并將模擬退火算法、自適應(yīng)機理相結(jié)合,建立更加適合云計算任務(wù)調(diào)度求解的混合優(yōu)化算法。最后,通過實驗分析,以僅對任務(wù)完成時間優(yōu)化和僅對計算成本優(yōu)化的算法進行比較,該文研究的混合算法的云計算任務(wù)調(diào)度方法能夠有效平衡任務(wù)完成時間和計算成本,有效提高云計算的效率,降低其計算成本。
[Abstract]:In the research of task scheduling methods, in order to reduce the difficulty of the research, only a certain scale of task scheduling methods is usually studied. It is common for the optimized methods to gain shorter task completion time at the cost of higher computation cost, sometimes the gain is outweighed by the loss. Therefore, the task completion time and computing cost are taken as the goal of optimization in this paper. The task scheduling method is studied to balance the task completion time and computing cost to improve the efficiency of cloud computing. In this paper, genetic optimization algorithm is used to solve the task scheduling problem mentioned above, and the simulated annealing algorithm and adaptive mechanism are combined to establish a hybrid optimization algorithm which is more suitable for the task scheduling of cloud computing. Finally, through the experimental analysis, comparing the algorithms of task completion time optimization and computation cost optimization, the hybrid algorithm of cloud computing task scheduling can effectively balance the task completion time and computing cost. Effectively improve the efficiency of cloud computing, reduce its computing costs.
【作者單位】： 阿壩師范學(xué)院;
【基金】：四川省教育廳自然科學(xué)重點課題:高校數(shù)據(jù)中心建設(shè)與研究(13ZA0038);四川省教育廳自然科學(xué)重點課題:Open Flow在校園網(wǎng)的應(yīng)用方案研究(15ZA0338)
【分類號】：TP18;TP3

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本文編號：1813706