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  本文選題：云計算 + 虛擬機��； 參考：《計算機測量與控制》2014年05期

【摘要】：針對云計算環(huán)境下大量并行任務運行所導致的某些節(jié)點負載過重,從而引起整個系統(tǒng)負載不均和效率低下的問題,提出了一種基于并行計算熵的資源負載均衡算法;首先,描述了云計算虛擬機部署原理并給出了適合云計算環(huán)境和異構(gòu)集群的并行計算熵的計算方式,然后,定義了在系統(tǒng)并行計算熵低于閾值時遷移的源物理節(jié)點、遷移虛擬機和遷移目標物理節(jié)點的確定方式;最后,定義了基于并行計算熵的負載均衡算法;采用CloudSim云計算仿真工具對文中方法進行仿真實驗,結(jié)果表明文中方法較其它方法的平均負載均衡度約低21.8%,具有較低的任務平均響應時間、合理的資源利用率和較小的負載均衡度,具有較大的優(yōu)越性。
[Abstract]:A resource load balancing algorithm based on parallel computing entropy is proposed to solve the problem that some nodes are overloaded due to the running of a large number of parallel tasks in cloud computing environment, which leads to the uneven load and low efficiency of the whole system. Firstly, a parallel computing entropy based resource load balancing algorithm is proposed. This paper describes the deployment principle of cloud computing virtual machine and gives the computing method of parallel computing entropy suitable for cloud computing environment and heterogeneous cluster. Then, the source physical node is defined when the parallel computing entropy of the system is lower than the threshold. Finally, the load balancing algorithm based on parallel computing entropy is defined, and the method is simulated by CloudSim cloud computing simulation tool. The results show that the average load balancing degree of the proposed method is about 21.8 lower than that of the other methods, and the average task response time is lower, the reasonable resource utilization ratio and the load balancing degree are smaller, and the method has more advantages.
【作者單位】： 常州信息職業(yè)技術學院;
【分類號】：TP393.01

【參考文獻】

相關期刊論文 前5條

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本文編號：2003947