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P2P计算具有一些良好的特质,但是由于资源分布的任意性、互联网较大的延时、较低的有效带宽以及较高的数据传输代价,实际中目前的P2P计算效率受到了很大限制。对此问题以前的研究工作主要集中于在现行的P2P计算模型下,对一些机制进行改进。与这些先前工作不同,该研究提出了一个新的模型,它对P2P计算进行优化的组织,即将一些合适的P2P计算实例调度到适合的云计算节点上,并且以最优的方式来为其调度所需资源。更重要地,该文对优化组织过程进行了详细的数学分析和深入的理论建模,并同时对性能和代价进行了考虑。由于问题的解空间将随着问题规模的增长以指数速度扩张,因此提出了基于生物免疫思想的智能计算方法。实验验证了该算法的有效性和效率;并且与现行P2P计算模式进行对比实验的结果表明:该模型和方法为不同类型的P2P计算任务节省了运行时间和实际代价。
P2P computing has some good characteristics. However, due to the randomness of resource distribution, larger delay of the Internet, lower effective bandwidth and higher data transmission cost, the current P2P computing efficiency has been greatly restricted. Previous research on this issue has focused on improving some mechanisms under the current P2P computing model. Different from these previous works, the research proposed a new model, which optimizes the P2P computing organizations, that is, some suitable P2P computing instances are scheduled on the suitable cloud computing nodes and the best way to schedule them Resources required. More importantly, the article gives a detailed mathematical analysis and in-depth theoretical modeling of the process of optimizing the organization, taking into account both performance and cost. Since the solution space of the problem will expand exponentially with the increase of the scale of the problem, an intelligent calculation method based on the biological immunity theory is proposed. Experimental results show the effectiveness and efficiency of the proposed algorithm. Compared with the existing P2P computing model, the experimental results show that the proposed model and method can save time and money for different types of P2P computing tasks.