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A novel solution for the P2P network observer placement problem on DNA-based supercomputing

机译:基于DNA的超级计算中P2P网络观察者放置问题的新解决方案

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Since the “free-riding” behavior objectively exists in a P2P network, how to precisely determine the “free-riders” in the network is now a key problem. Passive testing method has been the best way of finding the potential faults on the real network at present. The observer placement problem is one of the critical problems that have been played much attention on. The problem has been also proved to be a NP-complete problem. In this paper, a new DNA computing algorithm for the observer placement problem is produced. On the basis of the sticker-based model''s solution space and the Adleman-Lipton model''s biological operations, the algorithm consists of a pre-treatment algorithm, a vertex composer, a solution space generator, a parallel searcher and an observer placement searcher. Furthermore, we introduced greedy strategy into our new algorithm for reducing the solution space. In an experimental simulation, the algorithm is proved to have better storage utilization and fault tolerant ability.
机译:由于P2P网络中客观存在“搭便车”行为,因此,如何在网络中精确确定“搭便车”是一个关键问题。目前,无源测试方法一直是发现实际网络中潜在故障的最佳方法。观察者放置问题是倍受关注的关键问题之一。该问题也被证明是NP完全问题。本文提出了一种用于观察者放置问题的新的DNA计算算法。在基于贴纸的模型的解空间和Adleman-Lipton模型的生物运算的基础上,该算法包括一个预处理算法,一个顶点组合器,一个解空间生成器,一个并行搜索器和一个观察者位置搜索者。此外,我们在新算法中引入了贪婪策略,以减少求解空间。在实验仿真中,证明该算法具有更好的存储利用率和容错能力。

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