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SPSI: A hybrid super-node election method based on information theory

机译:SPSI:基于信息论的混合超节点选举方法

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By exploiting heterogeneity, the super-node paradigm can lead to improved efficiency, without compromising the decentralized nature of peer-to-peer (P2P) networks. So many relevant applications such as grids, cloud computings use super-node paradigm as the lower service. However, due to inherent decentralisation, scale, dynamism, and complexity of P2P environments, self-managing super-node selection is a challenging problem. This paper present a super-node election protocol based on self-information theory (SPSI). In SPSI, every node has a information vector (VI), and SPSI uses a weighted mean mechanism based on VI to promote the “best” nodes to super-node status. We are the first (to the best of our knowledge) to use self-information theory to select super-node. The paper also includes extensive simulation experiments to prove the efficiency, scalability and robustness of SPSI.
机译:通过利用异构性,超节点范式可以提高效率,而不会损害对等(P2P)网络的分散性。因此,许多相关的应用程序(例如网格,云计算)使用超节点范式作为较低的服务。但是,由于固有的分散性,规模,动态性和P2P环境的复杂性,自管理超级节点选择是一个具有挑战性的问题。本文提出了一种基于自信息理论(SPSI)的超节点选举协议。在SPSI中,每个节点都有一个信息向量(VI),SPSI使用基于VI的加权均值机制将“最佳”节点提升为超节点状态。我们是第一个(据我们所知)使用自我信息论选择超级节点的人。本文还包括大量的仿真实验,以证明SPSI的效率,可扩展性和鲁棒性。

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