S-Kcore:口袋交换网络中社会感知的Kcore分解算法

Ming Li, Longxiang Gao, Wanlei Zhou
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引用次数: 3

摘要

网络中的关键节点对系统的恢复和生存起着至关重要的作用。许多传统的关键节点选择算法都是利用物理拓扑的特性来寻找关键节点。但由于移动自组网的移动性,它们很难在移动自组网中取得成功。在本文中,我们提出了一种社会感知的Kcore选择算法来工作在口袋交换网络。网络的社会观表明,移动节点的社会位置有助于发现口袋交换网络中的关键节点。S-Kcore选择算法旨在利用节点的社交特性来提高数据通信性能。使用NS2进行的实验表明,S-Kcore选择算法在口袋交换网络中是可行的。此外,有了社会行为信息,这些关键节点更适合表示和提高整个网络的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
S-Kcore: A Social-aware Kcore Decomposition Algorithm in Pocket Switched Networks
The key nodes in network play the critical role in system recovery and survival. Many traditional key nodes selection algorithms utilize the characters of the physical topology to find the key nodes. But they can hardly succeed in the mobile ad hoc network due to the mobility nature of the network. In this paper we propose a social-aware Kcore selection algorithm to work in the Pocket Switched Network. The social view of the network suggests the social position of the mobile nodes can help to find the key nodes in the Pocket Switched Network. The S-Kcore selection algorithm is designed to exploit the nodes' social features to improve the performance in data communication. Experiments use the NS2 shows S-Kcore selection algorithm workable in the Pocket Switched Network. Furthermore, with the social behavior information, those key nodes are more suitable to represent and improve the whole network's performance.
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