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A delivery scheme based on fuzzy inference Routing algorithm for Human Contact Networks

机译:基于模糊推理路由算法的人接触网交付方案

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Human Contact Network is a kind of DTN (Delay Tolerant Networks), and is closely related with people' activities. Owing to its intermittent connectivity and unique human mobility patterns, how to transmit data in an effective way is a challenging problem for DTN. In this paper, considering the regularity of people activities, we propose a THM (Trip History Model) to record the activities of people. Through the spatial and temporal characteristic of people stored in THM, the further moving destination can be predicted. In order to transfer data more reasonable, Fuzzy inference Routing algorithm has been proposed, which introduce fuzzy inference into routing scheme to help select a better sensor node. Our simulation results show that, compared with LABEL and PROPHET algorithms, FIRA effectively improves the routing performance of the network.
机译:人际联系网络是一种DTN(时延容忍网络),与人们的活动密切相关。由于其间歇性的连接性和独特的人类移动性模式,如何以有效的方式传输数据对于DTN而言是一个充满挑战的问题。在本文中,考虑到人的活动的规律性,我们提出了THM(旅行历史模型)来记录人的活动。通过THM中存储的人员的时空特征,可以预测进一步的移动目的地。为了更合理地传输数据,提出了模糊推理路由算法,将模糊推理引入路由方案,以帮助选择更好的传感器节点。仿真结果表明,与LABEL和PROPHET算法相比,FIRA有效地提高了网络的路由性能。

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