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

机译:一种基于模糊推理路由算法的人类联系网络的传送方案

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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:人类联系网络是一种DTN(延迟宽容网络),与人们的活动密切相关。 由于其间歇性连接和独特的人类移动模式,如何以有效的方式传输数据是DTN的具有挑战性问题。 在本文中,考虑到人们活动的规律性,我们提出了一种攻击(旅行历史模型)来记录人们的活动。 通过存储在THM中的人的空间和时间特征,可以预测进一步的移动目的地。 为了传输数据更合理,已经提出了模糊推断路由算法,这将模糊推断引入路由方案中,以帮助选择更好的传感器节点。 我们的仿真结果表明,与标签和先知算法相比,FiRA有效提高了网络的路由性能。

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