FRDV: A DTN Routing Based on Human Moving Status in Urban Environments

Li, Wenzao, Wan, Bing, Wen, Zhan, Liu, Jianwei, Cao, Yue, Wu, Tao and Zhou, Jiliu (2018) FRDV: A DTN Routing Based on Human Moving Status in Urban Environments. In: ICCCS 2018 - 4th International Conference on Cloud Computing and Security, 8th - 10th June 2018, Haikou, China.

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It is a fast and simple way to run a Delay Tolerant Network (DTN) by mobile terminals in an urban environment, therefore DTN currently plays an important role as a network for Internet of Things (IoT). The network metrics are important for performance of DTN based communication systems. Because moving characteristics in urban environments are different from other challenging network environments, then the routing method is also different in various environments. In general, routing algorithm decides the DTN performance, so it cannot release potential performance with traditional routing algorithms in cities. In this paper, we propose a routing algorithm for urban areas, named Forward Routing based Distance Variation (FRDV), and we designed such approach according to human moving characteristics. FRDV comprises two stages which include selecting relay node and messages transmission decision. At the first stage, FRDV select a relay node depend on sending activity which depends on delivery frequency of nodes. During the short encounter time, the nodes selectively sent messages to the relay node based on moving status of nodes at the second stage. The simulation results suggest that FRDV outperforms than classical algorithms such as Epidemic, Prophet, Direct Delivery and First Contact algorithms in urban environments.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Delay tolerant network, Internet of Things, Performance, Routing algorithm, Urban environments
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 23 Oct 2019 13:32
Last Modified: 23 Oct 2019 13:32

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