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BiRep:一种减轻延迟容忍型车联网中黑洞节点影响的声誉机制。

BiRep: A Reputation Scheme to Mitigate the Effects of Black-Hole Nodes in Delay-Tolerant Internet of Vehicles.

作者信息

Nabais Catarina, Pereira Paulo Rogério, Magaia Naercio

机构信息

INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, 1000-029 Lisboa, Portugal.

INESC-ID/INOV, Instituto Superior Técnico, Universidade de Lisboa, 1000-029 Lisboa, Portugal.

出版信息

Sensors (Basel). 2021 Jan 27;21(3):835. doi: 10.3390/s21030835.

DOI:10.3390/s21030835
PMID:33513736
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7866179/
Abstract

Delay-tolerant networking (DTN) enables communication in disruptive scenarios where issues such as sparse and intermittent connectivity, long and variable delays, high latency, high error rates, or no end-to-end connectivity exist. Internet of Vehicles (IoV) is a network of the future in which integration between devices, vehicles, and users will be unlimited and universal, overcoming the heterogeneity of systems, services, applications, and devices. Delay-tolerant internet of vehicles (DT-IoV) is emerging and becoming a popular research topic due to the critical applications that can be realized, such as software or map update dissemination. For an IoV to work efficiently, a degree of cooperation between nodes is necessary to deliver messages to their destinations. However, nodes might misbehave and silently drop messages, also known as a black-hole attack, degrading network performance. Various solutions have been proposed to deal with black-hole nodes, but most are centralized or require each node to meet every other node. This paper proposes a decentralized reputation scheme called BiRep that identifies and punishes black-hole nodes in DT-IoV. BiRep is tested on the Prophet routing protocol. Simulation results show excellent performance in all scenarios, comparable or better to other reputation schemes, significantly increasing the delivery ratio of messages.

摘要

容迟网络(DTN)能够在存在稀疏和间歇性连接、长且可变延迟、高延迟、高错误率或无端到端连接等问题的中断场景中实现通信。车联网(IoV)是未来的一种网络,其中设备、车辆和用户之间的集成将是无限和普遍的,克服了系统、服务、应用和设备的异构性。由于可以实现诸如软件或地图更新传播等关键应用,容迟车联网(DT-IoV)正在兴起并成为一个热门的研究课题。为了使车联网高效运行,节点之间需要一定程度的协作才能将消息传递到目的地。然而,节点可能会行为不当并悄悄丢弃消息,这也被称为黑洞攻击,会降低网络性能。已经提出了各种解决方案来处理黑洞节点,但大多数是集中式的,或者要求每个节点与其他每个节点相遇。本文提出了一种名为BiRep的去中心化声誉方案,用于识别和惩罚DT-IoV中的黑洞节点。BiRep在先知路由协议上进行了测试。仿真结果表明,在所有场景中BiRep都具有出色的性能,与其他声誉方案相当或更好,显著提高了消息的传递率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/d3f915b4f349/sensors-21-00835-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/dfb9abfeef22/sensors-21-00835-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/95fa49b6bb0a/sensors-21-00835-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/30a8ce8fd87a/sensors-21-00835-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/1fdd439ee756/sensors-21-00835-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/7371cd4e0e9d/sensors-21-00835-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/03c664db5607/sensors-21-00835-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/26f4decf2722/sensors-21-00835-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/6e097d927b60/sensors-21-00835-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/857557ea1de8/sensors-21-00835-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/23bee2dd9060/sensors-21-00835-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/ff45aef8b622/sensors-21-00835-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/ab9de4c9f2c3/sensors-21-00835-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/d3f915b4f349/sensors-21-00835-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/dfb9abfeef22/sensors-21-00835-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/95fa49b6bb0a/sensors-21-00835-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/30a8ce8fd87a/sensors-21-00835-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/1fdd439ee756/sensors-21-00835-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/7371cd4e0e9d/sensors-21-00835-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/03c664db5607/sensors-21-00835-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/26f4decf2722/sensors-21-00835-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/6e097d927b60/sensors-21-00835-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/857557ea1de8/sensors-21-00835-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/23bee2dd9060/sensors-21-00835-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/ff45aef8b622/sensors-21-00835-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/ab9de4c9f2c3/sensors-21-00835-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c3b/7866179/d3f915b4f349/sensors-21-00835-g013.jpg

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