Singh Jagdeep, Dhurandher Sanjay Kumar, Woungang Isaac, Chao Han-Chieh
Sant Longowal Institute of Engineering and Technology, Longowal 148106, India.
Department of Information Technology, Netaji Subhas University of Technology, New Delhi 110078, India.
Sensors (Basel). 2024 Nov 29;24(23):7650. doi: 10.3390/s24237650.
In opportunistic IoT (OppIoT) networks, non-cooperative nodes present a significant challenge to the data forwarding process, leading to increased packet loss and communication delays. This paper proposes a novel Context-Aware Trust and Reputation Routing (CATR) protocol for opportunistic IoT networks, which leverages the probability density function of the beta distribution and some contextual factors, to dynamically compute the trust and reputation values of nodes, leading to efficient data dissemination, where malicious nodes are effectively identified and bypassed during that process. Simulation experiments using the ONE simulator show that CATR is superior to the Epidemic protocol, the so-called beta-based trust and reputation evaluation system (denoted BTRES), and the secure and privacy-preserving structure in opportunistic networks (denoted PPHB+), achieving an improvement of 22%, 15%, and 9% in terms of average latency, number of messages dropped, and average hop count, respectively, under varying number of nodes, buffer size, time to live, and message generation interval.
在机会物联网（OppIoT）网络中，非合作节点给数据转发过程带来了重大挑战，导致数据包丢失增加和通信延迟。本文提出了一种用于机会物联网网络的新型上下文感知信任与声誉路由（CATR）协议，该协议利用贝塔分布的概率密度函数和一些上下文因素，动态计算节点的信任和声誉值，从而实现高效的数据传播，在此过程中能有效识别并绕过恶意节点。使用ONE模拟器进行的仿真实验表明，CATR优于流行病协议、所谓的基于贝塔的信任和声誉评估系统（简称BTRES）以及机会网络中的安全与隐私保护结构（简称PPHB+），在节点数量、缓冲区大小、生存时间和消息生成间隔不同的情况下，平均延迟、丢弃消息数量和平均跳数分别提高了22%、15%和9%。
