基于区块链框架的优化链路状态路由协议,实现移动 Ad-Hoc 网络的高效视频包传输和安全性

IF 3.3 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Huda A. Ahmed, H. Al-Asadi
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引用次数: 0

摘要

移动 ad-hoc 网络(MANET)需要适当的路由技术来实现最佳数据传输。要解决现有问题,必须在利用默认设置的同时选择合适的路由协议。为了在城域网中实现有效的视频流,本研究提出了一种新颖的优化链路状态路由(OLSR)协议,该协议结合了深度学习模型。首先,从 Kaggle 数据集中收集输入视频。然后,使用基于双注意的新型密集卷积双向门控网络(SA_ DCBiGNet)模型检测黑洞节点。接着,使用信任值分析邻近节点,并使用扩展的鱼鹰辅助优化链路状态路由协议(EO_OLSRP)技术执行路由选择。同样,扩展鱼鹰优化算法(EOOA)根据节点稳定性和链路稳定性等参数选择最优特征。最后,区块链存储利用星际文件系统(IPFS)技术提高了城域网数据的安全性。此外,提议的区块链系统还利用基于委托权益证明(DPoS)的共识技术进行了验证。所提议的方法使用 Python,并通过 NS3 模拟器从各种移动模拟器模型中获取的数据对其进行了评估。与 PDR 为 89.1%、AED 为 22 秒、吞吐量为 1780 字节的现有方法相比,拟议模型性能更佳,数据包交付率 (PDR) 为 91.6%,平均终端延迟 (AED) 为 23.6 秒,吞吐量为 2110 字节。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Optimized Link State Routing Protocol with a Blockchain Framework for Efficient Video-Packet Transmission and Security over Mobile Ad-Hoc Networks
A mobile ad-hoc network (MANET) necessitates appropriate routing techniques to enable optimal data transfer. The selection of appropriate routing protocols while utilizing the default settings is required to solve the existing problems. To enable effective video streaming in MANETs, this study proposes a novel optimized link state routing (OLSR) protocol that incorporates a deep-learning model. Initially, the input videos are collected from the Kaggle dataset. Then, the black-hole node is detected using a novel twin-attention-based dense convolutional bidirectional gated network (SA_ DCBiGNet) model. Next, the neighboring nodes are analyzed using trust values, and routing is performed using the extended osprey-aided optimized link state routing protocol (EO_OLSRP) technique. Similarly, the extended osprey optimization algorithm (EOOA) selects the optimal feature based on parameters such as node stability and link stability. Finally, blockchain storage is included to improve the security of MANET data using interplanetary file system (IPFS) technology. Additionally, the proposed blockchain system is validated utilizing a consensus technique based on delegated proof-of-stake (DPoS). The proposed method utilizes Python and it is evaluated using data acquired from various mobile simulator models accompanied by the NS3 simulator. The proposed model performs better with a packet-delivery ratio (PDR) of 91.6%, average end delay (AED) of 23.6 s, and throughput of 2110 bytes when compared with the existing methods which have a PDR of 89.1%, AED of 22 s, and throughput of 1780 bytes, respectively.
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来源期刊
Journal of Sensor and Actuator Networks
Journal of Sensor and Actuator Networks Physics and Astronomy-Instrumentation
CiteScore
7.90
自引率
2.90%
发文量
70
审稿时长
11 weeks
期刊介绍: Journal of Sensor and Actuator Networks (ISSN 2224-2708) is an international open access journal on the science and technology of sensor and actuator networks. It publishes regular research papers, reviews (including comprehensive reviews on complete sensor and actuator networks), and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
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