NDN-based IoT with Edge computing

Wang, Xiaonan; Wang, Xingwei; Li, Yanli

doi:10.1016/j.future.2020.09.018

Cited by 22 publications

(8 citation statements)

References 21 publications

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“…Considering the application with limited resources, the energysaving part of wireless resources and computing resources is jointly optimized to calculate the shunting method, through wireless energy transmission [11]. Wang et al proposed a joint optimization scheme of the edge computing system based on full-duplex relay wireless power supply and proposed a joint optimization method of energy consumption and delay based on fog computing [12]. Yang et al put forward a strategy called PRIMAL, which selectively migrates computing tasks to their best location, considers the benefits and costs of migrating users' tasks to the appropriate mobile edge cloud according to their location, and optimizes the tradeoff between migration benefits and migration costs.…”

Section: Related Workmentioning

confidence: 99%

Certificateless Batch Authentication Scheme and Intrusion Detection Model Based on the Mobile Edge Computing Technology NDN-IoT Environment

Sun

2022

Journal of Function Spaces

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With the rapid development of mobile communication technology, the data transmission rate of mobile communication has been significantly improved and emerging Internet of things applications need a lot of computing resources to meet their own computing needs. However, the existing intelligent terminals have limited computing power and cannot meet the low-latency computing requirements with limited energy consumption. Mobile edge computing technology is considered to be one of the technical solutions that can efficiently solve this problem. Through mobile edge computing technology, intelligent terminals can actively divert some computing tasks to the computing servers deployed in edge network nodes and return the computing results to intelligent terminals after the edge computing servers have finished computing, thus greatly reducing the computing delay of users. In this paper, aiming at multiple edge server networks, combined with dual-connection technology, based on the research of a single edge computing server network, it is further extended to two edge computing servers and a joint optimization problem of computing task allocation and security performance requirements of intelligent terminals and edge computing servers is proposed, so as to minimize the global time delay for completing the computing tasks of intelligent terminals. By layering the problem, this paper proposes a corresponding algorithm, which can efficiently obtain the optimal solution of the initial problem. Compared with the linear search algorithm, the algorithm proposed in this paper can significantly reduce the computation time.

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Section: Related Workmentioning

confidence: 99%

Certificateless Batch Authentication Scheme and Intrusion Detection Model Based on the Mobile Edge Computing Technology NDN-IoT Environment

Sun

2022

Journal of Function Spaces

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“…In this line, edge computing may also help in networking tasks such as introducing novel data communication paradigms, e.g. Named Data Networking (NDN) (Wang et al, 2021), helping to select the most adequate settings for end-device transmissions (Sanchez-Iborra et al, 2018), or supporting IoT data security (Alaba et al, 2017).…”

Section: Edge Computing For Iotmentioning

confidence: 99%

Intelligent and Efficient IoT Through the Cooperation of TinyML and Edge Computing

Sánchez-Iborra¹,

Zoubir²,

Hamdouchi³

et al. 2023

Informatica

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The coordinated integration of heterogeneous TinyML-enabled elements in highly distributed Internet of Things (IoT) environments paves the way for the development of truly intelligent and context-aware applications. In this work, we propose a hierarchical ensemble TinyML scheme that permits system-wide decisions by considering the individual decisions made by the IoT elements deployed in a certain scenario. A two-layered TinyML-based edge computing solution has been implemented and evaluated in a real smart-agriculture use case, permitting to save wireless transmissions, reduce energy consumption and response times, at the same time strengthening data privacy and security.

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“…In order to solve the problem of IoT data interaction efficiency, Zhang proposed building an IoT integration framework by utilizing the easy-to-use and efficient content delivery features of NDN, which realized a good interaction between IoT communication programs and services [2]. Due to resource constraints of IoT devices, Wang introduced mobile edge devices to help implement request aggregation and network caching in NDN, reducing the difficulty of direct deployment and effectively reducing data communication delay and cost [3]. However, the above research did not take the built-in security into consideration, because although NDN far surpasses the TCP/IP architecture in terms of efficiency, it does not have channel security, which brings great trust issues to IoT data sharing.…”

Section: Related Workmentioning

confidence: 99%

A Trusted IoT Communication Architecture Based on Blockchain and Named Data Network

Sun

Chen

Fang

et al. 2022

J. Phys.: Conf. Ser.

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The trusted cross-domain sharing capability of the Internet of Things (IoT) terminals needs to be improved urgently. Aiming at the technical issues of routing overhead and authentication security of data sharing of IoT devices, this paper proposes a trusted transmission architecture for network-chain collaboration. Introduce the mobile edge computing (MEC) platform in named data network (NDN) to deploy blockchain light nodes and improve the PBFT consensus algorithm. Besides, a cross-domain authentication algorithm based on elliptic curve encryption is proposed. Simulation results show that the improved PBFT and cross-domain authentication algorithm can effectively improve IoT cross-domain sharing capabilities.

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NDN-based IoT with Edge computing

Cited by 22 publications

References 21 publications

Certificateless Batch Authentication Scheme and Intrusion Detection Model Based on the Mobile Edge Computing Technology NDN-IoT Environment

Certificateless Batch Authentication Scheme and Intrusion Detection Model Based on the Mobile Edge Computing Technology NDN-IoT Environment

Intelligent and Efficient IoT Through the Cooperation of TinyML and Edge Computing

A Trusted IoT Communication Architecture Based on Blockchain and Named Data Network

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