An NDN IoT Content Distribution Model With Network Coding Enhanced Forwarding Strategy for 5G
Abstract
The challenging requirements of fifth-generation (5G) Internet-of-Things (IoT) applications have motivated a desired need for feasible network architecture, while Named Data Networking (NDN) is a suitable candidate to support the high density IoT applications. To effectively distribute increasingly large volumes of data in large-scale IoT applications, this paper applies network coding techniques into NDN to improve IoT network throughput and efficiency of content delivery for 5G. A probability-based multipath forwarding strategy is designed for network coding to make full use of its potential. To quantify performance benefits of applying network coding in 5G NDN, this paper integrates network coding into a NDN streaming media system implemented in the ndnSIM simulator. The experimental results clearly and fairly demonstrate that considering network coding in 5G NDN can significantly improve the performance, reliability, and QoS. Besides, this is a general solution as it is applicable for most cache approaches. More importantly, our approach has promising potentials in delivering growing IoT applications including high-quality streaming video services.
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The new named data network (NDN) has been proposed to support high density applications in 5G-IoT environment, in which network virtualisation technologies, e.g., NFV, will be utilized to manage increasingly fragmented networks.
“The new named data network (NDN) has been proposed to support the high density applications in 5G-IoT environment (Lei et al., 2018), in which network virtualisation technologies, e.g., NFV will be utilized to manage the increasingly fragmented networks (Aijaz & Sooriyabandara, 2018;Li et al., 2018).”
From Future Industry Internet of Things with Zero-trust Security (2024) · cites this paper as Lei et al., 2018
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Future Industry Internet of Things with Zero-trust Security
Li, S., Iqbal, M., & Saxena, N. (2024) · Information Systems Frontiers · doi:10.1007/s10796-021-10199-5 · Cited by 128 · see citing works
- Authors
- Lei, K., Zhong, S., Zhu, F., Xu, K., & Zhang, H.
- Affiliations
- Peking University (CN)
- Arizona State University (US)
- University of Science and Technology Beijing (CN)
- Venue
- IEEE Transactions on Industrial Informatics
- Published
- 2018-06
- Volume
- 14
- Issue
- 6
- Pages
- 2725-2735
- ISSN
- 1551-3203 (ISSN-L)
- 1941-0050
- OpenAlex
- W2772422095
- Cited by
- 69
- References
- 22
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 4 · 2023: 10 · 2022: 7 · 2021: 7 · 2020: 12 · 2019: 13 · 2018: 10
- FWCI
- 6.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Industrial Informatics (publishedVersion)
- Funders
- National Natural Science Foundation of China (61471025, 61771044)
- Young Elite Scientist Sponsorship Program by CAST (2016QNRC001)
- Research Foundation of Ministry of Education of China & China Mobile (MCM2018-1-8)
- Beijing Municipal Natural Science Foundation (L172025)
- Fundamental Research Funds for the Central Universities (FRF-GF-17-A6)
- Shenzhen Key Fundamental Research Projects (JCYJ20160330095313861, JCYJ20170412151008290)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Caching and Content Delivery
- Physical Sciences › Computer Science › Computer Networks and Communications › Peer-to-Peer Network Technologies
- Physical Sciences › Computer Science › Computer Networks and Communications › Opportunistic and Delay-Tolerant Networks
- Keywords
- Named Data Networking, Internet of Things, network coding, content distribution, 5G, multipath forwarding, streaming media, network throughput, quality of service, ndnSIM
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