Abstract
Named data networking (NDN) is a promising future network architecture in 5G edge computing scenarios because it supports multicast, mobility, in-network caching, and security. The key problem of service invocation in edge computing is how to dynamically select the appropriate edge CNs for the computing requester according to the edge CNs and network status. NDN mainly solves this problem by forwarding strategy. NDN uses a forwarding strategy to reasonably select the forwarding path, which can achieve load balancing, congestion control, low latency, and high throughput. However, scenarios have various characteristics and application requirements, and a forwarding strategy should adapt to them. In this study, we define the forwarding path selection as a multiple attribute decision-making (MADM) problem. We propose the coefficient of variation-based probabilistic forwarding (CVPF) strategy. We compare CVPF to our previous work, the entropy-based probabilistic forwarding (EPF) and probabilistic forwarding based maximizing deviation method (MDPF) strategies, and determine the characteristics of these three forwarding strategies. Experiments were conducted in different scenarios to compare them. We find that EPF, MDPF, and CVPF have different preferences depending on traffic conditions. The results show that EPF is the most sensitive method and is suitable for large-scale topology and large-bandwidth environments, such as data-center networks (DCNs). CVPF is the most stable and is suitable for small-scale topology and small-bandwidth environments such as 5G edge computing. MDPF has moderate sensitivity and stability, so it is a general approach.
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Acknowledgements
This work is supported by the National Science 1054 Foundation of China (NSFC 62072012), Key-Area Research and Development Program of Guangdong Province (2020B0101090003), Shenzhen Project (JSGG20191129110603831), and Shenzhen Key Laboratory Project (ZDSYS201802051831427), and the project “PCL Future Regional Network Facilities for Large-scale Experiments and Applications”.
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This article belongs to the Topical Collection: Special Issue on Convergence of Edge Computing and Next Generation Networking
Guest Editors: Deze Zeng, Geyong Min, Qiang He, and Song Guo
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Zhang, M., Luo, J., Zhang, L. et al. Comparative analysis of probabilistic forwarding strategies in ICN for edge computing. Peer-to-Peer Netw. Appl. 14, 4014–4030 (2021). https://doi.org/10.1007/s12083-021-01219-x
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DOI: https://doi.org/10.1007/s12083-021-01219-x