4.6 Article

Information-Centric Networking With Edge Computing for IoT: Research Challenges and Future Directions

期刊

IEEE ACCESS
卷 6, 期 -, 页码 73465-73488

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2018.2884536

关键词

Internet of things; Information centric networking; cloud computing; edge computing; caching; naming; ICN-IoT security services; self-certification; location-awareness; offloading; latency

资金

  1. National Research Foundation of Korea (NRF) - Korea Government [2018R1A2B6002399]

向作者/读者索取更多资源

Cloud computing is a paradigm that offers storage, computation, and software services on demand in the Cloud and far from end users. These services and computations are then extended to the Edge of the network with the Edge computing paradigm. This paradigm offers computation, data, and application services in close proximity of end users. Future Internet architectures will result in a fast information response time, and low latency will be a main feature of evolving 5th generation (5G) radio networks. To ensure the widespread adoption of 5G applications, low latency, security, mobility, and scalable content distribution support is required. Information-centric networking (ICN) is a newly proposed future Internet paradigm in which communication is based on content names irrespective of their locations. At the same time, ICN promises efficient content delivery, mobility support, scalability, and security for content. The Edge computing and ICN provide an opportunity to reduce latency, support mobility, security, and scalability. In this paper, discussions on Edge computing with ICN are provided. In detail, the Edge computing proposals, use cases, differences among Edge computing proposals and drivers for Edge computing are investigated. The Edge computing standardization, research, and industry/vendors collaboration overview are studied. Applications of ICN integration in Edge computing and their advantages and limitations are highlighted. We conclude our paper by describing potential directions for future research in the field of ICN over Edge computing.

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