Deploying ICN in 3GPP’s 5G NextGen Core Architecture

Ravindran, Ravishankar; Suthar, Prakash; Chakraborti, Asit K.; Amin, Syed Obaid; Azgin, Aytac; Wang, Guoqiang

doi:10.1109/5gwf.2018.8517046

Cited by 29 publications

(37 citation statements)

References 10 publications

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“…However, the natural support for servicecentric networking in ICN can minimize the network related configuration for applications. It will reduce the reconfiguration delay and allow fast resolution for named service instances [181].…”

Section: Information Centric Networkingmentioning

confidence: 99%

Survey on Multi-Access Edge Computing for Internet of Things Realization

Porambage

Okwuibe

Liyanage

et al. 2018

IEEE Commun. Surv. Tutorials

622

328

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The Internet of Things (IoT) has recently advanced from an experimental technology to what will become the backbone of future customer value for both product and service sector businesses. This underscores the cardinal role of IoT on the journey towards the fifth generation (5G) of wireless communication systems. IoT technologies augmented with intelligent and big data analytics are expected to rapidly change the landscape of myriads of application domains ranging from health care to smart cities and industrial automations. The emergence of Multi-Access Edge Computing (MEC) technology aims at extending cloud computing capabilities to the edge of the radio access network, hence providing real-time, high-bandwidth, low-latency access to radio network resources. IoT is identified as a key use case of MEC, given MEC's ability to provide cloud platform and gateway services at the network edge. MEC will inspire the development of myriads of applications and services with demand for ultra low latency and high Quality of Service (QoS) due to its dense geographical distribution and wide support for mobility. MEC is therefore an important enabler of IoT applications and services which require real-time operations. In this survey, we provide a holistic overview on the exploitation of MEC technology for the realization of IoT applications and their synergies. We further discuss the technical aspects of enabling MEC in IoT and provide some insight into various other integration technologies therein.

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Section: Information Centric Networkingmentioning

confidence: 99%

Survey on Multi-Access Edge Computing for Internet of Things Realization

Porambage

Okwuibe

Liyanage

et al. 2018

IEEE Commun. Surv. Tutorials

622

328

View full text Add to dashboard Cite

show abstract

“…In [34], the potential of ICN in 5G systems and, specifically, in the 5G core network (5GC) is discussed, by specifying extensions to the 5GC's control plane (CP) and user plane (UP) to support ICN traffic. Unlike the aforementioned work, our proposal mainly focuses on the RAN segment and specifically considers the NDN architecture.…”

Section: Gap Analysis and Contribution Of This Papermentioning

confidence: 99%

Enhancing the 3GPP V2X Architecture with Information-Centric Networking

et al. 2019

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Vehicle-to-everything (V2X) communications allow a vehicle to interact with other vehicles and with communication parties in its vicinity (e.g., road-side units, pedestrian users, etc.) with the primary goal of making the driving and traveling experience safer, smarter and more comfortable. A wide set of V2X-tailored specifications have been identified by the Third Generation Partnership Project (3GPP) with focus on the design of architecture enhancements and a flexible air interface to ensure ultra-low latency, highly reliable and high-throughput connectivity as the ultimate aim. This paper discusses the potential of leveraging Information-Centric Networking (ICN) principles in the 3GPP architecture for V2X communications. We consider Named Data Networking (NDN) as reference ICN architecture and elaborate on the specific design aspects, required changes and enhancements in the 3GPP V2X architecture to enable NDN-based data exchange as an alternative/complementary solution to traditional IP networking, which barely matches the dynamics of vehicular environments. Results are provided to showcase the performance improvements of the NDN-based proposal in disseminating content requests over the cellular network against a traditional networking solution.

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“…The 5G system adopts the Control-Plane and User-Plane Separation (CUPS) architecture. In our ENRS, UE first sends an EID resolution request to the local hierarchical HM based on response time requirements to get the NA(s) of EID through Control-Plane functions, such as extensional Access and Management Function (AMF++) and extensional Session and Mobility Function (SMF++) [46] When the NA(s) re returned, then UE will send a data request to the NA(s) and perform the cache strategies through User Plane Function (UPF).…”

Section: System Modelmentioning

confidence: 99%

A Temporally Hierarchical Deployment Architecture for an Enhanced Name Resolution System

2019

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The challenging requirements of the fifth generation (5G) cellular networks motivate the need to explore the feasibility of delivering services over new network architectures. Information-Centric Networking (ICN) is an emerging and promising network to satisfy 5G requirements. The name resolution is at the heart of ICN. We focus on satisfying the delay-sensitive requirement of the Name Resolution Service (NRS) in a 5G-ICN integrated network. We aim to design a local NRS that provides a deterministic low latency name resolution service. In this paper, we propose a temporally hierarchical deployment architecture for an Enhanced Name Resolution System (ENRS) to realize deterministic latency. The ENRS quantifiably organizes the nodes into hierarchical and nested domains by latency constraints. We design demand-aware name registration and resolution schemes to achieve constant forwarding hops in order to realize local resolution and forwarding locality. We introduce a tolerable latency-based peer resolver forwarding algorithm to improve the query hit ratio. We present a proactive name binding replicas distribution approach based on temporal–spatial features to reduce the resolution latency and query traffic. The video streaming monitoring service in Smart Home is used as a typical use case to show the continuity of service guaranteed by ENRS. Analysis demonstrates that ENRS can achieve deterministic latency. Evaluation results show that the average query hit ratio of ENRS outperforms the K-NearestNeighbor-Distributed Name Resolution System (KNN-DNRS) and Random Name Resolution System (Random-NRS) with 23.2% and 18.1%, respectively. The query traffic overhead of ENRS is up to 33.3 times smaller than KNN-DNRS. ENRS can process up to 21 GB/s name resolution traffic when the user nodes are in the magnitude order of 106.

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Deploying ICN in 3GPP’s 5G NextGen Core Architecture

Cited by 29 publications

References 10 publications

Survey on Multi-Access Edge Computing for Internet of Things Realization

Survey on Multi-Access Edge Computing for Internet of Things Realization

Enhancing the 3GPP V2X Architecture with Information-Centric Networking

A Temporally Hierarchical Deployment Architecture for an Enhanced Name Resolution System

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