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As mobile internet and IoT develop rapidly, there are needs for diverse 5G services. 3GPP has defined three major 5G scenarios: enhanced mobile broadband (eMBB), ultra reliable low latency communications (uRLLC), and massive machine-type communications (mMTC). The eMBB scenario provides high-traffic mobile broadband services, such as high-speed download, HD video and VR/AR, with peak rates exceeding 10 Gbps and the bandwidth up to dozens of Gbps, which will put great pressure on wireless backhaul networks. Therefore, it is necessary to deploy services to the network edge as much as possible for local offload. The URLLC scenario provides ultra reliable and low latency communication services, such as automatic driving, industrial control and telemedicine, requiring an end-to-end high reliability of up to 99.999% and an end-to-end ultra-low latency of less than 1 ms to meet the higher requirements of the digital industry. In this case, services need to be moved to the network edge to reduce the latency caused by network transmission and multi-level service forwarding.
Traditional large-scale centralized telecom cloud cannot meet the requirements of 5G eMBB and URLLC scenarios. Multi-access edge computing (MEC) thus comes into being. As a key technology of 5G evolution, MEC provides cloud computing and IT service environments for edge applications at the network edge closer to customers. MEC features ultra-low latency, ultra-large bandwidth, and local real-time analysis and processing. On the one hand, MEC is deployed at the network edge, and edge services operate on terminals, resulting in faster feedback for addressing the latency issue. On the other hand, MEC allows contents and computing capability to be given at the edge and provides intelligent traffic scheduling, local offload and local content cache, so that some regional services can be terminated locally. This not only improves user experience but also reduces the occupation of backbone transmission and upper-layer core network resources. Therefore, MEC will be the best choice for 5G edge cloud deployment in the 5G era.
Location to Deploy MEC
MEC does not restrict its network deployment mode. It can be flexibly deployed in accordance with specific service scenarios and latency requirements. MEC resources can be deployed in access office (AO), central office (CO), and regional office (RO), as shown in Fig. 1.
To improve the adaptability and resource density of MEC deployment, ZTE and Intel jointly launched a dedicated open edge platform (OEP600) that adopts a small all-in-one machine with the chassis depth of only 450 mm. Its CPU uses latest Intel's Xeon scalable processor to provide higher computing performance for edge computing. OEP600 supports wide temperature operation, strong heat dissipation, and easy maintenance, meets the requirements of multiple MEC deployment environments, and achieves the best match between performance and cost. At the MEC Technology and Industry Development Summit 2019, ZTE won the MEC Technology Innovation Award 2018–2019 for its edge computing hardware platform OEP600, fully demonstrating ZTE's innovation capability and leadership in the field of edge computing.
Deploying a Unified MEC Management Platform
Edge clouds are usually small in scale, large in number and dispersed in location, which brings great complexity to their planning, deployment, operation and maintenance (O&M). It is therefore necessary to deploy a unified MEC management platform on the upper-level convergence sites to manage lower-level edge sites in a unified manner (Fig. 2). Only computing nodes and storage nodes are deployed on each edge cloud to reduce resource usage of the management module.
The unified management of MEC is implemented in two aspects: resource management and O&M management.
—Unified resource management: The MEC management platform manages and allocates resource pools (computing, storage, and networks) on all edge nodes in a unified manner. It provides a unified interface to centrally monitor the topology, alarm, performance, capacity, and other information of physical resources on each edge node, and also provides fault location means such as log and alarm analysis for infrastructure administrators. NFVO, which is only deployed on the upper-layer convergence nodes, directly interconnects with the unified MEC management platform to avoid interconnection with the resource pools of all edge nodes and to uniformly orchestrate and deploy virtual machines (VMs) and containers deployed on all edge nodes.
—Unified O&M management: The MEC management platform provides unified O&M management for VIMs in each edge cloud, including site management, user/tenant management, feature configuration, image distribution, centralized backup, upgrade/patch management, inspection, and API distribution. It provides unified FCAPS management, unified alarm, configuration, and performance statistics. It also provides smart and simple automation tools for fast installation and upgrade, fast inspection, fast fault analysis and location, and log analysis to improve O&M efficiency.
Deploying 5G UPF to the Edge for Local Offload
To meet the requirements for big bandwidth and low latency in 5G application scenarios, MEC will be deeply integrated with 5G network architecture during deployment, and its service distribution, policy control, and QoS guarantee will be implemented through standard 5G network functions. Based on the C/U separation architecture of a 5G core network, user plane function (UPF) needs to be deployed at the network edge to reduce transmission latency and implement local offload of data traffic. The control plane's functional network elements such as SMF are deployed in the central DC for unified control of UPFs deployed in MEC as well as unified configuration and distribution of offload policies.
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