In addition, new devices are added to the network to handle these workloads. For a more detailed explanation, see How to explain edge computing in plain English.] Integrating all the layers of our edge computing architecture. After building the CI/CD hub, we use it to onboard each of the xNFs in our network layer. In our use case, we are using OpenShift and OpenStack as the VIM to manage the network layer and deploy components of our 5G network slice on the 5G core xNF. Both OpenStack and OpenShift provide VIM capabilities to manage the virtual infrastructure where vNFs (to OpenStack) and cNFs (to OpenShift) can be deployed. Users are given restricted access to certain namespaces or projects based on cluster roles and other controls. On-premise edge computing retains sensitive data on-premises while still taking advantage of the elasticity offered by the edge … At the same time, the central data center oversees the proceedings and gets valuable insights the local data processing. Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth.. This infrastructure requires effective use of resources that may not be continuously connected to a network such as laptops, smartphones, tablets, and sensors. Cache and buffering optimization The ‘Edge’ refers to having computing infrastructure closer to the source of data. An example of location properties for an OpenStack tenant: These deployment locations can be used as a parameter in a service design to define where particular xNFs will be deployed. In this edge computing series, we provided a high-level overview of edge. This is bad news in the case of data-reliant devices such as self-driving cars. You create a network slice and all devices that are needed to the monitor safety are dedicated to this slice. Amazon is operating worldwide. The move toward edge computing is driven by mobile computing, the decreasing cost of computer components and the sheer number of networked devices in the internet of things (IoT). The data is then sent to the IMS for transmission to the end point. Edge computing in IT is defined as the deployment of data-handling activities or other network operations away from centralized and always-connected network segments, and toward individual sources of data capture, such as endpoints like laptops, tablets or smartphones. It may be referred to as a distributed IT network architecture that enables mobile computing for data produced locally. Photo: Stephen Gossett Photo: Stephen Gossett What Is Edge Computing? The application can be deployed to the application layer including servers or to the device layer such as a cameras. We identified xNFs that are needed to build the 5G network slice service, and we have a CI/CD pipeline in place, and now we need to complete the following two steps before the network slice service can be finalized and added to a service catalog. Most current xNFs are virtualized, but future xNFs will primarily be containerized. The result is the video is streamed to the application layer for further analysis using the network layer. Part one of two on an exploration of distributed cloud architecture. For example: lmctl project push --armname . However, before we do that, we need to determine the VIM on which these xNFs should run on. In our example, to configure an observer job, you will need to provide a Unique ID for the job, IBM Agile Lifecycle Manager instance name to identify the IBM Agile Lifecycle Manager, Topic (Kafka topic), Group ID (Kafka group ID), and connection details such as Kafka host and port to be used. Edge computing. This creates the transport network to connect the 5G network components in our deployment. The solution for this is to create a network slice for the worker safety application. CI/CD is a process/practice that is used to quickly and safely push your development cycle updates. In this article, we’ll step through how to do this for the 5G Core xNF. Both processes rely on data processing on the spot for initial proceedings (i.e. We used Ansible resource manager for automation, so we create Ansible playbooks to create our xNF packages. In order to view a topology, you need to define a seed resource on which to base your view. Key Differences between Data Lake and Data Warehouse, Cloud Service Models Explained: SaaS v PaaS v IaaS v DBaaS. Set up the network function virtualized infrastructure (NFVi) with infrastructure managers (VIMs). Learn more here. This approach reduces the need to bounce data back and forth between the cloud and device while maintaining consistent performance. Running applications in the application layer that will use the network layer for network functions. All the above xNFs are needed to create a network slice. Cloud computing is one of those emerging technologies with a need of storing data and providing scalable services in its field. The advanced 5G features and capabilities for IoT, intelligent edge, and AI/IVR are very real and attention should be paid to 5G network architecture in order to take advantage. In addition to this, Uber and Lyft are testing autonomous driving systems as a service. PRIVATE VS. The network layer includes the network components, such as routers and switches, that are needed to run the local edge. The network layer is virtualized because managing physical network devices at the edge is a very complex task. Service design also includes definitions of relationships between xNFs and their intent-based lifecycle events. Edge computing definition. The network traffic can vary as multiple video streams can be flowing though the network and devices keep getting added and removed. We will configure OpenStack and Red Hat OpenShift as data center locations where our xNFs can be deployed. In this step, you need to create a CI/CD pipeline with tools like Jenkins and Gogs to manage the onboarding and testing of xNFs and network services. Edge computing is a kind of expansion of cloud computing architecture - an optimized solution for decentralized infrastructure. Since its location is at the edges of the diagram - it's name reflects this fact. They also do not offer the simplicity or speed that is necessary for the feasibility of edge computing. Next to each icon is a number that indicates the number of events with that severity. As speed of data analysis is key in some Industrial Internet of Things applications, edge computing has recently seen a dramatic increase in popularity among Industrial Internet of Things ecosystems. Each row contains the characteristics of a single event. To summarize, the full end-to-end implementation of an edge use case will involve the following: Deployment and management of the application layer as described in Part 2 of this series. In this paper, we survey state-of-the-art methods, protocols, and applications in this new emerging area. send results of the operation). The events area contains a table of events and their characteristics. This enables much faster customer turnaround with lesser chances of getting into a bottleneck at the counter. Edge computing is a distributed information technology (IT) architecture in which client data is processed at the periphery of the network, as close to the originating source as possible. All these different layers communicate through the network layer. This is the case for edge computing architecture. Edge solutions can also be utilized as part of a private network, which isolates architecture and makes it safer and more resilient. This approach reduces the need to bounce data back and forth between the cloud and device while maintaining consistent performance. The following figure shows the topology view of our 5G Slice Network service. We start off with a network engineer that loads the software. To open the topology viewer, under the Agile Service Management subheading, from the Incident drop-down menu, choose Topology Viewer. Healthcare is one of those industries that takes the most out of emerging technologies. However, the underlying network layer needs to be available to run these applications at the edge. This architecture allows distributed cloud to overcome the following potential challenges with public cloud: The following screenshot highlights the deployment location input configuration in the service design for each xNF component of our 5G Slice service: 5G Core, IMS, and Juniper xNF. In edge computing, data is processed by the device itself or by a local computer or server, rather than being transmitted to a data centre. To create a network slice service you need to chain the 5G core, IMS, and Juniper xNF assemblies built on the xNFs in Step 1. The intermediary server method is also used for remote/branch office configurations when the target user base is geographically diverse (in other words - all over the place). The data is sent to the transport layer to the 5G core. This negatively impacts the video analytics for the worker safety application. Overall, five key challenges come with the implementation of edge computing applications. You will notice that Edge computing architectures are an expansion of IoT (Internet of Things) architectures and use terms like OT for operational technology. Edge computing definition. This aspect helps to maintain its timely and consistent performance. Multi-access edge computing (MEC), formerly mobile edge computing, is an ETSI-defined network architecture concept that enables cloud computing capabilities and an IT service environment at the edge of the cellular network and, more in general at the edge of any network. Architecture of IoT Edge Computing. The following article, Cloud Computing Architecture provides an outline of the architecture of cloud computing. Edge computing works with Cloud computing, not against ... By asking the Edge vendor about these important architecture considerations, you will ensure you have an Edge stack which can be used quickly and securely to develop and deploy Edge applications at scale. This process requires rapid-fire data processing to gain situational awareness. Then, we create scripts for lifecycle events such as Install, Start, Stop, Configure and Integrity check. Edge operations shouldn’t necessarily just cut … The emergence of IoT devices, self-driving cars, and the likes, opened the floodgates of various user data. The sensors are made out of a NodeMCU and a DHT11, as explained in the first step of the first tutorial . Gather and analyze sensor data on the edge, Edge computing architecture and use cases, Building out the edge in the application layer and device layer, Telecommunications, Media & Entertainment, Understanding the network layer of an edge computing architecture, Step 1: Identify your network function components (xNFs), Step 2: Set up the Network Function Virtualization Infrastructure (NFVi) and Virtual Infrastructure Manager (VIM), Step 4: Onboarding and managing the xNF components that are needed for the network slice, Step 5: Test the deployment of xNF components to OpenStack and OpenShift to provision the network slice, Step 6: Configure your operations platform, Viewing the 5G network slice topology in the Topology Viewer, Integrating all the layers of our edge computing architecture, Building and deploying a 5G network service for your edge apps (this article), Network function (xNFs) components which can be Virtualized (vNF) or Containerized (cNF), Virtualized infrastructure manager (VIM), which is the infrastructure on which the xNFs will run, Management and orchestration (MANO) and monitoring components, which are used on the xNFs deployed on the network, Continuous integration and continuous deployment (CI/CD) pipeline, which manage xNFs on the VIM using the MANO components, Identify the network function components (xNFs) that will form the building blocks of your 5G network. 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