This is my 2nd article in the series “Edge Computing” articles. In this article I’m going to provide an overview about Project “Akraino” which is an opensource initiative of Edge Computing platforms from LF Edge (Linux Foundation Edge). Read my introduction article about Edge Computing “Introduction to Edge Computing & Open Source Edge Platforms” for more details about the Edge Computing Implementations and is available in the below link.

LF Edge is an umbrella organization that aims to establish an open, interoperable framework for edge computing independent of hardware, silicon, cloud, or operating system. By bringing
together industry leaders, LF Edge will create a common framework for hardware and software standards and best practices critical to sustaining current and future generations of IoT and edge devices.

Akraino Edge Stack

Akraino is a Linux Foundation project initiated by AT&T and Intel, intends to develop a fully integrated edge infrastructure solution, and is completely focused towards Edge Computing. Akraino is a set of open infrastructures (like ONAP, OpenStack, Airship, Kubernetes, Calico etc.) and application blueprints for the Edge, spanning a broad variety of use cases, including 5G, AI, Edge IaaS/PaaS, IoT, for both provider and enterprise edge domains. Akraino edge stack is targeted for all three type of edge computing implementation like MEC, Fog Computing / IoT, Cloudlet.

Since the edge computing solutions require large-scale deployment (typically covering 1000 plus locations) the key requirement for the Akraino project is to keep the cost low and ensure it supports large-scale deployments via automation. The goal of Akraino is to supply a fully integrated solution that supports Zero-touch provisioning, and Zero-touch lifecycle management of the integrated stack.

Akraino is targeted for different use cases and implementation, the community manages these use cases and implementation by defining Blueprints for each deployment. The Blueprints are the declarative configuration of entire stack i.e., Infrastructure / Cloud platform, APIs for managing, and Applications. Here the Declarative configuration management refers to set of tools that allow the users / operators to declare the desired state of the system (be it a physical machine, EC2 VPC or a Cloud account, or anything else), and then allow the configuration management system to automatically bring the system to the declared state.

Every blueprint consists of the following main components.

  • Declarative Configuration which is used to define all the components used within that reference architecture such as Hardware, Software, tools to manage the entire stack, and point of delivery i.e., the method used to deploy in a site
  • The required hardware and software to realize the deployment
  • The CI/CD pipeline for continuous integration and delivery
  • POD – Point of Delivery which defines the BOM of the hardware components to deploy a
    particular deployment with different scale requirement.

Blueprints have been created by the Akraino community and focus exclusively on the edge in all of its different forms. What unites all of these blueprints is that they have been tested by the community and are ready for adoption as-is, or used as a starting point for customizing a new edge blueprint.

Akraino supports VM, container and bare metal workloads based on the application deployment. To meet this, Akraino community works with multiple upstream open source communities such
as Airship, OpenStack, ONAP, etc., to deliver a fully integrated stack. The below link provides the list of blueprints approved by the Akraino.

In this article, I’m going to cover one of the blueprints and explain in detail. Since this article is a series talking about the 5G deployment, the blueprint which I’m going to talk about comes under the “5G MEC System Blueprint Family” and is called as “Enterprise Applications on
Lightweight 5G Telco Edge (EALTEdge)”

EALTEdge Introduction

The main objective of EALTEdge is to provide a platform that can be leveraged by various Telecom operators to give value added services to end users which intends to make a complete
ecosystem for 5G Telco Edge Enterprise level platform. The EALTEdge is targeted for the Telco Edge and provides Lightweight MEP Solution. I had written an article about the collaboration between the 5G Telco Providers and the Cloud Providers in detail sometime back in the below article. One such implementation of 5G providers to enable the Enterprise to run their application in 5G MEC Edge is EALTEdge.

This Lightweight MEC platform enables real-time enterprise applications on 5G telco edge. The following are some of the use cases of EALTEdge deployment

  • Optimized Streaming Media
  • Machine Vision in Campus Networks
  • Mobile Office


The below diagram represent the high level architecture of the EALTEdge platform.

It consists of MEC Management and MEP platform components. The OCD helps is deploying
the MEP and MECM components and consist of list of playbook to deploy the platform and

MECM Components:

  • Application LCM: Handles the application life cycle management of Applications.
  • Catalog: Provides application package management
  • Monitoring: Monitoring and Visualization of platform and applications.
  • Common DB: Persistent Database.

MEC Host Components:

  • MEP Agent: Client Libraries for application developer for service registry and discovery.
  • API Gateway: Single entry point for MEP Services.
  • Certificate Management: Cloud Native Certificate Creation and Management.
  • Secret Management: Cloud Native Secret Generation and Management.
  • Event BUS: Message BUS Service offered to applications.
  • CNI: Container Network.
  • Service Registry: The service registry provides visibility of the services available on the MEC
  • Monitoring: Monitoring and Visualization of platform and applications.
  • Common DB: Persistent Database.

The below diagram represents the software being used in the different layers of EALTEdge platform

Deployment Architecture

Typically the EALTEdege platform will be deployed in 3 different nodes (including OCD node) and the list of software being used in these nodes are as follows. The Deployment Architecture consists of the following nodes

  • One-Click Deployment Node
  • MECM Node
  • MEC Hosts Node

Kingston Smiler Selvaraj

Founder & CEO at PALC Networks ;⠀► Co-Chair at TIP (Telecom Infra Project) OOPT NOS Goldstone sub group 3 articles Following

Few months back I had written an article about the synergy between cloud providers and 5G providers wherein I had covered briefly about edge computing. Refer to the below link to read that article.

In this article I’m going to talk more details about the Edge Computing and Various Open Source alternatives of Edge Computing Platform. This is going to be a series of article and this article covers the introduction. Before getting into the edge computing platforms, let’s look into what is Edge Computing and various implementation of Edge Computing.

Edge Computing: Edge computing refers to running applications closer to the end user by deploying compute, storage, and network functions relatively close to end users and/or IoT endpoints. Edge computing provides a highly distributed computing environment that can be used to deploy applications and services as well as to store and process content in close proximity. Based on the type of edge device, the proximity and implementation of edge computing varies.

For example if the edge device is going to be a mobile phone, then the proximity of edge computing in 5G era is the network operator’s data centers at the edge of the 5G network using MEC implementation (service provide edge). On the other hand, if the edge device is going to be IoT nodes inside a manufacturing plant, then the proximity of edge computing is on-site within the production facility using Fog Computing implementation (user edge). The below diagram represents a high level view of user edge and the service provider edge.

So the implementation of Edge Computing differs based on the end nodes and been
defined with different implementations as

  • Mobile Edge Computing / Multi-Access Edge Computing (MEC)
  • Fog Computing
  • Cloudlet

Mobile Edge Computing / Multi-Access Edge Computing (MEC)

MEC brings the computational and storage capacities to the edge of the network within the 5G Radio Access Network. The MEC nodes or servers are usually co-located with the Radio Network Controller or a macro base-station to reduce latency. MEC provides the ecosystem wherein the operators can open their Radio Access Network (RAN) edge to authorized third-parties, allowing them to flexibly and rapidly deploy innovative applications and services towards mobile subscribers, enterprises and vertical segments.

The MEC is an initiative from Industry Specification Group (ISG) within ETSI. The purpose is to create a standardized, open environment which will allow the efficient and seamless integration of applications from different vendors, service providers, and third- parties across multi-vendor Multi-access Edge Computing platforms. Full specification of MEC is available in

Some of the use cases of MEC are

  • Video analytics
  • OTT (Over the Top services)
  • Location services
  • Internet-of-Things (IoT)
  • Augmented reality
  • Optimized local content distribution and data caching

Fog Computing (FC)

Fog computing is a term created by Cisco that refers to extending cloud computing to the edge of an enterprise’s network. Fog computing is a decentralized computing infrastructure placed at any point between the end devices and the cloud. The nodes are heterogeneous in nature and thus can be based on different kinds of elements including but not limited to routers, switches, access points, IoT gateways as well as set-top boxes. Since cloud computing is not viable for many IoT applications, fog computing is often used to address the needs of IoT and Industrial IoT (IIoT). Fog computing reduces the bandwidth need and reduces the back-and-forth communication between sensors/IoT nodes and the cloud, which can affect the performance badly. Some of the use cases of FC are as follows

  • Transportation / Logistics
  • Utilities / Energy / Manufacturing
  • Smart Cities / Smart Buildings
  • Retail / Enterprise / Hospitality
  • Service Providers / Data Centers
  • Oil / Gas / Mining
  • Healthcare
  • Agriculture
  • Government / Military
  • Residential / Consumer
  • Wearables / Ubiquitous Computing


Cloudlets are similar to public cloud wherein the public cloud provider offers the end user with different offerings like compute, network and storage in the public cloud, however in cloudlets it will be offered in the edge closer to the user location. A cloudlet is basically a small-scale cloud however, unlike cloud computing that provides unlimited resources, the cloudlet can only provide limited resources. The services provided by Cloudlets are over a one-hop access with high bandwidth, thus offering low latency for applications. Cloudlet provides better security and privacy, since the users are directly connected to the cloudlet. Cloudlets are often compared are confused with Fog computing. Typically Fog computing are associated with IoT/ IIoT use cases whereas cloudlets are associated with use cases which requires the traditional cloud offerings in the Edge.

One of the important aspects of cloudlet is handoff across clouds / cloudlets. When a mobile device user moves away from the cloudlet he is currently using there is a need to offload the services on the first cloudlet to the second cloudlet maintaining end-to-end network quality. This resembles VM migration in cloud computing but differs considerably in a sense that the VM handoff happens in Wide Area Network (WAN).

Till now we have seen about the various implementation of edge computing. Now we are going to see the various platforms especially the open source platforms available in the
market to realize the edge platform.

The below are the list of platform available in the open source community for MEC segment

  • Akraino Edge Stack (LF Edge)
  • CORD (Linux Foundation)
  •  Airship (OpenStack Foundation)
  • StarlingX (OpenStack Foundation)

The above list is not exhaustive.

There are many other projects for FOG / IoT use case like

  • EdgeX Foundry (LF Edge)
  • KubeEdge
  • Eclipse IoFog (Eclipse)
  • Baetyl (LF Edge)
  • Eclipse Kura (Eclipse)
  • Fledge (LF Edge)
  • Edge Virtualization Engine (LF Edge)
  • Home Edge etc. (LF Edge)

Below are some of the projects in cloudlet

  • OpenStack++
  • Elijah Cloudlet Project.

This is going to be a series of articles and in the next article, we are going to see the MEC
Edge stack in detail with Akraino Edge Stack and CORD.