Opensource Projects for Edge Computing

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Edge Computing involves optimizing cloud computing systems by performing data processing near the data source, i.e., at the Edge of the network. Edge computing decentralizes workloads, in contrast to cloud computing. Edge computing is used to support modern use cases like real-time IoT, connected cars, remote health care, video gaming, virtual and augmented reality where it reduces network latency for better user experience. This blog provides a basic introduction to some of the opensource projects that have emerged based on Edge Computing. Each of these projects varies based on use cases and Edge implementations.

Opensource Projects for Edge Computing

Intel OpenNESS

This project aims at fostering open collaboration and application innovation at Edge computing, feasible for IoT and cloud-native applications to develop solutions for Edge and 5G. OpenNESS enables performance Edge platforms to onboard and manage network functions and applications with cloud-like agility across any kind of network. OpenNESS abstracts network complexity and makes applications migration easy from cloud to Edge. It is built using a modular, microservice-based architecture that lays the foundation for various activities like traffic steering, access termination, service registry, telemetry, service authentication, appliance discovery, and so on.

Figure 1: Same applications run unmodified in cloud and different edge locations with OpenNESS

To know more about Intel OpenNESS project, visit https://www.openness.org/

Akraino Edge Stack

This is a well-known open-source Edge project under Linux Foundation (LF). Akraino Edge stack, launched in 2018. The main goal of Akraino is to create an opensource software stack that supports a high-availability cloud stack optimized for Edge computing applications. Akraino is an umbrella of several blueprints and we can choose any deployable blueprint based on our requirement.

Akraino’s first premier release R1 has ten “ready and proven” blueprints including Radio Edge Cloud (REC), Network cloud, StarlingX Far Edge Distributed Cloud, Edge Lightweight, and IOT (ELIOT), and Kubernetes-Native Infrastructure (KNI). Some of the recently added blueprints to these existing R1 blueprints are connected vehicle, integrated cloud-native NFV/ application stack (ICN), SDN-enabled broadband access (SEBA), Network cloud, and Tungsten Fabric, and IEC type 4/ AR/VR- oriented Edge stack. Akraino R2 delivers an open-source Edge cloud innovation to IoT, enterprise Edge services, and telco services for flexibility and scalability. Akraino recently released its R3 in August 2020 which delivers a fully functional open source edge stack with innovative support for new levels of flexibility that scale 5G, telco, enterprise edge cloud, and industrial IoT. Akraino R3 includes 6 new blueprints including 5G MEC/Slice system, AI edge, micro-MEC, IEC type 3 (android cloud-native applications on Arm servers on the edge). Akraino can be used in use cases from every field.

Figure 2: Akraino Edge Stack: Scope

To know more about Linux Foundation Akraino, visit https://www.lfedge.org/projects/akraino/

KubeEdge

This project by Huawei joined the CNCF foundation in March 2019. This is the first Kubernetes native Edge computing platform. KubeEdge can extend native containerized orchestration capabilities to host at the Edge. A Kubernetes based mini cloud in Edge site is possible with KubeEdge as it already has cloud synchronization, service management, and device management facilities applied inside. KubeEdge v1.4 released in August 2020 has a major upgrade for maintainability and edge devices management.

Figure 3: KubeEdge workflow at the edge

To know more about KubeEdge, visit https://kubeedge.io/en/

TARS Microservices Platform

Tars is a high-performance microservice framework that offers excellent solutions for a variety of applications, including Edge computing. To address the requirements of Edge computing, Tars is optimized to have a high-performance RPC component and a light-weight framework. TARS framework supports multiple languages and microservice related functions such as load balancing, service register/discovery, flow control, area perception, tracing, set mode, and so on.

Figure 4: TARS Micro-service Ecosystem

To learn more about TARS framework, visit https://www.linuxfoundation.org/blog/2020/03/the-tars-foundation-the-formation-of-a-microservices-ecosystem/

LF Edge

This aims at establishing an open, interoperable Linux Foundation framework for Edge computing which will work independent of silicon, hardware, operating system, or cloud. LF Edge is an umbrella organization that aims at creating a common framework for Edge irrespective of hardware and software standards, bringing together all the best practices to foster current and future developments in Edge computing and IoT. LF Edge groups together some important edge projects across cloud, enterprise, and IoT to enhance unification across communities, platforms, and ecosystems. Some of the renowned projects are Akarino Edge Stack, Baetyl, Edge XFoundry, Edge Virtualization Engine, Fledge, Home Edge, State of the Edge, and Open Horizon.

Figure 5: Scope of LF Edge

To know more about LF Edge, visit https://www.lfedge.org/

StarlingX Platform

StarlingX is an Openstack foundation project. Intel and WindRiver have jointly open-sourced this project. This opensource project is based on IoT and edge computing platform and offers support for various low-latency and high-performance use cases with its several useful features. It offers a highly reliable and scalable edge infrastructure that is tested and available as a complete stack. StarlingX has recently launched its release 4.0. StarlingX ensures compatibility with other opensource components and provides unique support for service management and fault tolerance. The important features of StarlingX are re-configure proven cloud technologies for edge, robustness, maturity, scalability, low latency, reliability, and high performance. Use cases include IoT, video delivery, telecom, 5G, industrial automation, smart buildings, and smart cities, virtual radio access networks (vRAN), and other ultra-low-latency applications.

Figure 6: StarlingX Use cases

To know more about StarlingX, visit https://www.starlingx.io/learn/

Extra Information on Related Projects

There are even more open source projects for edge computing and they cover a variety of use cases and scenarios. The table below provides extra information on these projects for your reference.

ProjectFoundationScopeOfficial Website/Code Repo
AirshipOpenStack FoundationOpenstack on Kuberneteshttps://www.airship.com/
Azure IoT EdgeN/AInternet of Things (IoT) service that offload task to edgehttps://azure.microsoft.com/en-in/services/iot-edge/
CORDLinux FoundationMEC for residential, enterprise & mobilehttps://www.linuxfoundation.org/tag/cord-project/
Eclipse KuraEclipse FoundationPlatform for building IoT gateways, enabling remote management & app deploymenthttps://www.eclipse.org/kura
EdgeX FoundryLinux FoundationCommon framework for Edge solutions (SDK) https://www.edgexfoundry.org/
ioFogEclipse FoundationEdge computing platform through microservice at edgehttps://iofog.org/
ONAP4K8SLinux FoundationPlatform for managing network functions and applications across edge and cloudhttps://github.com/onap/multicloud-k8s
OpenEdgeN/AOpen edge computing frameworkhttps://github.com/baetyl/baetyl
vCOLinux FoundationMEC for residential, enterprise & mobilehttps://wiki.opnfv.org/display/OSDD/VCO+Demo+3.0+Home

Conclusion

Edge computing is in its budding stage and its popularity will likely lead to more use cases, implementation, and an increase in the number of projects in the future. This article provides just a glimpse of some of the opensource projects available in the market today.

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