Category

Akraino

What do LF Edge, Akraino, OPNFV, ONAP, Fishing and Fairy Tales Have in Common?

By Akraino, Blog

Written by Aaron Williams, LF Edge Developer Advocate

What do LF Edge, Akraino, OPNFV, ONAP, fishing and fairy tales have in common?  They all came up during our interview with the new Chair and Co-Chair of LF Edge’s project Akraino.

LF Edge’s Akraino project recently wrapped up our semi-annual face to face and welcomed newly elected Technical Steering Committee Chairs.

After two terms of serving as a co-chair, Tina Tsou, Enterprise Architect at Arm, was elected to be the Chair this year and Oleg Berzin, Technology Innovation Fellow under the Office of the CTO at Equinix, was elected Co-Chair by the Akraino TSC members.  We sat down with Tina and Oleg to learn more about them, what they are looking forward to next year, and how they see Akraino growing in 2021.

Tina Tsou

Oleg Berzin

How did you first get involved with Akraino?  

[Tina Tsou] My introduction to Akraino happened when I was working on an Edge use case for one of our customers at Arm. But I’m no stranger to the open source communities and working groups. Before Akraino, I directed the OPNFV (Open Platform for Network Function Virtualization) Auto project as PTL, integrating ONAP onto OPNFV (upon both x86 and Arm architecture and hardware) with a focus on edge cloud use cases. I was also the Chair of the Open Source SDN Breckenridge Working Group.

I am currently an active member of the Linux Foundation Networking (LFN) Technical Advisory Committee (TAC) and also lead the VPP/AArch64 activities in FD.io representing Arm.

[Oleg Berzin] Akraino aligned with my interest in the Edge and more specifically in the multi-domain nature of the Edge (spanning from devices to networks, to aggregation, to data centers, to clouds). I was involved in the ONAP (Open Network Automation Platform) project in the past (as an operator/user). With the diverse and complex nature of the edge deployments, we need a community supported set of capabilities integrated as blueprints so customers/user can deploy these solutions with minimum friction.

What was the first blueprint that you worked on?

[Tina Tsou] For Akraino, I worked closely on the Integrated Edge Cloud(IEC) blueprint family which is part of the Edge Stack of Akraino. The blueprint intends to develop a fully integrated edge infrastructure solution for Edge Computing. This open source software stack provides critical infrastructure to enable high performance, reduced latency, improved availability, lower operational overhead, provide scalability, address security needs, and improve fault management. The IEC project will address multiple edge use cases beyond the Telco Industry. IEC intends to develop solutions and support the needs of carriers, service providers, and the IoT networks.

[Oleg Berzin] The first blueprint I worked on was the Public Cloud Edge Interface (PCEI). The idea behind PCEI is to enable interworking between mobile operators, public clouds and edge infrastructure/application providers so that operators have a systematic way to enable their customers access to public and 3rd party edge compute resources and applications via open APIs that facilitate deployment of telco and edge compute functions, interconnection of these functions as well as intelligent orchestration of workloads so that the expected performance characteristics can be achieved.

What is a Blueprint that you find interesting (I know that you don’t have a “favorite”)?

[Tina Tsou] You’re right. It is hard to choose a favorite blueprint since all of them are interesting and serve purposeful needs for many use cases. But here are two that I find very interesting:

School/Education Video Security Monitoring Blueprint: This belongs to the AI Edge Blueprint family and focuses on establishing an open source MEC platform that combined with AI capacities at the Edge. In this blueprint, the latest technologies and frameworks like microservice framework, Kata container, 5G accelerating, and open API have been integrated to build an industry-leading edge cloud architecture that could provide comprehensive computing acceleration support at the edge. This blueprint is a life saver and hence my favorite since it improves the safety and engagement in places such as factories, industrial parks, catering services, and classrooms that rely on AI-assisted surveillance.

IIoT at the Smart Device Edge Blueprint family: This blueprint family use case is for those devices that live at the Smart Device Edge are characterized by having a small footprint yet being powerful enough to be able to compute tasks at the edge.  They tend to have a minimum of 256 MB for a single node and can grow to the size of a small cluster.  These resources could be a router, hub, server, or gateway that are accessible.  Since these device types vary heavily based on the form factor and use case served, they have a very fragmented security and device standards on how the OS and firmware is booted. This is where Arm backed initiatives like Project Cassini and PARSEC helps to enable the standardization of device booting and platform security. I’m excited for this blueprint to see successful deployments of Edge based compute.

[Oleg Berzin] One thing that surprised me when I joined Akraino was the diversity of use cases (IOT, AI, Private 5G, Radio Edge Cloud) that reinforce the notion that edge is everywhere and that it is very complex. I am honored to work with the Akraino community and contributing to the development of blueprints. At this point in time my goal is to make progress in the PCEI blueprint.

Is there a Blueprint that you are looking forward to seeing develop?

[Tina Tsou] I prefer the IEC Type 3: Android cloud native applications on Arm servers in edge for Integrated Edge Cloud (IEC) Blueprint Family. It evolves from Anbox based for single instance in R3, Robox based for multiple instances in R4, and my hope is to have a support for vGPU in the near future.

[Oleg Berzin] I think the Radio Edge Cloud is a very interesting blueprint. If developed, it has a potential of revolutionizing how the radio infrastructure is managed and adopted to diverse use cases.

What is the biggest misconception that people have about Akraino?

[Tina Tsou] As with many open source projects and technologies, the common perception that users have is that these projects serve a very narrow use case. I believe Akraino suffers from a similar misconception that it is a Telco-oriented project only. The reality is quite different. Akraino project blueprints can be applied in many facets of the industry verticals from Edge, Cloud, Enterprises, and IoT.

[Oleg Berzin] I am relatively new to Akraino, and my own misconception was that it only focused on small edge devices and IoT. As a Co-Chair and now having been exposed to the breadth and depth of use cases, I can now see that Akraino is involved in a very diverse set of blueprints targeting enterprise, telco and clouds while also interworking with other organizations and communities, such as ORAN, 3GPP, CNCF, LF Networking, TIP.

What are your and Akraino’s priorities for 2021?

[Tina Tsou &Oleg Berzin] There are multiple that we can list but we would point to these top 3 priorities for 2021.

  1. Akraino Blueprints for O-RAN specifications (e.g., REC integration with RIC)
  2. Akraino Blueprint to support Public Cloud Edge interface
  3. Akraino Edge APIs

What do you like to do in your free time?

[Tina Tsou] I live in the sunny-California bay area and I love fishing during weekends. Anyone who is interested to join me and have a chat about the Akraino project can contact me. 🙂

[Oleg Berzin] Apart from being involved in the technology and networking industry for many years, I enjoy learning new languages and finding common roots in different cultures. I sometimes find inspiration and time to translate children fairy tales from Russian into English – you can find the tales that I translated on Amazon.

Anything that you want people to know about Akraino?

[Tina Tsou] Ever since its launch in 2018, Akraino has found great community support for innovative creation of deployable Edge solutions with work going in more than 30+ Blueprints. These Akraino blueprints are now globally deployed to address several Edge Use Cases. It is a vast community with many active users and contributors and here are few things to know of:

  • Akraino hosts sophisticated communities and multiple user labs to speed the edge innovation.
  • Akraino delivered fully functional new Blueprints for deployment in R3 to address edge use cases such as 5G MEC, AI Edge, Cloud Gaming at Edge, Android in Cloud, Micro-MEC and Hardware acceleration at the edge.
  • Created framework for defining and standardizing APIs across stacks, via upstream/downstream collaboration and published a whitepaper.
  • Akraino introduced tools for automated Blueprint Validations, security tools for Blueprint Hardening and Edge API’s in collaboration with LF Edge projects
  • Akraino community has participated in several industry outreach events that featured participation to foster collaboration and engagement on edge projects across the entire ecosystem.

[Oleg Berzin] The most important fact I want people to know about Akraino is the dedication and professionalism of the individuals who make up our community. The work they do on creating and proving the blueprints is done on a volunteer basis in addition to their primary jobs. It takes long hours, patience, respect for others and true trust to work together and move the edge technology forward.

XGVela: Bring More Power to 5G with Cloud Native Telco PaaS

By Akraino, Blog

Written by Sagar Nangare, an Akraino community member and technology blogger who writes about data center technologies that are driving digital transformation. He is also an Assistant Manager of Marketing at Calsoft.

A Platform-as-a-Service (PaaS) model of cloud computing brings lots of power to the end-users. It provides a platform to the end customers to develop, run, and manage applications without the complexity of building and maintaining the infrastructure typically associated with developing and launching an application. In the roadmap to build a 5G network, telecom networks need such breakthrough models that help them focus more on the design and development of network services and applications.

XGVela is 5G cloud-native open-source framework that introduces Platform-as-a-Service (PaaS) capabilities for telecom operators. With this PaaS platform, telecom operators can quickly design, develop, and innovate the telco network functions and services. This way, there will be more focus on seizing business opportunities for telecom companies rather than diving into complexities of telecom infrastructure.

China Mobile initiated this project internally which was later hosted and announced by Linux Foundation as a part to support the initiative to accelerate the telco cloud adoption. Apart from China Mobile, other supporters of XGVela are China Unicom, China Telecom, ZTE, Red Hat, Ericsson, Nokia, H3C, CICT, and Intel.

Initially for building XGVela, PaaS functionality was brought from existing open-source PaaS projects like Grafana, Envoy, Zookeeper, and further enhanced with telco requirements.

Why need XGVela PaaS capabilities for the 5G network?

  • XGVela helps telecom operators to align with fast changes in requirements to build a 5G network driven by cloud-native backhaul. They need faster upgrades to network functions and services along with agility in new service deployments.
  • Telecom operators need to focus more on the microservices driven and containers-based network functions (CNFs) rather than VM based network functions (VNFs). But need to continue to use both concurrently. XGVela can support CNFs and VNFs both in the underlying platform.
  • Telecom operators want to reduce network construction costs by adopting an open and healthy technology ecosystem like ONAP, Kubernetes, OpenDaylight, Akraino, OPNFV, etc. XGVela adopted this to reduce the barriers that bring end-to-end orchestrated 5G telecom networks.
  • XGVela simplifies the design and innovation of 5G network functions by allowing developers to focus on application development with service logic rather than dealing with underlying complex infrastructure. XGVela provides standard APIs to tie many internal projects

XGVela integrates CNCF projects based on telco requirements to form General-PaaS. It is architected kept in mind the microservices design method for network function development and further integrated into telco PaaS.

XGVela is integrated with OPNFV and Akraino for integration and testing. In a recent presentation, by Srinivasa Adepalli and Kuralamudhan Ramakrishnan shown that feature set of Akraino ICN blueprints are like XGVela. It is seen that many like to deployed CNFs and application on same cluster. In those environments, there is a need to figure out what additional things to be done on top of K8s to enable CNF deployment, especially telco CNF, normal CNF and application deployments, and further need to evaluate how it worked together. This is where XGVela and Akraino ICN BP family are inclined to each other.

You can subscribe to the XGVela mailing list here to track the project progress. For more information about Akraino Blueprints, click here: https://wiki.akraino.org/. Or, join the conversation on the LF Edge Slack Channel #akraino-blueprints #akraino-help #akraino-tsc

LF Edge Member Spotlight: Zenlayer

By Akraino, Akraino Edge Stack, Blog, LF Edge, Member Spotlight

The LF Edge community comprises a diverse set of member companies and people that represent the IoT, Enterprise, Cloud and Telco Edge. The Member Spotlight blog series highlights these members and how they are contributing to and leveraging open source edge solutions. Today, we sit down with Jim Xu, Principal Engineer at Zenlayer, to discuss the importance of open source, collaborating with industry leaders in edge computing, their contributions to Akraino and the impact of being a part of the LF Edge ecosystem.

Can you tell us a little about your organization?

Zenlayer is an edge cloud service provider and global company headquartered in Los Angeles, Shanghai, Singapore, and Mumbai. Businesses utilize Zenlayer’s platform to deploy applications closer to the users and improve their digital experience. Zenlayer offers edge compute, software defined networking, and application delivery services in more than 180 locations on six continents.

Why is your organization adopting an open source approach?

Zenlayer has always relied on open source solutions. We strongly believe that open source is the right ecosystem for the edge cloud industry to grow. We connect infrastructure all over the globe. If each data center and platform integrate open-source software, it is much easier to integrate networks and make literal connections compared to a milieu of proprietary systems. Some of the open source projects we benefit from and support are Akraino Blue Prints, ODL, Kubernetes, OpenNess, DPDK, Linux, mySQL, and more.

Why did you join LF Edge and what sort of impact do you think LF Edge has on the edge, networking, and IoT industries?

We are a startup company in the edge cloud industry. LF Edge is one of the best open-source organizations both advocating for and building open edge platforms. The edge cloud space is developing rapidly, with continuous improvements in cloud technology, edge infrastructure, disaggregated compute, and storage options. Both impact and complexity go far beyond just cloud service providers, device vendors, or even a single traditional industry. LF Edge has helped build a community of people and companies from across industries, advocating for an open climate to make the edge accessible to as many users as possible.

What do you see as the top benefits of being part of the LF Edge community?

Our company has been a member of the LF Edge community for over a year now. Despite the difficulties presented by COVID-19, we have been able to enjoy being part of the Edge community. We interacted with people from a broad spectrum of industries and technology areas and learned some exciting use cases from the LF Edge community. This has helped us build a solid foundation for Zenlayer’s edge cloud services. 

What sort of contributions has your team made to the community, ecosystem through LF Edge participation?

We are proud to be part of the Edge Cloud community. Zenlayer is leading the Upstream subcommittee within Akraino and has invited multiple external communities such as ONF CORD,  CNTT, TIP OCN, O-RAN and TARS to share our common interest in building the edge. We also contributed to the upstream requirement and reviews for Akraino releases.

What do you think sets LF Edge apart from other industry alliances?

LF Edge has a clear focus on edge cloud and a very healthy and strong governing board to ensure unbiased technological drive toward open systems. 

How will LF Edge help your business?

We hope LF Edge will continue to empower rapid customer innovation during the drive to edge cloud for video streaming, gaming, enterprise applications, IoT, and more. As a member of a fast-growing community, we also look forward to more interactions via conferences and social events (digital or in person as is safe) so we can continue to get to know and better understand each other’s needs and how we can help solve them. 

What advice would you give to someone considering joining LF Edge?

LF Edge is a unique community pushing for the best future for edge cloud. The group brings together driven people, a collaborative culture, and fast momentum. What you put in you receive back tenfold. Anyone interested in the future of the edge should consider joining, even if they do not yet know much about open source and its benefits. The community will value their inputs and be happy to teach or collaborate in return.

To find out more about LF Edge members or how to join, click here. To learn more about Akraino, click here. Additionally, if you have questions or comments, visit the  LF Edge Slack Channel and share your thoughts in the #community or #akraino-tsc channels.

Akraino White Paper: Cloud Interfacing at the Telco 5G Edge

By Akraino, Akraino Edge Stack, Blog

Written by Aaron Williams, LF Edge Developer Advocate

As cloud computing migrates from large Centralized Data Centers to the Server Provider Edge’s Access Edge (i.e. Server-based devices at the Telco tower) to be closer to the end user and reduce latency, more applications and use cases are now available.  When you combine this with the widespread roll out of 5G, with its speed, the last mile instantly becomes insanely fast.  Yet, if this new edge stack is not constructed correctly, the promise of these technologies will not be possible.

LF Edge’s Akraino project has dug into these issues and created its second white paper called Cloud Interfacing at the Telco 5G Edge.  In this just released white paper, Akraino analyzes the issues, proposes detailed enabler layers between edge applications and 5G core networks, and makes recommendations for how Telcos can overcome these technical and business challenges as they bring the next generation of applications and services to life.

Click here to view the complete white paper: https://bit.ly/34yCjWW

To learn more about Akraino, blueprints or end user case stories, please visit the wiki: https://wiki.akraino.org.

On the “Edge” of Something Great

By Akraino, Announcement, Baetyl, Blog, EdgeX Foundry, Fledge, Home Edge, LF Edge, Open Horizon, Project EVE, Secure Device Onboard, State of the Edge

As we kick off Open Networking and Edge Summit today, we are celebrating the edge by sharing the results of our first-ever LF Edge Member Survey and insight into what our focuses are next year.

LF Edge, which will celebrate its 2nd birthday in January 2021, sent the survey to our more than 75 member companies and liaisons. The survey featured about 15 questions that collected details about open source and edge computing, how members of the LF Edge community are using edge computing and what project resources are most valuable. 

Why did you chose to participate in LF Edge?

The Results Are In

The Top 3 reasons to participate in LF Edge are market creation and adoption acceleration, collaboration with peers and industry influence. 

  • More than 71% joined LF Edge for market creation and adoption acceleration
  • More than 57% indicated they joined LF Edge for business development
  • More than 62% have either deployed products or services based on LF Edge Projects or they are planned by for later this year, next year or within the next 3-5 years

Have you deployed products or services based on LF Edge Projects?

This feedback corresponds with what we’re seeing in some of the LF Edge projects. For example, our Stage 3 Projects Akraino and EdgeX Foundry are already being deployed. Earlier this summer, Akraino launched its Release 3 (R3) that delivers a fully functional open source edge stack that enables a diversity of edge platforms across the globe. With R3, Akraino brings deployments and PoCs from a swath of global organizations including Aarna Networks, China Mobile, Equinix, Futurewei, Huawei, Intel, Juniper, Nokia, NVIDIA, Tencent, WeBank, WiPro, and more. 

Additionally, EdgeX Foundry has hit more than 7 million container downloads last month and a global ecosystem of complementary products and services that continues to increase. As a result, EdgeX Foundry is seeing more end-user case studies from big companies like Accenture, ThunderSoft and Jiangxing Intelligence

Have you gained insight into end user requirements through open collaboration?


Collaboration with peers

The edge today is a solution-specific story. Equipment and architectures are purpose-built for specific use cases, such as 5G and network function virtualization, next-generation CDNs and cloud, and streaming games. Which is why collaboration is key and more than 70% of respondents said they joined LF Edge to collaborate with peers. Here are a few activities at ONES that showcase the cross-project and members collaboration. 

Additionally, LF Edge created a LF Edge Vertical Solutions Group that is working to enable easily-customized deployments based on market/vertical requirements. In fact, we are hosting an LF Edge End User Community Event on October 1 that provides a platform for discussing the utilization of LF Edge Projects in real-world applications. The goal of these sessions is to educate the LF Edge community (both new and existing) to make sure we appropriately tailor the output of our project collaborations to meet end user needs. Learn more.

Industry Influence

More than 85% of members indicated they have gained insights into end user requirements through open collaboration. A common definition of the edge is gaining momentum. Community efforts such as LF Edge and State of the Edge’s assets, the Open Glossary of Edge Computing, and the Edge Computing Landscape are providing cohesion and unifying the industry. In fact,  LF Edge members in all nine of the projects collaborated to create an industry roadmap that is being supported by global tech giants and start-ups alike.

 

 

Where do we go from here? 

When asked, LF Edge members didn’t hold back. They want more. They want to see more of everything – cross-project collaboration, end user events and communication, use cases, open source collaboration with other liaisons. As we head into 2021, LF Edge will continue to lay the groundwork for markets like cloud native, 5G, and edge for  more open deployments and collaboration.  

 

Where the Edges Meet: Public Cloud Edge Interface

By Akraino, Akraino Edge Stack, Blog

Written by Oleg Berzin, Ph.D., a member of the Akraino Technical Steering Committee and Senior Director Technology Innovation at Equinix

Introduction

Why 5G

5G will provide significantly higher throughput than existing 4G networks. Currently, 4G LTE is limited to around 150 Mbps. LTE Advanced increases the data rate to 300 Mbps and LTE Advanced Pro to 600Mbps-1 Gbps. The 5G downlink speeds can be up to 20 Gbps. 5G can use multiple spectrum options, including low band (sub 1 GHz), mid-band (1-6 GHz) and mmWave (28, 39 GHz). The mmWave spectrum has the largest available contiguous bandwidth capacity (~1000 MHz) and promises dramatic increases in user data rates. 5G enables advanced air interface formats and transmission scheduling procedures that decrease access latency in the Radio Access Network by a factor of 10 compared to 4G LTE.

The Slicing Must Go On

Among advanced properties of the 5G architecture, Network Slicing enables the use of 5G network and services for a wide variety of use cases on the same infrastructure. Network Slicing (NS) refers to the ability to provision a common physical system to provide resources necessary for delivering service functionality under specific performance (e.g. latency, throughput, capacity, reliability) and functional (e.g. security, applications/services) constraints.

Network Slicing is particularly relevant to the subject matter of the Public Cloud Edge Interface (PCEI) Blueprint. As shown in the figure below, there is a reasonable expectation that applications enabled by the 5G performance characteristics will need access to diverse resources. This includes conventional traffic flows, such as access from mobile devices to the core clouds (public and/or private) as well as the general access to the Internet, edge traffic flows, such as low latency/high speed access to edge compute workloads placed in close physical proximity to the User Plane Functions (UPF), as well as the hybrid traffic flows that require a combination of the above for distributed applications (e.g. online gaming, AI at the edge, etc). One point that is very important is that the network slices provisioned in the mobile network must extend beyond the N6/SGi interface of the UPF all the way to the workloads running on the edge computing hardware and on the Public/Private Cloud infrastructure. In other words, “The Slicing Must Go On” in order to ensure continuity of intended performance for the applications.


The Mobile Edge

The technological capabilities defined by the standards organizations (e.g. 3GPP, IETF) are the necessary conditions for the development of 5G. However, the standards and protocols are not sufficient on their own. The realization of the promises of 5G depends directly on the availability of the supporting physical infrastructure as well as the ability to instantiate services in the right places within the infrastructure.

Latency can be used as a very good example to illustrate this point. One of the most intriguing possibilities with 5G is the ability to deliver very low end to end latency. A common example is the 5ms round-trip device to application latency target. If we look closely at this latency budget, it is not hard to see that to achieve this goal a new physical aggregation infrastructure is needed. This is because the 5ms budget includes all radio/mobile core, transport and processing delays on the path between the application running on User Equipment (UE) and the application running on the compute/server side. Given that at least 2ms will be required for the “air interface”, the remaining 3ms is all that’s left for the radio/packet core processing, network transport and the compute/application processing budget. The figure below illustrates an example of the end-to-end latency budget in a 5G network.

The Edge-in and Cloud-out Effect

Public Cloud Service Providers and 3rd-Party Edge Compute (EC) Providers are deploying Edge instances to better serve their end-users and applications, A multitude of these applications require close inter-working with the Mobile Edge deployments to provide predictable latency, throughput, reliability, and other requirements.

The need to interface and exchange information through open APIs will allow competitive offerings for Consumers, Enterprises, and Vertical Industry end-user segments. These APIs are not limited to providing basic connectivity services but will include the ability to deliver predictable data rates, predictable latency, reliability, service insertion, security, AI and RAN analytics, network slicing, and more.

These capabilities are needed to support a multitude of emerging applications such as AR/VR, Industrial IoT, autonomous vehicles, drones, Industry 4.0 initiatives, Smart Cities, Smart Ports. Other APIs will include exposure to edge orchestration and management, Edge monitoring (KPIs), and more. These open APIs will be the foundation for service and instrumentation capabilities when integrating with public cloud development environments.

Public Cloud Edge Interface (PCEI)

Overview

The purpose of Public Cloud Edge Interface (PCEI) Blueprint family is to specify a set of open APIs for enabling Multi-Domain Inter-working across functional domains that provide Edge capabilities/applications and require close cooperation between the Mobile Edge, the Public Cloud Core and Edge, the 3rd-Party Edge functions as well as the underlying infrastructure such as Data Centers, Compute hardware and Networks. The Compute hardware is optimized and power efficient for Edge such as the Arm64 architecture.

The high-level relationships between the functional domains are shown in the figure below:

The Data Center Facility (DCF) Domain. The DCF Domain includes Data Center physical facilities that provide the physical location and the power/space infrastructure for other domains and their respective functions.

The Interconnection of Core and Edge (ICE) Domain. The ICE Domain includes the physical and logical interconnection and networking capabilities that provide connectivity between other domains and their respective functions.

The Mobile Network Operator (MNO) Domain. The MNO Domain contains all Access and Core Network Functions necessary for signaling and user plane capabilities to allow for mobile device connectivity.

The Public Cloud Core (PCC) Domain. The PCC Domain includes all IaaS/PaaS functions that are provided by the Public Clouds to their customers.

The Public Cloud Edge (PCE) Domain. The PCE Domain includes the PCC Domain functions that are instantiated in the DCF Domain locations that are positioned closer (in terms of geographical proximity) to the functions of the MNO Domain.

The 3rd party Edge (3PE) Domain. The 3PE domain is in principle similar to the PCE Domain, with a distinction that the 3PE functions may be provided by 3rd parties (with respect to the MNOs and Public Clouds) as instances of Edge Computing resources/applications.

Architecture

The PCEI Reference Architecture and the Interface Reference Points (IRP) are shown in the figure below. For the full description of the PCEI Reference Architecture please refer to the PCEI Architecture Document.

Use Cases

The PCEI working group identified the following use cases and capabilities for Blueprint development:

  1. Traffic Steering/UPF Distribution/Shunting capability — distributing User Plane Functions in the appropriate Data Center Facilities on qualified compute hardware for routing the traffic to desired applications and network/processing functions/applications.
  2. Local Break-Out (LBO) – Examples: video traffic offload, low latency services, roaming optimization.
  3. Location Services — location of a specific UE, or identification of UEs within a geographical area, facilitation of server-side application workload distribution based on UE and infrastructure resource location.
  4. QoS acceleration/extension – provide low latency, high throughput for Edge applications. Example: provide continuity for QoS provisioned for subscribers in the MNO domain, across the interconnection/networking domain for end-to-end QoS functionality.
  5. Network Slicing provisioning and management – providing continuity for network slices instantiated in the MNO domain, across the Public Cloud Core/Edge as well as the 3Rd-Party Edge domains, offering dedicated resources specifically tailored for application and functional needs (e.g. security) needs.
  6. Mobile Hybrid/Multi-Cloud Access – provide multi-MNO, multi-Cloud, multi-MEC access for mobile devices (including IoT) and Edge services/applications
  7. Enterprise Wireless WAN access – provide high-speed Fixed Wireless Access to enterprises with the ability to interconnect to Public Cloud and 3rd-Party Edge Functions, including the Network Functions such as SD-WAN.
  8. Distributed Online/Cloud Gaming.
  9. Authentication – provided as service enablement (e.g., two-factor authentication) used by most OTT service providers 
  10. Security – provided as service enablement (e.g., firewall service insertion)

The initial focus of the PCEI Blueprint development will be on the following use cases:

  • User Plane Function Distribution
  • Local Break-Out of Mobile Traffic
  • Location Services

User Plane Function Distribution and Local Break-Out

The UPF Distribution use case distinguishes between two scenarios:

  • UPF Interconnection. The UPF/SPGW-U is located in the MNO network and needs to be interconnected on the N6/SGi interface to 3PE and/or PCE/PCC.
  • UPF Placement. The MNO wants to instantiate a UPF/SPGW-U in a location that is different from their network (e.g. Customer Premises, 3rd Party Data Center)

UPF Interconnection Scenario

UPF Placement Scenario

UPF Placement, Interconnection and Local Break-Out Examples

Location Services (LS)

This use case targets obtaining geographic location of a specific UE provided by the 4G/5G network, identification of UEs within a geographical area as well as facilitation of server-side application workload distribution based on UE and infrastructure resource location.

 

Acknowledgements

Project Technical Lead: Oleg Berzin

Committers: Suzy GuTina Tsou Wei Chen, Changming Bai, Alibaba; Jian Li, Kandan Kathirvel, Dan Druta, Gao Chen, Deepak Kataria, David Plunkett, Cindy Xing

Contributors: Arif , Jane Shen, Jeff Brower, Suresh Krishnan, Kaloom, Frank Wang, Ampere

LF Edge Member Spotlight: HPE

By Akraino, Akraino Edge Stack, Blog, Member Spotlight

The LF Edge community is represents a diverse set of member companies and people that represent the IoT, Enterprise, Cloud and Telco Edge. The Member Spotlight blog series highlights these members and how they are contributing to and leveraging open source edge solutions. Today, we sat down with Rohit Arora, Enterprise Architect at Hewlett Packard Enterprise (HPE) to discuss the importance of open source, leading Multi Access Edge Computing (MEC) initiatives, participating in the Technical Advisory Committee (TAC) and collaborating with the LF Edge ecosystem.

Can you tell us a little about your organization?

HPE is a global, edge-to-cloud Platform-as-a-Service company. HPE solutions connect, protect, analyze, and act on data and applications wherever they live, from edge to cloud, so insights can be turned into outcomes at the speed required to thrive in today’s complex world.

Why is your organization adopting an open source approach?

We at HPE believe in innovation and open source encourages innovation by bringing communities together to build common platform. HPE has been involved in various open source projects.

Why did you join LF Edge and what sort of impact do you think LF Edge has on the edge, networking, and IoT industries?

We joined LF edge because it aligns with HPE’s direction of edge to cloud. Edge computing is creating a major transformation in most industries and we believe initiatives driven by LF edge are critical for this digital transformation

What do you see as the top benefits of being part of the LF Edge community?

There are many benefits of being part of LF edge but we believe the biggest is to be part of a community which is driving the innovation for the next gen networks at the edge.

What sort of contributions has your team made to the community, ecosystem through LF Edge participation?

HPE has contributions on the LF Edge Governing Board and TAC, HPE has also made some contributions to the infrastructure requirements for LF Edge. HPE is also actively involved in LF edge projects such as Akraino and process adoption.

What do you think sets LF Edge apart from other industry alliances?

There are two main reasons LF Edge is different from other industry alliances

  1. A wide set of different community members: There is a wide variety of community members in LF edge from telco services providers, NEPs to chip manufacturers. This provides different viewpoints and provides the right level of expertise that is needed.
  2. Projects execution: The community really believes in executing and we have seen some projects coming from idea to development and then testing at a very fast pace.

How will  LF Edge help your business?

HPE is leading infrastructure provider and have wide variety of solutions for the edge. We are also leading MEC (Multi Access Edge Computing) initiatives with some major telcos. By being part of LFEdge we get access to latest innovations and resources in edge computing. This can help us build our solution to fit industry needs.

What advice would you give to someone considering joining LF Edge?

There are so many projects LF Edge is driving, the best place to start would be to pick a project which aligns with your company’s directions and see how you can drive innovation with your contributions for the project. There are many resources available and all the community members are very helpful to provide any info you need.

To find out more about LF Edge members or how to join, click here.

Additionally, if you have questions or comments, visit the  LF Edge Slack to share your thoughts and engage with community members. 

 

Akraino’s AI Edge-School/Education Video Security Monitoring Blueprint

By Akraino, Akraino Edge Stack, Blog, Use Cases

Written by Hechun Zhang, Staff Systems Engineer, Baidu; Akraino TSC member, and PTL of the AI Edge Blueprint; and Tina Tsou, Enterprise Architect, Arm and Akraino TSC Co-Chair

In order to support end-to-end edge solutions from the Akraino community, Akraino uses blueprint concepts to address specific Edge use cases. A Blueprint is a declarative configuration of the entire stack i.e., edge platform that can support edge workloads and edge APIs. In order to address specific use cases, a reference architecture is developed by the community.

The School/Education Video Security Monitoring Blueprint belongs to the AI Edge Blueprint family. It focuses on establishing an open source MEC platform that combined with AI capacities at the Edge. In this blueprint, latest technologies and frameworks like micro-service framework, Kata container, 5G accelerating, and open API have been integrated to build a industry-leading edge cloud architecture that could provide comprehensive computing acceleration support at the edge. And with this MEC platform, Baidu has expanded AI implementation across products and services to improve safety and engagement in places such as factories, industrial parks, catering services, and classrooms that rely on AI-assisted surveillance.

Value Proposition

  • Establish an open-source edge infrastructure on which each member company can develop its own AI applications, e.g. video security monitoring.
  • Contribute use cases which help customers adopt video security monitoring, AI city, 5G V2X, and Industrial Internet applications.
  • Collaborate with members who can work together to figure out the next big thing for the industry.

Use cases

Improved Student-Teacher Engagement

 

Using deep learning model training for video data from classrooms, school management can evaluate class engagement and analyze individual student concentration levels to improve real-time teaching situations.

Enhanced Factory Safety and Protection

Real-time monitoring helps detecting factory workers who might forget security gadgets, such as helmets, safety gloves, and so on, to prevent hazardous accidents in the workplace. Companies can monitor safety in a comprehensive and timely way, and used findings as a reference for strengthening safety management.

Reinforced Hygiene and Safety in Catering

Through monitoring staff behavior in the kitchen, such as smoking breaks and cell phone use, this solution ensures the safety and hygiene of the food production process.

Advanced Fire Detection and Prevention

Linked and networked smoke detectors in densely populated places, such as industrial parks and community properties, can help quickly detect and alert authorities to fire hazards and accidents.

Network Architecture

OTE-Stack is an edge computing platform for 5G and AI. By virtualization it can shield heterogeneous characteristics and gives a unified access of cloud edge, mobile edge and private edge. For AI it provides low-latency, high-reliability and cost-optimal computing support at the edge through the cluster management and intelligent scheduling of multi-tier clusters. And at the same time OTE-Stack makes device-edge-cloud collaborative computing possible.

Baidu implemented video security monitoring blueprints on the Arm infrastructure, including cloud-edge servers, hardware accelerators, and custom CPUs designed for world-class performance. Arm and Baidu are members of the Akraino project and use edge cloud reference stack of networking platforms and cloud-edge servers built on Arm Neoverse. The Arm Neoverse architecture supports a vast ecosystem of cloud-native applications and combines AI Edge blueprint for an open source mobile edge computing (MEC) platform optimized for sectors such as safety, security, and surveillance.

“Open source has now become one of the most important culture and strategies respected by global IT and Internet industries. As one of the world’s top Internet companies, Baidu has always maintained an enthusiastic attitude in open source, actively contributing the cutting edge products and technologies to the Linux foundation. Looking towards the future, Baidu will continue to adhere to the core strategy of open source and cooperate with partners to build a more open and improved ecosystem.” — Ning Liu, Director of AI Cloud Group, Baidu

In the 5G era, OTE-Stack has obvious advantages in the field of edge computing:

  • Large scale and hierarchical cluster management
  • Support third cluster
  • Lightweight cluster controller
  • Cluster autonomy
  • Automatic disaster recovery
  • Global scheduling
  • Support multi-runtimes
  • Kubernetes native support

For more information about this Akraino Blueprint, click here.  For general information about Akraino Blueprints, click here.

MicroMEC now available with the Akraino R3 Release!

By Akraino, Akraino Edge Stack, Blog

Written by Tapio Tallgren, Technical Leader at Nokia Mobile Networks, Community Sub-Committee Chair of Akraino TSC,Ferenc Szekely, Program Manager, SUSE, Committer of Micro MEC blueprint of Akraino TSC and Tina Tsou, Enterprise Architect, Arm, Akraino TSC Co-Chair

The MicroMEC platform started life as a platform to run applications at the very edge of the network, like in a light pole. We joined the LF Edge’s Akraino project from the very beginning.

To find out what the use cases would be first, we participated in the IoThon hackathon in 2019 where we built a miniature city with sensors, cameras and small servers — also known as Raspberry Pis. Our plan was that we will provide APIs to enable developers to access the sensors, cameras, or other independent hardware devices attached to our small servers, ie. the MicroMEC nodes. It was clear that we wanted to deploy all the APIs as well as the apps in containers. We needed a tool like Kubernetes to help us build and manage the MicroMEC cluster. As we targeted “small” devices, with max 4GB of RAM -at that time- and low power consumption we looked into alternatives to k8s. That is how we picked k3s. 

By the autumn of 2019 we had our lab running Raspberry Pi 3B+ and 4B nodes with k3s. We had a successful hackathon – Junction 2019 – in Finland where the teams presented solutions utilizing the MicroMEC cluster. We also added OpenFaaS Cloud (OFC) into the mix and a developer UI to the platform. This allowed developers to write serverless applications for the MicroMEC cluster and deploy them with ease. They could concentrate on their core business: developing apps while MicroMEC with OFC took away the burden of cluster management, deployment etc.

Right after Junction, we were at the Akraino 5G MEC Hackathon in the USA. For this event MicroMEC had to become more “MEC”. This implied the implementation of MEC-11 interfaces and the UI to manage those apps that our MEC-11 implementation made discoverable for customers near the MicroMEC cluster. The MEC cluster runs on Arm architecture based hardware.

With all this activity, we missed the first two Akraino releases, but now we are very happy to join the Akraino R3 release! For this, we had to figure out what is the easiest way to install the stack on the device with a MMC card. The easiest way is to not install anything on the fragile card, but boot the stack from a network server. Eventually we made all MicroMEC nodes to boot from a network server using PXE and the storage of each node was attached via iscsi. This requires a fast enough LAN, but thankfully cheap gigabit switches are widely available these days. 

Learn more about Akraino here.

 

LF Edge’s Akraino Project Release 3 Now Available, Unifying Open Source Blueprints Across MEC, AI, Cloud and Telecom Edge

By Akraino, Announcement, LF Edge

    • 6 New R3 Blueprints (total of 20)  covering use cases across Telco, Enterprise, IoT, Cloud and more
    • Akraino Blueprints cover areas including MEC, AI/ML, Cloud, Connected Vehicle, AR/VR, Android Cloud Native, smartNICs, Telco Core & Open- RAN, with — ongoing support for R1-R2 blueprints and more
    • Community delivers open edge API specifications — to standardize across devices, applications (cloud native), orchestrations,  and multi-cloud — via new white paper

SAN FRANCISCO  August 12, 2020LF Edge, an umbrella organization within the Linux Foundation that aims to establish an open, interoperable framework for edge computing independent of hardware, silicon, cloud, or operating system, today announced the availability of Akraino Release 3 (“Akraino R3”).  Akraino’s third and most mature release to date delivers fully functional edge solutions– implemented across global organizations– to enable a diversity of edge deployments across the globe. New blueprints include a focus on  MEC, AI/ML, and Cloud edge. In addition, the community authored the first iteration of a new white paper to bring common open edge API standards to align the industry.

Launched in 2018, and now a Stage 3 (or “Impact” stage) project under the LF Edge umbrella, Akraino Edge Stack delivers an open source software stack that supports a high-availability cloud stack optimized for edge computing systems and applications. Designed to improve the state of carrier edge networks, edge cloud infrastructure for enterprise edge, and over-the-top (OTT) edge, it enables flexibility to scale edge cloud services quickly, maximize applications and functions supported at the edge, and to improve the reliability of systems that must be up at all times. 

“Akraino has evolved to unify edge blueprints across use cases,” said Arpit Joshipura, general manager, Networking, Automation, Edge and IoT, the Linux Foundation. “With a growing set of blueprints that enable more and more use cases, we are seeing the power of open source impact every aspect of the edge and how the world accesses and consumes information.”  

About Akraino R3

Akraino Release 3 (R3) delivers a fully functional open source edge stack that enables a diversity of edge platforms across the globe. With R3, Akraino brings deployments and PoCs from a swath of global organizations including Aarna Networks, China Mobile, Equinix, Futurewei, Huawei, Intel, Juniper, Nokia, NVIDIA, Tencent, WeBank, WiPro, and more.

Akraino enables innovative support for new levels of flexibility that scale 5G, industrial IoT, telco, and enterprise edge cloud services quickly, by delivering community-vetted and tested edge cloud blueprints to deploy edge services.  New use cases and new and existing blueprints provide an edge stack for Connected Vehicle, AR/VR, AI at the Edge, Android Cloud Native, SmartNICs, Telco Core and Open-RAN, NFV, IOT, SD-WAN, SDN, MEC, and more. 

 Akraino R3 includes  6 new blueprints for a total of 20,  all tested and validated on real hardware labs supported by users and community members — the Akraino community has established a full-stack, automated testing with strict community standards to ensure high-quality blueprints. 

The 20 “ready and proven” blueprints include both updates and long-term support to existing R1 & R2 blueprints, and the introduction of six new blueprints:

      • The AI Edge – School/Education Video Security Monitoring 
      • 5G MEC/Slice System–  Supports Cloud Gaming, HD Video, and Live Broadcasting
      • Enterprise Applications on Lightweight 5G Telco Edge (EATLEdge)
      • Micro-MEC (Multi-access Edge Computing) for SmartCity Use Cases
      • IEC Type 3: Android Cloud Native Applications on Arm®-based  Servers on the Edge 
      • IEC Type 5: Smart NIC: Edge hardware acceleration 

More information on Akraino R3, including links to documentation, code, installation docs for all Akraino Blueprints from R1-R3, can be found here. For details on how to get involved with LF Edge and its projects, visit https://www.lfedge.org/

API  White Paper

The Akraino community published the first iteration of a  new white paper to bring common open edge API standards to the industry. The new white paper makes available, for the first time, generic edge APIs for developers to standardize across devices, applications (cloud native), orchestrations,  and multi-cloud. The paper serves as a stepping stone for broad industry alignment on edge definitions, use cases, APIs. Download the paper here: https://www.lfedge.org/wp-content/uploads/2020/06/Akraino_Whitepaper.pdf

Looking Ahead

The community is already planning R4, which will include more implementation of open edge API guidelines, more automation of testing, increased alliance with upstream and downstream communities, and development of public cloud standard edge interfaces. Additionally, the community is expecting new blueprints as well as additional enhancements to existing blueprints. 

Don’t miss the Open Networking and Edge Summit (ONES) virtual event happening September 28-29, where Akraino and other LF Edge communities will collaborate on the latest open source edge developments. Registration is now open!

Ecosystem Support for Akraino R3

Arm
“The demands on compute, networking, and storage infrastructure are changing significantly as we connect billions of intelligent devices, many of which live at the edge of the 5G network,” said Kevin Ryan, senior director of software ecosystem development, Infrastructure Line of Business, Arm. “By working closely with the Akraino community on the release of Akraino R3, and through our efforts with Project Cassini for seamless cloud-native deployments, Arm remains committed to providing our partners with full- edge solutions primed to take on the 5G era.”

AT&T 
Mazin Gilbert, VP of Technology and Innovation, AT&T, said: “As a founding member of the Akraino platform, AT&T has seen first-hand the remarkable progress as a result of openness and industry collaboration. AI and edge computing are essential when it comes to creating an intelligent, autonomous 5G network, and we’re proud to work together with the community to deliver the best possible solutions for our customers.”

Baidu
In the 5G era, AI+ Edge Computing is not only an important guarantee for updating the consumer and industrial Internet experience (such as video consumption re-upgrading, scene-based AI capabilities, etc.), but also a necessary infrastructure for the development of the Internet industry,” said Ning Liu, Director of AI Cloud Group, Baidu. “Providing users with AI-capable edge computing platforms, products and services is one of Baidu’s core strategies. Looking towards the future, Baidu will continue to adhere to the core strategy of open source and cooperate with partners to build a more open and improved ecosystem.” 

China Unicom
“Commercial 5G is going live around the world. Edge computing will play an important role for large bandwidth and low delay services in the 5G era. The key to the success of edge computing is to provide integrated ICT PaaS capabilities, which is beneficial for the collaboration between networks and services, maximizing the value of 5G,” said Xiongyan Tang, Chief Scientist and CTO of the Network Technology Research Institute of China Unicom. “The PCEI Blueprint will define a set of open and common APIs, to promote the deep cooperation between operators and OTTs, and help to build a unified network edge ecosystem.”  

Huawei 
“High bandwidth, low latency, and massive connections are 5G typical features. Based on MEC’s edge computing and open capabilities, 5G network could build the connection, computing, and capabilities required by vertical industries and enables many applications. In the future, 5G MEC will be an open system that provides an application platform with rich atomic capabilities,” said by Bill Ren, Huawei Chief Open Source Liaison Officer. “Managing a large number of applications and devices on the MEC brings great challenges and increases learning costs for developers. We hope to make 5G available through open source, so that more industry partners and developers can easily develop and invoke 5G capabilities. Build a common foundation for carriers’ MEC through open source to ensure the consistency of open interfaces and models. Only in this way can 5G MEC bring tangible benefits to developers and users.”

Juniper Networks
“Juniper Networks is proud to have been an early member of the Akraino community and supportive of this important work. We congratulate this community for introducing new blueprints to expand the use cases for managed edge cloud with this successful third release,” said Raj Yavatkar, Chief Technology Officer at Juniper Networks. “Juniper is actively involved in the integration of multiple blueprints and we look forward to applying these solutions to evolve edge cloud and 5G private networks to spur new service innovations – from content streaming to autonomous vehicles.”

Tencent
“The new generation network is coming, IoT and Edge Computing are developing rapidly. At the same time, it also brings great challenges to technological innovation. High performance, low latency, high scalability, large-scale architecture is a must for all applications. TARS has released the latest version to meet the adjustment of 5G and Edge Computing. Massive devices can easily use TARS Microservice Architecture to realize the innovation of edge applications. The Connect Vehicle Blueprint and AR/VR Blueprint in Akraino are all using the TARS Architecture,” said Mark Shan, Chairman of Tencent Open Source Alliance, Chairman of TARS Foundation, and Akraino TSC Member. “The blueprints on the TARS Architecture solve the problem of high throughput and low latency. TARS is a neutral project in the Linux Foundation, which can be easily used and helped by anyone from the open-source community.”

Zenlayer
“We are proud to be part of the Edge Cloud community. Zenlayer is actively exploring edge solutions and integrating the solutions to our bare metal product. We hope the edge products will empower rapid customer innovation in video streaming, gaming, enterprise applications and more,” said Jim XU, chief engineering architect of Zenlayer.

About the Linux Foundation
Founded in 2000, the Linux Foundation is supported by more than 1,000 members and is the world’s leading home for collaboration on open source software, open standards, open data, and open hardware. Linux Foundation’s projects are critical to the world’s infrastructure including Linux, Kubernetes, Node.js, and more.  The Linux Foundation’s methodology focuses on leveraging best practices and addressing the needs of contributors, users and solution providers to create sustainable models for open collaboration. For more information, please visit us at linuxfoundation.org.

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