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Akraino Edge Stack

LF Edge Member Spotlight: Altran

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

The LF Edge community is comprised of a diverse set of member companies 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 Shamik Mishra, Vice President, Research and Innovation of Altran, to discuss the importance of open source software, collaborating with industry leaders in edge computing, security, how they contribute to the Akraino Edge Stack project and the impact of being a part of the LF Edge ecosystem.

Can you tell us a little about your organization?

Altran is a world leader in engineering and R&D services. The Group offers a unique value proposition that helps customers meet their transformation and innovation challenges. Altran supports its customers, from concept to industrialization, to develop the products and services of tomorrow. Altran has been working for more than 35 years with major players in many sectors: Automotive, Aeronautics, Space, Defense & Naval, Rail, Infrastructure & Transport, Industry & Consumer Products, Life Sciences, Communications, Semiconductor & Electronics, Software & Internet, Finance & Public Sector. In 2019, Capgemini, and Altran announced a merger project in the context of a friendly tender offer to create a global leader in Intelligent Industry. Altran generated 3.2 billion in revenue in 2019, with more than 50,000 employees in more than 30 countries.

Why is your organization adopting an open source approach?

Open Source Software has revolutionized the technology industry globally in more ways than one. It has significantly shortened software/product development cycles, spurred innovation and boosted entrepreneurship. Licenses come free of cost, with the expenses typically being for deploying, hardening, supporting, customizing, and maintaining the software. Businesses have the flexibility of choosing and customizing the best solutions for their needs. At Altran, we help our clients lead into the future by solving their most complex engineering and R&D problems through specialized solutions. We see open source software as an opportunity to differentiate our offerings by accelerating development of such solutions for our clients. This provides them the required flexibility of choice and a way to optimize costs for creating value towards their clients.

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

Altran envisioned the significant role and impact of Edge Computing early in its evolution cycle. However, one of the key challenges is that different organizations in the industry perceive Edge Computing differently based on the nature of their business or pursuit. LF Edge is an umbrella organization that is agnostic of hardware, silicon, cloud and OS. This helps the industry leaders arrive at a common understanding of Edge Computing and create an open and standard framework for the technology. We believe LF Edge can decisively reduce the semantic dissonance on Edge Computing in the industry and help businesses work together to accelerate innovation.

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

 LF Edge community has industry leading organizations as members who specialize in large-scale hardware manufacturing (chip, mobile devices, network equipment etc.), software product development, operating systems, engineering services, telecom services, cloud solutions and more. This diversity helps set a broad framework for Edge Computing by considering various concerns and scenarios relevant to the member domains. Since the framework will be open source, it strengthens its credibility and will likely be adopted widely in the industry. Altran being a world leader in engineering and R&D services, believes the LF Edge forum presents a unique opportunity to engage with the community and contribute to the open source Edge Computing framework. Based on our early start in this space, the exposure to experts on the LF Edge forum helps us to benefit from the views and propositions of diverse organizations to validate and strengthen our service offerings and competencies in Edge Computing.

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

Altran aims to play a leading role in the Edge Computing ecosystem by contributing some of its software and solution breakthroughs to the open community, including (but not limited to) contributions to compute frameworks, APIs, management plane and use cases. Altran is currently actively pursuing the Akraino project particularly on security aspects. Other interest areas are device edge and intelligent application development leveraging the LF edge projects.

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

Three key features set LF Edge apart from other industry alliances and are likely to make it successful: 1. The diversity of members. The community has members ranging across multiple domains such as Chip, Mobile, Network Equipment Manufacturing, software product development, telecom service providers, cloud service providers, engineering service providers etc. The diversity is also geographical. It includes organizations that are across various geos, thereby helping to absorb wide range of views and concerns for the community. With so much diversity the framework is inclined to remain neutral and is unlikely to be driven by the interests of a few members in the community. 2. The timing of the alliance Edge Compute, in its evolution, is currently at a point, where it is possible for the industry to come together and define a framework and standards that can be eventually adopted by various players and can be evolved and customized. Unlike other alliances, the timing of this alliance helps it to be more successful. 3. The framework is open source and the projects onboarded are also open source. This makes it easy to accelerate the innovation in this space. The community also draws strength from the support of Linux Foundation.

How will  LF Edge help your business?

Altran’s vision for Multi-Access Edge Computing (MEC) is to create a developer-centric architecture and cloud-native platform that will make Edge discovery, onboarding and management of applications easy and seamless for Edge application developers. The Altran Ensconce platform brings together multiple capabilities, accelerators and frameworks that enables rapid development of Multi-Access Edge Compute (MEC) solutions. Being part of LF Edge, we see an opportunity to further evolve our MEC solutions, working with the LF Edge alliance on the open source framework for Edge Computing. We believe that our clients can benefit from this approach by quick adoption of our solutions and be ahead in their businesses. We also believe that there is a unique opportunity for us to contribute to the community from our experience.

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

LF Edge is a great opportunity for various organizations in the industry that are interested in collaborating with other industry leaders to drive innovation in Edge Computing and mutually benefit from the ecosystem. Organizations can shape the future of Edge Computing by joining this alliance early in the innovation cycle.

To learn more about Akraino Edge Stack, click here. To find out more about our members or how to join LF Edge, 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 Edge Stack Use Cases: Tencent’s End User Story

By Akraino Edge Stack, Blog

Written by Tencent’s xin qiu  and Mark Shan, active members of the Akraino technical community

Akraino, a project creating an open source software stack that supports high-availability cloud services optimized for edge computing systems and applications, has created blueprints to support a variety of edge use cases. The Akraino community tests and validates the blueprints on real hardware labs supported by users and community members. Below is a description of several validated blueprints by LF Edge member Tencent.

Tencent has been deploying Tars on Connected Vehicle Blueprint and validating on IEC Type 4: AR/VR oriented Edge Stack for Integrated Edge Cloud (IEC) Blueprint Family.

Tars Microservice Framework

Tars is a key component for Connected Vehicle Blueprint and IEC Type 4 AR/VR Blueprint.  So we introduce Tars Framework first prior to diving into the Akraino Blueprint. Tars is a high-performance microservice framework, which supports C++, Java, Nodejs as well as PHP for now. Tars framework offers a set of efficient solutions for development, test, and maintenance. Tars framework integrates extensible components for encoding/decoding, high-performance RPC protocol, name service, monitor, statistics and configuration.  Tars framework will be a great help for reliable distributed application development.

Tars framework has been used in Tencent since 2008. Nowadays it has already been used by hundreds of applications in Tencent, services developed on the Tars Framework run on 16 000 machines. The applications include but not limited to social networks, gaming, video,  financial, telecom, education. 

Tars architecture

The following picture depicts Tars’ architecture.  Tars can be deployed in multiple environments, including bare metal,  virtual machines as well as the container.

In terms of RPC, Tars supports Tars, Protocol Buffer, TUP, SSL, HTTP1/2. The customers can select any RPC protocol based on the application’s requirement.

Beyond  RPC call, Tars supports multiple languages and microservice governance functions, including Service Register/Discovery, Load Balance, Area Perception, Flow Control, Set Mode, Tracing and so on.

Tars Optimization for edge

To address the requirements of time-critical Application on the edge, some optimizations are itemized below:

  • High-Performance RPC:   Tars Framework supports a high-performance RPC Protocol, called Tars Protocol.   To improve the performance, the Tars protocol re-design a brand new RPC protocol and make the transfer between “request” and “Binary stream” more efficiently. In terms of the detail of Tars protocol, refer to the Tars.h file in the https://github.com/TarsCloud/Tars.
  • Lightweight framework
    1. To make Tars can be well deployed on the edge computing platform, we make the framework pluggable. The customer plugin the pluggable components when we really need it. Unnecessary components can be avoided.
    2. Rewrite some functions(like scale-out, monitor and so on) to reduce CPU consumption.
    3. Orchestrate no-urgent functions(like monitor data calculation and so on) from edge to DC(or higher level edge). Reduce resource consumption.

For more detail information for Tars, refer to https://github.com/TarsCloud/Tars/blob/master/Introduction.md.

Connect Vehicle Blueprint

For Connected Vehicle Blueprint,Connected Vehicle Blueprint focuses on establishing an open-source MEC platform, which is the backbone for the V2X application.

Sponsor Companies

Tencent, Arm, Intel, Nokia

Value Proposition

  • Establish an open-source edge MEC platform on which each member company can develop its own v2x application.
  • Contribute some use cases which help customers adopt V2X applications.
  • Find some members who can work together to figure out something big for the industry.

Use Cases

From the use case perspective,  the following are the potential use cases. More is possible in the future.

  • Accurate Location: Accuracy of location improved by over 10 times than today’s GPS system. Today’s GPS system is around 5-10 meters away from your reallocation, <1 meter is possible with the help of Connected Vehicle Blueprint.
  • Smarter Navigation: Real-time traffic information update, reduce the latency from minutes to seconds, figure out the most efficient way for drivers.
  • Safe Drive Improvement: Figure out the potential risks which can NOT be seen by the driver.
  • Reduce traffic violation: Let the driver understand the traffic rules in some specific area. For instance,  change the line prior to a narrow street, avoiding the opposite way drive in the one-way road, avoiding carpool lane when a single driver and so on.

Network Architecture

From the network architecture perspective,  the blueprint can be deployed in both 4G and 5G networks. Two key points should be paid special attention to.

  1. One is offloading data to edge MEC platform.  The policy of data offload is configurable based on different applications.
  2. The other is the ability that letting the edge talks to the other edges as well as the remote data center. In some use cases, the data in one edge can NOT address the application’s requirements, we need to collect the data from different edges or send the data to the remote data center.

Screen Shot 2019-11-03 at 8.30.34 PM.png

The general data flows are itemized below:

  • Grab the traffic/vehicle information and circulate the information to the edge;
  • Different types of information are distributed to the corresponding application based on the configurable policy;
  • The corresponding edge applications process the information in a very fast speed and figure out the suggested action items for drivers;
  • The suggested action items are sent back to the driver via the network.

MEC Development Architecture

From the MEC deployment perspective,  the blueprint consists of three layers.

  • IaaS Layer     Connected Vehicle Blueprint can be deployed on community hardware, virtual machine as well as the container.   Both the Arm and x86 platforms are BOTH well supported.
  • PaaS Layer   Tars is the microservice framework of Connected Vehicle Blueprint. Tars can provide high-performance RPC calls, deploy microservice in larger scale-out scenarios efficiently, provide easy-to-use service management features.
  • SaaS Layer   The latest v2x application depicted in the foregoing use case perspective.

For more information about Connected Vehicle Blueprint,  please refer to:

Connected Vehicle Blueprint(Aka CVB)

Release 2 Documents

Slide Deck

IEC Type 4: AR/VR oriented Edge Stack for Integrated Edge Cloud(IEC) Blueprint Family

Integrated Edge Cloud(IEC) is an Akraino approved blueprint family and part of Akraino Edge Stack, which intends to develop a fully integrated edge infrastructure solution, and the project is completely focused on Edge Computing. This open-source software stack provides critical infrastructure to enable high performance, reduce latency, improve availability, lower operational overhead, provide scalability, address security needs, and improve fault management. The IEC project will address multiple edge use cases and industry, not just the Telco Industry. IEC intends to develop solution and support of carrier, provider, and the IoT networks.

IEC Type 4 is focused on AR VR applications on the edge.  In general, the architecture consists of three layers:  Iaas(IEC Type2), PaaS(Tars), SaaS(AR/VR Application).

Sponsor Companies

Tencent, Arm, HTC, IBM, MobiledgeX, Visby, UC Irvine, Juniper, PSU, Orange

Value Proposition

  • Establish an open-source edge infrastructure on which each member company can develop its own AR/VR application.
  • Contribute some use cases which help customers adopt ARVR applications.
  • Find some members who can work together to figure out something big for the industry.

Use Cases

The combination of IEC Type2 and Tars provides high performance and high availability infrastructure for AR/VR applications. The AR/VR application includes but not limited to operation guidance, virtual classroom, sports live, gaming as so on.

For Release 2, we focus on building the infrastructure and virtual classroom application (Highlighted in dark purple color). Virtual Classroom is a basic app that allows you to live a virtual reality experience simulating a classroom with teachers and students.

UseCases Value Proposition
Operation Guidance ​ Predict the next step for the operations(like assembling Lego blocks, cooking sandwiches, etc) and help people to achieve a goal.
Virtual Classroom  Simulating a virtual classroom,  ​which improves online education experiences for the teachers and students.
Sports Live Augment and simulate the sports live, which gives the audiences an amazing immersive watching experience.  ​
Gaming Augment and simulate the game scenario, let players enjoy an immersive game world.  ​

Architecture

The whole architecture, shown below, consists of two parts: the front end and the backend.

  • For the front end, the minimal requirements are two clients, one for the teacher and the other one for the student. The client device could be a cellphone, tablets, wearable devices,personal computers, etc.  The client collects information from the real world and transfers the data to the backend for calculation. Beyond data transfer and calculation, render is another function running on the front end client-side.
  • For the backend, we deploy the backend in two virtual machines in the Cloud.
    1. To make the VR backend work well, we deploy IEC in the IaaS Layer, Tars framework in PaaS Layer, Virtual Classroom Backend in SaaS Layer.
    2. To make CI/CD available, we deploy Jenkins Master in one Virtual Machine.  The Jenkins master issues command to triger the script run on the dedicated VM.

For more information about IEC Type 4,  please refer to:

Release 2 Documentation

Leader’s Statements

” Open Source is Tencent’s core strategy. Tencent, as a platinum member and board of Linux Foundation, continuously promotes network innovation from application perspectives. We believe that application-drive-network will bring tremendous benefits to our customers and stakeholders. After the Tars project in 2018 and recent Akraino blueprints, Tencent will contribute new open-source Foundation and projects in the future. Welcome more Linux member companies get involved!”

  • Xin Liu, General Manager of Future Network Lab, Tencent
“Tencent has been ready for open source and joined the Linux Foundation to become a platinum member. Tencent also donated TARS to Linux Foundation , a multilingual microservice development framework that has been used for ten years.Tars has been a mature project in Linux Foundation, and is currently providing mature infrastructure for projects in LF Edge. At present, TARS has become the unique microservice development framework in the connected vehicle and AR / VR blueprint of Akraino, improving the necessary conditions for high availability, high performance and service governance of applications. We will continue to develop the TARS project and Akraino project in edge computing. Tencent will establish an open-source foundation with more partners and contribute more projects to the open-source industry in the future. Welcome to join us! ”
  • Mark Shan, Project consultant of Tencent Technical Committee, Akraino TSC member

*******************************

Guoxu Liu, Tencent

In Tencent buildings in Shenzhen, ELIOT AIoT in Smart Office Blueprint has been deployed. The development of this blueprint helps enterprises  increasing  the efficiency of management and decrease the overall cost of managing offices and meeting rooms. At the same, employees can reserve and use meeting rooms more easily and conveniently.

Recently, Tencent is planning to deploy this blueprint in Beijing, Shanghai, Guangzhou,  and many other cities in China.

For more information about the Akraino blueprints or end user case stories, please visit the wiki: https://wiki.akraino.org. Additionally, if you have questions or comments, visit the  LF Edge Slack Channel and share your thoughts in the #community or #akraino channels.

LF Edge Member Spotlight: Netsia

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

The LF Edge community is comprised of a diverse set of member companies 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 Madhu Kashyap, Director of Product Management for Netsia, to discuss the importance of a open source, their infrastructure and need for communication at the edge, how they contribute to the Akraino Edge Stack project and the impact of being a member of the LF Edge community.

Can you tell us a little about your organization?

Netsia develops fixed broadband and wireless solutions for the telecom industry. Netsia’s vision is to provide a shared infrastructure for fixed mobile convergence at the edge.  

Netsia’s SEBA (Software-Enabled Broadband Access) solution transforms the traditional Passive Optical Network (PON) used in fixed access networks (FTTx) through an open, programmable, cloud-native, vendor agnostic future-proof platform, that is based on Cloudification, Virtualization, Software Defined Networking (SDN) and Network Functions Virtualization (NFV). It leverages network disaggregation, open source software and white box economies at the network edge.

Why is your organization adopting an open source approach?

Netsia is an active participant in open source communities and standards bodies and provides enriched telco-grade distributions of open source platforms in a continuous manner with long term support.

Communication Service Providers (CSPs), both fixed and mobile, are looking to transform their PoPs (Point of Presence) / Central Offices (COs) as edge clouds. The current architecture is rigid, closed, monolithic and purpose-built leading to high CAPEX and OPEX due to vendor lock-in. CSPs want to use virtualization, cloudification, SDN, NFV technologies by leveraging open source software and disaggregated white boxes.

Open source software helps Netsia to gather CSPs’ requirements and share the cost of development with the community. Netsia adds value by hardening and productizing open source.

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

Netsia is focused on the Edge. CSPs are looking to consolidate various access network technologies to a common management platform that includes SDN controller, orchestration, VIM etc.  while addressing the latency and bandwidth demands of 5G networks.

The LF Edge community provides the industry with a solid foundation for managing the edge with its development of blueprints across different domains and shaping the future of edge networking and IoT.

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

LF Edge provides a dedicated forum of like-minded organizations be it operators or vendors who believe in openness through design, architecture, APIs or code to drive  edge transformation. By participating in LF Edge, Netsia stands to gain from the collective innovation that drives the industry forward. With a community like this the whole is greater than the sum of the parts and organizations can benefit greatly from the different perspectives and ideas that are generated in the course of project planning, design and implementation. 

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

Netsia is actively involved in the Akraino project and the SEBA Blueprint.

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

 Being part of the LF umbrella opens many doors and adds significant heft to initiatives that are taken seriously by the industry. Harmonization with other open source communities and working with upstream projects LF Edge makes sure there is no duplication and overlap of effort.

How will  LF Edge help your business?

As LF Edge blueprints get adopted by industry it helps Netsia by differentiating itself in a highly competitive field. LF Edge provides the name recognition and brand that is recognized in the industry as innovating with cutting edge technology.

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

Netsia would definitely encourage and advocate for anyone considering LF Edge membership. The level of commitment by the community is unparalleled and provides high visibility to member organizations through events and other marketing activities.

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

Additionally, if you have questions or comments, visit the  LF Edge Slack Channel and share your thoughts in the #community or #akraino channels. 

Akraino Edge Stack Use Cases: Baidu’s End User Story

By Akraino Edge Stack, Blog

Written by Baidu representatives who actively participate in Akraino’s TSC

Edge scenarios are very important commercial scenarios for AI applications. There are many type of hardware, OSes, etc. It is hard for AI application providers to adapt their products to all these edge components. Fortunately, the Akraino community and LF Edge member companies can help to do the validation/development or to support their products. The AI application providers need to state their requirements or cooperate with member companies in their Blueprint validation/integration labs. In this way, the AI application providers  are more likely to find potential partners and potential commercial market.

The AI Edge Blueprint Family

LF Edge member Baidu has deployed School/Education Video Security Monitoring blueprint. With this blueprint, teachers and school authorities could conduct a full evaluation of the overall class and the concentration of individual students, helping to fully understand the real time teaching situation. According to the concentration data of each course, teachers and school authorities can conduct knowledge test and strengthen. And the School/Education Video Security Monitoring blueprint has been deployed in Beijing, Shanghai, Hangzhou(Zhejiang Province), and many other cities in China.

The AI Edge Blueprint mainly focuses on establishing an open source MEC platform combined with AI capacities at the Edge, which could be used for safety, security, and surveillance sectors. Currently it has been highly supported by partners like Arm and Intel. And both Arm and Intel infrastructures, such as Servers and GPU cards,  have been implemented in respective scenarios.

A picture of the architecture

The AI Edge: RoboTaxi blueprint proposal has been deployed in Changsha, Hunan province, China. Commercial code is being run. The community version of code will be available in Q1 of 2020.

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

Akraino 5G MEC Hackathon: Winners, Insights and More

By Akraino Edge Stack, Blog

Written byy Suzy Gu, CMTI 5G ICSV; Tina Tsou, Arm; Nitish Nagesh, UCSD; Guoxi Wang, UCI; Jerry Lin, Columbia University; Kangxian Xie, UCSD; Alex Reznik, ETSI

A few months ago, more than 76 developers gathered to participate in the Akraino 5G MEC Hackathon, sponsored by LF Edge, China Mobile Technology, ETSI and ETSI MEC. Attendees participated in-person at the Qualcomm campus in San Diego, a breakout venue in Columbia University and virtually via Zoom conference.

Different blueprints and solutions will be worked through in real time, including: Micro-MEC, AR/VR, 5G MEC edge stack accelerated with SmartNICs, and more. For the hackathon competition, we also featured a top prize of  $1000 and $500 for the runner-up teams. Please read on below for feedback from participants and details for the winning teams – Team Planet (1st), Team BlueHat (2nd), Team Blaz3r (3rd) and Team grind (3rd-tie).

“It was a day trip to San Diego to attend the Akraino 5G MEC Hackathon. I was excited when I entered the conference room in Qualcomm campus. Honestly, I never expected so many people. There were people from all over the world gathered in the room, which made it look and feel crowded in a good way with lots of enthusiasm radiating from everyone. What made me more surprised is that I saw a lot of college students. As an open-source project and cutting -edge (oh yes, edge!) technology, we really need the fresh blood! These students really have a lot of good ideas of how to prosper our edge computing platform, surveillance, IoT automotive, they bring creative and inspiring scenarios to the popular applications cases for MEC. Also, the hackathon is a good platform for people in the industry to change ideas on edge, I know a lot of people and companies got the chance to collaborate through this event. As a sponsor, CMTI (China Mobile Technology USA) also get a lot of good ideas and partners. I have to say it was a wonderful day!” – Su Gu, CMTI 5G ICSV

Some highlights on the winning teams are below.

1st Prize: Team Planet

Participating in Akraino 5G MEC Hackathon is an extraordinary experience for us.

After brainstorming at the beginning, we decided on the direction of our exploration: adopting the edge computing paradigm to mitigate the privacy issue of surveillance in the smart city. The foundation of smart city applications is the enormous amount of data collected from physical space. However, pervasive sensing also raises privacy concerns as the collected data may be highly sensitive. Even worse, the massive adoption of cloud computing in smart city applications makes sensitive data generally processed by the untrusted service provider on untrusted infrastructure. We argue that edge computing is capable of mitigating existing privacy issues as it could provide a different trust model to the smart city applications.

To instantiate our thought, we designed the driven scenario as a privacy-preserving video surveillance application in a meeting room. Video surveillance is commonly used in mission-critical spaces for security and safety purposes, like theft protection, environmental safety monitoring, and emergency response. However, on the other hand, video footage of public physical space is also highly sensitive. Residents are usually reluctant to let the video footage be reviewed or stored unless there is a real emergency or anomaly. So we designed our application, which first sends captured video to trust edge infrastructure to detect if there is an abnormal situation. Only the photos reflect the anomaly will be shared with the space manager on the cloud and be stored. In our proof-of-concept prototype, we define the abnormal condition as higher-than-expected occupancy in a room.

To implement the prototype, we leveraged the edge computing platform provided by MobiledgeX. It gives us a convenient way to deploy a containerized application to an edge infrastructure nearby. We deployed an open-source face recognition at the edge. We then implemented a Python program on a laptop to make it function as a video surveillance camera by using its webcam. The laptop keeps capturing the pictures, sending them to the edge, and calling the face detection algorithm to count the people in the room. If the occupancy is higher than a certain threshold, the image is sent to the cloud and stored. Otherwise, the program drops the image to protect residents’ privacy.

During the final review and judging phase, judges and audiences gave a lot of helpful comments and feedback. We together discussed topics like the scenarios that edge infrastructure is trusted, the capability of enhancing this application using trusted hardware, and how to extend this use case to other situations like controlling the activation of voice assistants.

In this hackathon, we not only learned more knowledge about edge computing but also got hands-on experience on real-world edge computing platforms and opportunities to build connections to the open-source community. Thank you, Akraino, for hosting this fantastic hackathon event. Thank you, Vikram and Bruce from MobiledgeX, for providing the edge computing platform and all the kind supports. Finally, a big thank you to everyone in this hackathon, for sharing your brilliant ideas and insights. We hope there will be more events like Akraino 5G MEC Hackathon that provides students opportunities to learn more about critical and cutting-edge technologies.

2nd Prize: Team BlueHat

When four of us read through the hackathon prompt, we thought to ourselves: how could we leverage a smart city’s sensor network to produce real impact? Our experience living in the city drew our attention to city traffic: very often we see an emergency vehicle, such as a fire truck and an ambulance, getting stuck at a red light behind a long line of cars. If the line was short, cars in front would notice the emergency vehicle behind and would actively run the red light to let the emergency vehicles pass the intersection. However, running a red light is inherently dangerous. In addition, when the line of cars becomes long under heavy traffic, the cars in front would often not be able to notice the emergency vehicles stuck way back. Therefore, we realized that an infrastructure-level solution is needed and developed Smart-city Emergency Express (S.E.E.), a traffic control system for smart cities. Using S.E.E., traffic lights can actively detect emergency on the streets and if those vehicles are found, they automatically switch to green lights for them to pass. The overall hackathon experience was exciting and fun. We have posted our code on Github. Thank you Akraino for the recognition of our work and hosting this meaningful hackathon! – Team BlueHat

3rd Prize (tie): Team TrailBlaz3r

It’s obvious that starting from years ago, the growth personal vehicles has exploded exponentially. As we progress into the future, the problem will only get worse because there are always more new cars than scraped cars. With this problem comes the challenges of parking, especially in the more densely populated area. For example, in major european, asian and north american cities, cars are all over the side of the streets and is extremely difficult to find parking. With the uprising of 5G as well as this device, we envision a situation where all the parking spots are being recorded and regulated such that you would always know, in which area of vicinity there is parking. It is applicable to mall’s parking structure. As we know, parking space indicators are individually placed for each parking spot. Therefore, it’s inefficient because of the amount of sensoring device required. With 5g technology, real-time parking availabilities are viable through prediction model and they could be sent to modile devices so that customers could have first hand information about uhe availability of parking spot. Additionally, with the upcoming of autonumous car, it would be also great for guiding cars without human onboard, to certain parking area in case there is no parking near the driver’s leaving point. These traffic/parking availability information could also be sold to data broker for specified needs.

3rd Prize (tie): Team Grind

On seeing a Facebook post about a hackathon in Qualcomm, San Diego, I was naturally inclined to attend it considering the proximity and value addition it had to offer. After treating ourselves to cookies and coffee, we began brainstorming approaches to solve a problem related to smart cities. After going through the slides and evaluating our options, we finally decided to develop an air quality analytics system. We developed a comparative model between Los Angeles and San Diego to explore possibility of location-specific alert generation system for air quality standards. We learnt the importance of edge-computing and familiarized ourselves with the latest technologies in different companies at the hackathon – Arm, China Mobile etc. I connected with wonderful people like Tina Tsou and Robert Wolff, whom I had the pleasure of meeting again at the Arm IoT Dev Summit in Mountain View, California on Dec 2-3rd, 2019. I hope to stay in touch with the community and contribute towards furthering technology on the edge. ~Nitish Nagesh, 2nd year CSE master student, UC San Diego

For more information about Akraino, visit the wiki page. Stay tuned here for more details about new hackathons and meetings for the Akraino project and other LF Edge projects!

LF Edge in 2020: Looking back and Revving forward

By Akraino Edge Stack, Baetyl, Blog, EdgeX Foundry, Fledge, Home Edge, Open Glossary of Edge Computing, Project EVE

Written by Melissa Evers-Hood, LF Edge Governing Board Chair 

Dear Community,

Happy New Year! As we kick off 2020, I wanted to send a note of thanks and recognition to each of you for a wonderful 2019, which marked several meaningful accomplishments for this organization.  LF Edge was launched in Jan 2019 with an aim to unify the edge communities across IOT, Telco, Enterprise and Cloud providing aligned open source edge frameworks for Infrastructure and Applications.

Our accomplishments include:

  • EdgeX Foundry has blossomed this year in participation, downloads, and use cases. EdgeX, as folks commonly call it, also graduated to Impact project stage and surpassed 1.5 million container downloads in 2019.
  • Akraino, which also reached Impact stage this year, is preparing for it’s second release with 5 new blueprints for R2, with updates to 9 of the existing 10 R1 blueprints already released. Most notably, its broadening its blueprint profile to include new blueprints for Connected Vehicles and AR/VR, truly becoming a viable framework across edge applications.
  • At the Growth Stage, Open Glossary provides common terminology and ecosystem mapping for the complex Edge environment. In 2019, the Glossary Project shipped 2.0 of the Glossary, which was integrated into the 2020 State of the Edge Report. The Glossary Project began the process of helping to standardize terminology across all LF Edge projects, and also launched the LF Edge Landscape Project: https://landscape.lfedge.org/.
  • Also at the Growth Stage, Project Eve allows cloud-native development practices in IOT and edge applications. EVE’s most recent release, 4.5.1 (which was gifted on December 25, 2019), provides a brand new initramfs based installer, ACRN tech preview, and ARM/HiKey support.
  • The Home Edge project, targeted to enable a home edge computing framework, announced their Baobab release in November. The Home Edge Project has initiated cross-project collaboration with EdgeX Foundry (secure data storage) and Project EVE (containerized OS).
  • We also added 2 additional projects this year.
    • Baetyl which provides an open source edge computing platform.
    • Fledge which is an open source framework and community for the industrial edge focused on critical operations, predictive maintenance, situational awareness and safety. Fledge has recently begun cross-project collaboration with Project EVE and Akraino, with more information available here.
  • Our reach has broadened with 9k articles, almost 50k new users, and 6.7M social media impressions.

I am excited about the work ahead in 2020, especially as we celebrate our one year anniversary this month. We laid the foundation last year – offered a solution to unite the various edge communities – and now, with your support and contributions, we’re ready to move to the next phase.

LF Edge is co-hosting Open Networking & Edge Summit in April and our teams are working hard on several cross-project demos and solutions. We’re planning meetups and other F2F opportunities at the show, so this conference will be a must.

Our focus as a community will be to continue to expand our developers and end users.  We will do this through having agile communities, that collaborate openly, create secure, updateable, production ready code, and work together as one. We also expect that there will be new projects to join and integrate.  As we walk into this bright future, working as a unified body will demonstrate that the fastest path to Edge products is through LF Edge.

I look forward to working with each of you in ‘20 and seeing you in Los Angeles this April at ONES!

Melissa

Working towards moving the industry forward together

By Akraino, Akraino Edge Stack, Blog

By Alex Reznik, Chair of MEC ISG, HPE Distinguished Technologist and LF Edge member

This content original ran on the ETSI blog.

Quite some time has passed since my last blog entry, and while I thought about a new blog a number of times, a good topic – i.e. one which is appropriate for discussion in a short, informal and public format – just did not seem to present itself. That’s not for the lack of interest or activity in MEC. 2019 is shaping up to be a critical year in which many operators are now public about their plans for edge computing, initial deployments are appearing and, as expected, holes in what the industry has been working on are beginning to be found (witness the much publicized and excellent Telefonica presentation at last month’s Edge Compute Congress). It’s just that it’s hard to blog about on-going work, even when it is very active, much less about internal efforts of various players in MEC. After all, what would that look like “this is hard and we are working hard on it…”

Nevertheless, the time has come. Those of you who follow my random MEC thoughts on a semi-regular basis might recall the subject of that last post ages ago (I mean in February): the need for both a vibrant Open Source community and Standards development in a space like MEC; and how the two are complimentary in that the focus is, by definition, on complimentary problems. And, if you don’t follow me religiously, here is the link: https://www.etsi.org/newsroom/blogs/entry/do-we-still-need-standards-in-the-age-of-open-source, grab a coffee, tea, a…. whatever … and read up!

In a significant way, that post was in part a response to comments and questions like: “There is a lot of confusion in the market, what’s up with ETSI and Akraino and EdgeXFoundry. You guys all seem to compete.” To that, the post provides a rather direct answer of “no we do not – we address different needs.” However, these related questions often followed: “OK, but how well DO YOU actually work together?” To date, one failing of the various players in MEC space has been the lack of a more convincing answer than “well, we all talk and we are all aware of each other.

That’s now changed in a very significant way. On the heels of a formal cooperation agreement between ETSI and LF Edge (see, e.g. https://www.linuxfoundation.org/press-release/2019/04/etsi-and-the-linux-foundation-sign-memorandum-of-understanding-enabling-industry-standards-and-open-source-collaboration/), the MEC ISG within ETSI and LF Edge’e Akraino project have been working towards moving the industry forward together. The first fruit of this labor is about to ripen – an Akraino Mini-Hackathon, endorsed by ETSI, to be held in San Diego the day before KubeCon.

This event was designed to highlight the work Akraino is doing in putting forward solutions which take advantage of ETSI’s Standards, and to allow developers an experience in developing for MEC. The most notable thing about this Hackathon is the model of cooperation – Akraino (and Open Source community) provides implementations to the industry, while the use of ETSI MEC (Standards Org.) standards ensures interoperability across other standards-compliant implementations.

So… that’s it then. We have arrived at a working, standardized solution for MEC, right??? Well, no. If you are looking for that, the mini-hackathon will sorely disappoint you. However, it is a step – an important first step in a growing cooperation between two organizations which should be, over time delivering those operational, standardized components for MEC. The work ahead of ETSI MEC and Akraino is significant, and much of it will lack opportunities for fanfare – as work in our industry often does. Still, there will be more coming from our two organization, so stay tuned…

An Akraino Developer Use Case

By Akraino, Akraino Edge Stack, Blog

Written by technical members members of the Akraino Edge Stack project including Bruce Lin, Rutgers; Robert Qiu, Tencent; Hechun Zhang, Baidu; Tina Tsou, Arm; Ciprian Barbu, Enea; Allen Chen, Tencent; Gabriel Yang, Huawei; Feng Yang, Tencent; Jeremy Liu, Tencent ; Tapio Tallgren, Nokia; Cristina Pauna, Enea

More intelligent edge nodes are deployed in 5G era. This blog shares a developer use case out of the Akraino project that the community is working on, specifically Telco  Appliance Blueprint Family, Connected Vehicle Blueprint, ELIOT: Edge Lightweight and IoT Blueprint Family, Micro-MEC, The AI Edge Blueprint Family, and 5G MEC/Slice System to Support Cloud Gaming, HD Video and Live Broadcasting Blueprint.

Telco Appliance Blueprint Family

Telco Appliance blueprint family provides a reusable set of modules that will be used to create sibling blueprints for other purpose tuned appliances.

Appliance model automates the installation, configuration and testing of:

  • Firmware and/or BIOS/UEFI
  • Base Operating System
  • Components for managing containers, performance, fault, logging, networking, CPU

The first blueprint integrated with TA is REC. Other appliances will be created by combining other applications with the same underlying components to create additional blueprints.

TA produces an ISO that, after being installed in the cluster, provides the underlying tools needed by the applications that come on top of it. The build of this ISO is automated in Akraino’s CI and it includes:

  • Build-tools: Based on OpenStack Disk Image Builder
  • Dracut: Tool for building ISO images for CentOS
  • RPM Builder: Common code for creating RPM packages
  • Specs: the build specification for each RPM package
  • Dockerfiles: the build specifications for each Docker container
  • Unit files: the systemd configuration for starting/stopping services
  • Ansible playbooks: Configuration of all the various components
  • Test automation framework

The image provides the following components, used during installation:

  • L3 Deployer: an OpenStack Ironic-based hardware manager framework
  • Hardware Detector: Used to adapt L3 deployer to specific hardware
  • North-bound REST API framework: For creating/extending blueprint APIs
  • CLI interface
  • AAA server to manage cloud infrastructure users and their roles
  • Configuration management
  • Container image registry
  • Security hardening configuration
  • A distributed lock management framework
  • Remote Installer: Docker image used by Regional Controller to launch deployer

The image provides the following components, usable by the applications:

  • CPU Pooler: Open Source Nokia project for K8s CPU management
  • DANM: Open Source Nokia project for K8s network management
  • Flannel: K8s networking component
  • Helm: K8s package manager
  • etcd: K8s distributed key-value store
  • kubedns: K8s DNS
  • Kubernetes
  • Fluentd: Logging service
  • Elasticsearch: Logging service
  • Prometheus: Performance measurement service
  • OpenStack Swift: Used for container image storage
  • Ceph: Distributed block storage
  • NTP: Network Time Protocol
  • MariaDB, Galera: Database for OpenStack components
  • RabbitMQ: Message Queue for Openstack components
  • Python Peewee: A Python ORM
  • Redis

Radio Edge Cloud (REC)

Akraino Radio Edge Cloud (REC) provides an appliance tuned to support the O-RAN Alliance and O-RAN Software Community‘s Radio Access Network Intelligent Controller (RIC) and is the first example of the Telco Appliance blueprint family.

  • RIC on Kubernetes on “bare metal” tuned for low latency round trip messaging between RIC and eNodeB/gNodeB,
  • Support for telco networking requirements such as SRIOV, dual POD interfaces, IPVLAN
  • Built from reusable components of the “Telco Appliance” blueprint family
  • Automated Continuous Deployment pipeline testing the full software stack (bottom to top, from firmware up to and including application) simultaneously on chassis based extended environmental range servers and commodity datacenter servers
  • Integrated with Regional Controller (Akraino Feature Project) for “zero touch” deployment of REC to edge sites
  • Deployable to multiple hardware models

In Akraino, the work on this blueprint will fully automate the deployment and testing on multiple hardware platforms in a Continuous Deployment system.

SDN Enabled Broadband Access (SEBA):

Here is SEBA user story.

As a Service Provider, I want to setup SEBA environment so that I can use ONF SEBA platform.

As an Administrator, I want to validate HOST OS environment so that I can install Kubernetes/SEBA.

As an Administrator, I want to validate Software environment so that I can install Kubernetes/SEBA

As an Administrator, I want to validate Virtual Machines for my Kubernetes/SEBA environment so that I can validate environment

As a Administrator, I want to validate services for my Kubernetes/SEBA environment so that validate working environment

SEBA validation on ARM – IEC Type 2

SEBA stands for SDN Enabled Broadband Access. It is an ONF/Opencord project which implements a lightweight platform, based on R-CORD. It supports a multitude of virtualized access technologies at the edge of the carrier network, including PON, G.Fast, and eventually DOCSIS and more.

SEBA is also an Akraino Blueprint, but in the context of the IEC Blueprint, the SEBA usecase is deployed and verified on an IEC Type 2 platform. IEC is also the main Akraino sub-project/blueprint which enables ARM architectures for Telco/Enterprise Edge applications.

For the purpose of validating SEBA on IEC Type 2, a SEBA compliant ARM64 lab has been setup at the Akraino Community Lab at the University of New Hampshire (UNH). The lab consists of two development PODs, using Marvel ThunderX2 networking processor equipped servers and Ampere HR330A servers.

The connectivity is provided by Edgecore 7816-64X TOR switches which fulfill the role of Fabric Switches in the SEBA Architecture.

For the validation work we have first ported and deployed BBSim on IEC for ARM64 and right now there is ongoing work for porting and verifying PONSim.

PONSim is also a central piece of SEBA-in-a-Box (SIAB) which is one of the main testing CI/CD projects in upstream Opencord Jenkins infrastructure.

There is ongoing work in Akraino IEC for replicating the SIAB setup by utilizing the same testing environments and facilities provided by Opencord.

Finally, recent collaboration with Opencord resulted in forming a Multiarch Brigade with the purpose of making SEBA seamlessly work on multiple architectures apart from the x86 servers. So far there has been some evident interest from the community and other parties for enabling multiarch support and perpetual verification in a CI/CD manner by adapting the Opencord infrastructure to support other architectures and ARM64 in particular.

Connected Vehicle Blueprint

Connected Vehicle Blueprint focuses on establishing an open source MEC platform, which is the backbone for V2X application.

From use cases perspectives,  the following are the use cases we have tested in our companies. More is possible in the future.

  • Accurate Location: Accuracy of location improved by over 10 times than today’s GPS system.Today’s GPS system is around 5-10 meters away from your reallocation, <1 meter is possible with the help of Connected Vehicle Blueprint.
  • Smarter Navigation: Real-time traffic information update, reduce the latency from minutes to seconds, figure out the most efficient way for drivers.
  • Safe Drive Improvement: Figure out the potential risks which can NOT be seen by the driver.
  • Reduce traffic violation: Let the driver understand the traffic rules in some specific area.For instance, change the line prior to narrow street, avoiding opposite way drive in the one way road, avoiding carpool lane when single driver etc.

From technology architecture perspective,  the blueprint consists of four major layers.

  • Hardware Layer: Connected Vehicle Blueprint runs on top of community hardware. Both Arm and x86 server are well supported.
  • IaaS Layer: Connected Vehicle Blueprint can be deployed in virtual environment as well.  Virtual Machine , Container as well as other IaaS mainstream software(like openstake, kubernates et al)  are supported.
  • PaaS Layer:Tars is the microservice framework of Connected Vehicle Blueprint. Tars can provide high performance RPC call, deploy microservice in larger scale-out scenario efficiently, provide easy-to-understand service monitor feature.
  • SaaS Layer: The latest v2x application depicted in upper use cases perspective.

From network architecture perspective,  the blueprint can be deployed in both 4G and 5G network. Two key points should be paid special attention to. One is offloading data to edge MEC platform.  The policy of data offload is configurable based on different applications.  The other is the ability that letting the edge talks to the other edges as well as remote data center. In some use cases, date process in one edge can NOT address the application’s requirements. We need to collect the data from different edges and figure out a “conclusion” for the application.

ELIOT: Edge Lightweight and IoT Blueprint Family

ELIOT AIoT in Smart Office Blueprint

This blueprint provides edge computing solutions for smart office scenarios. It manages intelligent devices, delivers AI training models and configures rules engine through cloud-edge  collaboration.

Services provided by cloud side:

  • Devices management
  • AI models training and deliver
  • Rules engine configuration
  • Third-party applications

Services provided by edge side:

  • Sending/Receiving devices data
  • Data analysis
  • AI models/Functions execution

Deployment environment:

  • Kubernetes
  • Container
  • VM
  • Bare Metal

Recently, we are still developing this project and Tencent will keep devoting great efforts to the research and development of this blueprint. In the near future, the project will also be open source. Any partners interested in this project are welcome to contact us and let’s work together to promote the application of edge computing in the field of smart office.

The AI Edge Blueprint Family

With this blueprint, teachers and school authorities could conduct a full evaluation of the overall class and the concentration of individual students, helping to fully understand the real time teaching situation. According to the concentration data of each course, teachers and school authorities can conduct knowledge test and strengthen.

The AI Edge Blueprint mainly focuses on establishing an open source MEC platform combined with AI capacities at the Edge, which could be used for safety, security, and surveillance sectors.

5G MEC/Slice System to Support Cloud Gaming, HD Video and Live Broadcasting Blueprint.

The purpose of the blueprint is to offer a 5G MEC networking platform to support delay sensitive, bandwidth consuming services, such as cloud gaming, HD video and live broadcasting. In addition, network slicing will be utilized to guarantee excellent user experience.

As a service provider of cloud gaming, I want to set up a computing platform to execute game rendering as well as video encoding, and deliver the compressed video to the player via a 4G/5G network.

As cloud gaming is sensitive to latency, the computing platform is required to be as close as possible to the network edge. Besides that, a mechanism to discover the service and direct players’ traffic to the platform is demanded.

To direct players’ traffic to the platform, I install an edge connector which is responsible for enabling flexible traffic offloading by interacting with EPC or 5GC, and subscribing the edge slice, which provisions a certain level of QoS between UE and edge application.

To interface with the user plane of 4G or 5G, I install an edge gateway (GW). In 5G SA, the edge GW is connected to a UPF, to manage the traffic from the mobile network. In 5G NSA or 4G, the edge GW is connected to an eNB or SGW, with an additional function of handling GTP-U, the tunneling protocol adopted by 4G and 5G.

When a player accesses a cloud gaming service hosted on the platform, the edge connector will establish an appropriate route between the mobile network and the edge GW. The compressed video and the player’s control data will be transferred between the gaming server and the user equipment, traversing the edge GW.

As a service provider of live broadcasting or HD video delivery, I want to set up a platform to transcode the video source to fit the bandwidth of the transport.

Similar to the cloud gaming use case, an edge connector is installed to direct the traffic to the computing platform, and an edge GW is installed to manage the mobile traffic and terminate GTP-U under 4G or 5G NSA. The computing platform will transfer the format of the video to be adapted to either the wireless link towards the mobile user or the transport towards the internet. The computing platform may be connected to a CDN to optimize the live broadcasting or HD video delivery.

Micro-MEC (µMEC)

 µMEC is a low-power, low-cost server at the edge of the network that supports Smart City use cases with different sensors (including cameras), is connected to Internet and telco networks, and allows third-party developers to create ETSI MEC applications to it.

So the µMEC focuses on Smart City use cases. If you had different smart sensors in a city, collecting data that is available for free, what could you make possible? That was the challenge that we gave in a developer hackathon in May. We used the Akraino uMEC platform and created a model city. Different sensors collected information and made it available through a database.

 

For the next hackathon, we want to make it very easy for developers to create applications that run on the µMEC device itself. For this, we are implementing ETSI MEC compliant interfaces and leverage the OpenFAAS serverless platform.

The µMEC platform that we are developing in Akraino will have a trusted computing stack, from trusted hardware to secure networking and signed containers.

Akraino will be hosting a MEC Hackathon on November 18 at Qualcomm. For more information or to register, visit the Akraino MEC Hackathon wiki.  For more informations about Akraino or blueprints, click here.

IoT World Today: Now a Part of LF Edge, EdgeX Foundry Gains Momentum

By Akraino, Akraino Edge Stack, EdgeX Foundry, In the News

When grappling with the enormity of IoT platforms, a sort of herd mentality has emerged, leading scores of vendors to create unique IoT platforms. But the problem is, no single IoT platform can accommodate all potential enterprise and industrial IoT use cases, according to Jason Shepherd, former chair of the EdgeX Foundry governing board. So organizations can become overwhelmed by the complexity of platform integration on the one hand or creating a platform from scratch on the other, Shepherd said. “I liken it to a riptide current. Your natural inclination is to swim into the current, but you risk drowning if you do that,” added Shepherd, who is the IoT and edge chief technology officer at Dell Technologies. “What you’re supposed to do, which is not intuitive, is to swim sideways.”

The EdgeX Foundry was created to sidestep the IoT platform battles. “While most people were trying to create their own platforms, we went open,” Shepherd said. “We swam sideways. And that’s what’s actually going to win.”

The EdgeX Foundry recently announced growing momentum with its latest release, known as “Edinburgh.” The product of a global ecosystem, Edinburgh is the latest example of the EdgeX Foundry’s open source microservices framework. The approach enables users to plug and play components from a growing number of third-party offerings.

In other LF Edge–related news, LF Edge’s Akraino Edge Stack initiative launched its first release in June to establish a framework for the 5G and IoT edge application ecosystem. Known as Akraino R1, it brings together several edge disciplines and offers deployment-ready blueprints.

Kandan Kathirvel, a director at AT&T and Akraino technical steering committee chair, invokes the early days of cloud computing to explain the mission behind the initiative. “In cloud computing, one of the pain points many users had when deploying the cloud was integrating multiple open source projects together,” Kathirvel said. “A user might need to work with hundreds of different open source communities.” And after deploying a cloud project, sometimes gaps were evident. Many organizations found themselves individually in this situation without realizing other users were essentially doing the same. “And this situation increases the cost and deployment time.”

Read more about EdgeX Foundry’s Edinburgh release and Akraino Edge Stack’s R1 release in this IoT World Today article here.