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Akraino Edge Stack

Akraino’s Debut at China Mobile’s “Innovation 2020 Cloud Technology Week”

By Akraino Edge Stack, Blog

Written by Tina Tsou, Co-Chair of the Akraino TSC, and Su Gu, Senior Researcher with China Mobile

On June 17, China Mobile Science and Technology Association held the “Innovation 2020 Cloud Technology Week” forum, which officially opened a series of cloud related activities  that included product launches, lectures, networking opportunities and more. For example, there was an announcement of “NEST+” plan geared for external industrial ecological cooperation. The event theme was innovation and celebrated the collaboration, openness, and win-win of technology companies both big and small. 

The event was attended and viewed by more than 734,000 people ranging from academicians, scholars, thought leaders and industry experts. There was a lot of buzz around the 5G development and collaboration in the  innovation, 6G frontier, artificial intelligence, Internet of Vehicles, Internet of Things, and other fields. 

As an important part of this ecosystem, LF Edge was represented at this event through project leaders and members. LF Edge’s Tina Tsou, Co-Chair of the Akraino TSC and Enterprise Architect at Arm, was on-hand to host a workshop with China Mobile Technology (USA) about the trend of edge computing and LF Edge’s Akraino Edge Stack project.

Other member speakers include Dr Oleg Berzin, Senior Director at Equinix, Jason Shepherd, LF Edge Governing Board member, Project EVE leader and Vice President at Zededa and Tapio Tallgren, a member of the LF Edge Technical Advisory Council and Lead SW Architect at Nokia, to introduce their contributes to Akraino and share their views on MEC.

Joe Ward, CEO at EdgeVideo, Arif Khan,CEO at ParserLabs and China Mobile’s Su Gu, Senior Researcher, and Dr Jian Li also shared their views on Telco MEC and how to interwork with public clouds on MEC.

The “Innovation 2020 Cloud Technology Week” was a great success.  To learn more about Akraino Edge Stack, click here

 

Private LTE/5G ICN Akraino Blueprint

By Akraino Edge Stack, Blog

Written by Amar Kapadia, member of the Akraino Edge Stack community, co-founder at Aarna Networks, Inc. and an ONAP specialist. This blog originally ran on the Aarna Networks blog. You can find more content like this here

As one of the main contributors, I’m thrilled to state that the Private LTE/5G Integrated Cloud Native NFV/App Stack blueprint in LF Edge’s Akraino Edge Stack project got approved last month.

Given the opening up of unlicensed/licensed private spectrum all around the world (e.g. CBRS in the US), Private LTE/5G promises to be very exciting market. Six end users (Airbus, Globe, Orange, Tata Communications, T-Mobile, and Verizon), a number of vendors (such as us), and individuals are collaborating on this blueprint demo which will be created in a completely open manner and will contain, to the degree possible, open source components.

The key components of this blueprint are:

Private LTE/5G ICN Blueprint Software Stack

  • NFVI hardware: Standard server, switch, storage components

  • NFVI software: Kubernetes with OVN (SDN), Virtlet (to run VMs), Multus (for multiple CNI), Istio, and SD-EWAN (to connect an app across clouds). A main component in the NFVI software will also be an open source 5G UPF CNF.

  • Orchestrator: ONAP with AF integration, OpenNESS

  • Workloads (CNFs): Facebook Magma for vEPC, TIP OCN and Polaris for 5GC

  • Workloads (CNAs): We are starting with the applications in the original ICN blueprint, viz. 360° video, EdgeX Foundry, video AI/ML. However, we might change things around to collaborate with other Akraino blueprints such as the 5G MEC blueprint that is working on cloud gaming, HD video, and live broadcasting.

We will first start with Private LTE over CBRS but then quickly move over to Private 5G and edge computing.

As an open source effort, we could always use more help, Please join us if this is interesting!

LF Edge Member Spotlight: Arm

By Akraino Edge Stack, Blog, 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 sat down with Tina Tsou, Enterprise Architect at Arm and Co-Chair of the Technical Steering Committee for the Akraino Edge Stack, 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?

I work for Arm, a semiconductor IP company, as Enterprise Architect in the Infrastructure line of business. 

What are your interests in open source projects?

The open source approach allows me to get requirements from customers, understand the solutions from partners, so I can get prepared well for internal design and products, having open source in mind.

What are your thoughts on LF Edge and what sort of impact do you think LF Edge has on the edge, networking, and IoT industries?

I joined the Akraino Edge Stack per a customer’s ask and then the project was merged under the LF Edge umbrella. LF Edge is the de facto standard for the mainstream product and deployment of edge computing including edge servers, network edge, and device gateway.

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

The top benefits include having direct connection with customers that keep me updated on the latest trends of edge computing and collaboration among end to end ecosystems and supply chain as well as validation in CI/CD environments.

What are your top contributions as a community member?

I serve as LF Edge TAC member, Akraino TSC co-chair, contributed Integrated Edge Cloud (IEC) platform (Arm enabler) used by multiple blueprints like the 5G MEC System, the AI Edge, etc.  Sample blueprints that I’ve contributed to include:

  1. The purpose of Public Cloud Edge Interface (PCEI) Blueprint family is to specify a set of open APIs for enabling interworking between multiple functional entities or Domains that provide services needed for implementation of Edge capabilities/applications that require close integration between the Mobile Edge, the Public Cloud Core and Edge as well as the 3rd-Party provided Edge functions. In Release 3 we choose to expose the set of location APIs as defined by the MTSI MEC to showcase the PCEI capability.
  2. KubeEdge Edge Service Blueprint showcases end-to-end solution for edge services with KubeEdge centered edge stack. The first release will focus on the ML inference offloading use case. It supports multi-arch.
  3. The Radio Edge Cloud Blueprint is a member of the Telco Appliance blueprint family which is designed to provide a fully integration tested appliance tuned to meet the requirements of the RAN Intelligent Controller (RIC). Changes since Release 2 (2019-11-18), include New Features like Arm64 Support! – REC Release 3 supports Arm based CPUs for the first time. Support includes Ampere Hawk and Falcon servers.
  4. IEC (Integrated Edge Cloud) is a platform that enables new functionalities and business models on the network edge.
  5. The IEC type 2 mainly focuses on the high-performance computing system of medium and/or large deployment at the data center.
  6. IEC Type 3 mainly focuses on Android Application running on edge Arm Cloud architecture with GPU/ vGPU Management.

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

LF Edge has a pragmatic approach for Practice, Project, Production in a closed loop, which is at production quality and deployable.

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

Start by questioning how you expect LF Edge will be used in your business and then read the end user stories. You will find the right project and perspective that you care about and then take baby steps, for example, try an Akraino blueprint you are interested in, and report any issue you find. The community always has your back. Have fun!

Members of the Akraino TSC at the March 2020 F2F

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.

LF Edge Expands Ecosystem with Open Horizon, adds Seven New Members and Reaches Critical Deployment Milestones

By Akraino Edge Stack, Announcement, Baetyl, EdgeX Foundry, Fledge, Home Edge, LF Edge, Open Horizon, Project EVE, State of the Edge

  • Open Horizon, an application and metadata delivery platform, is now part of LF Edge as a Stage 1 (At-Large) Project.
  • New members bring R&D expertise in Telco, Enterprise and Cloud Edge Infrastructure.
  • EdgeX Foundry hits 4.3 million downloads and Akraino R2 delivers 14 validated deployment-ready blueprints.
  • Fledge shares a race car use case optimizing car and driver operations using Google Cloud, Machine Learning and state-of-the-art digital twins and simulators.

SAN FRANCISCO – April 30, 2020 –  LF Edge, an umbrella organization under The Linux Foundation that aims to establish an open, interoperable framework for edge computing independent of hardware, silicon, cloud, or operating system, today announced continued project momentum with the addition a new project and several technical milestones for EdgeX Foundry, Akraino Edge Stack and Fledge. Additionally, the project welcomes seven new members including CloudBrink, Federated Wireless, Industrial Technology Research Institute (ITRI), Kaloom, Ori Industries, Tensor Networks and VoerEir to its ecosystem.

Open Horizon, an existing project contributed by IBM, is a platform for managing the service software lifecycle of containerized workloads and related machine learning assets. It enables autonomous management of applications deployed to distributed webscale fleets of edge computing nodes and devices without requiring on-premise administrators.

Edge computing brings computation and data storage closer to where data is created by people, places, and things. Open Horizon simplifies the job of getting the right applications and machine learning onto the right compute devices, and keeps those applications running and updated. It also enables the autonomous management of more than 10,000 edge devices simultaneously – that’s 20 times as many endpoints as in traditional solutions.

“We are thrilled to welcome Open Horizon and new members to the LF Edge ecosystem,” said Arpit Joshipura, general manager, Networking, Edge & IoT, the Linux Foundation. “These additions complement our deployment ready LF Edge open source projects and our growing global ecosystem.”

“LF Edge is bringing together some of the most significant open source efforts in the industry, said Todd Moore, IBM VP Open Technology, “We are excited to contribute the Open Horizon project as this will expand the work with the other projects and companies to create shared approaches, open standards, and common interfaces and APIs.”

Open Horizon joins LF Edge’s other projects including: Akraino Edge Stack, Baetyl,  EdgeX Foundry, Fledge, Home Edge, Project EVE and State of the Edge. These projects support emerging edge applications across areas such as non-traditional video and connected things that require lower latency, and  faster processing and mobility. By forming a software stack that brings the best of cloud, enterprise and telecom, LF Edge helps to unify a fragmented edge market around a common, open vision for the future of the industry.

Since its launch last year, LF Edge projects have met significant milestones including:

  • EdgeX Foundry has hit 4.3 million docker downloads.
  • Akraino Edge Stack (Release 2) has 14 specific Blueprints that have all tested and validated on hardware labs and can be deployed immediately in various industries including Connected Vehicle, AR/VR, Integrated Cloud Native NFV, Network Cloud and Tungsten Fabric and SDN-Enabled Broadband Access.
  • Fledge shares a race car use case optimizing car and driver operations using Google Cloud, Machine Learning and state-of-the-art digital twins and simulators.
  • State of the Edge merged under LF Edge earlier this month and will continue to pave the path as the industry’s first open research program on edge computing. Under the umbrella, State of the Edge will continue its assets including State of the Edge Reports, Open Glossary of Edge Computing and the Edge Computing Landscape.

Support from the Expanding LF Edge Ecosystem

Federated Wireless:

“LF Edge has become a critical point of collaboration for network and enterprise edge innovators in this new cloud-driven IT landscape,” said Kurt Schaubach, CTO, Federated Wireless. “We joined the LF Edge to apply our connectivity and spectrum expertise to helping define the State of the Edge, and are energized by the opportunity to contribute to the establishment of next generation edge compute for the myriad of low latency applications that will soon be part of private 5G networks.”

Industrial Technology Research Institute (ITRI):

“ITRI is one of the world’s leading technology R&D institutions aiming to innovate a better future for society. Founded in 1973, ITRI has played a vital role in transforming Taiwan’s industries from labor-intensive into innovation-driven. We focus on the fields of Smart Living, Quality Health, and Sustainable Environment. Over the years, we also added a focus on 5G, AI, and Edge Computing related research and development. We joined LF Edge to leverage its leadership in these areas and to collaborate with the more than 75 member companies on projects like Akraino Edge Stack.”

Kaloom:

“Kaloom is pleased to join LF Edge to collaborate with the community on developing open, cloud-native networking, management and orchestration for edge deployments” said Suresh Krishnan, chief technology officer, Kaloom.  “We are working on an unified edge solution in order to optimize the use of resources while meeting the exacting performance, space and energy efficiency needs that are posed by edge deployments. We look forward to contributing our expertise in this space and to collaborating with the other members in LF Edge in accelerating the adoption of open source software, hardware and standards that speed up innovation and reduce TCO.”

Ori Industries:

“At Ori, we are fundamentally changing how software interacts with the distributed hardware on mobile operator networks.” said Mahdi Yahya, Founder and CEO, Ori Industries. “We also know that developers can’t provision, deploy and run applications seamlessly on telco infrastructure. We’re looking forward to working closely with the LF Edge community and the wider open-source ecosystem this year, as we turn our attention to developers and opening up access to the distributed, telco edge.”

Tensor Networks:

“Tensor Networks believes in and supports open source. Having an arena free from the risks of IP Infringement to collaborate and develop value which can be accessible to more people and organizations is essential to our efforts. Tensor runs its organization, and develops products on top of Linux.  The visions of LF Edge, where networks and latency are part of open software based service composition and delivery, align with our vision of open, fast, smart, secure, connected, and customer driven opportunities across all industry boundaries.” – Bill Walker, Chief Technology Officer.

VoerEir:

“In our extensive work with industry leaders for NFVI/VIM test and benchmarking,  a need to standardize infrastructure KPIs in Edge computing has gradually become more important,” said Arif  Khan, Co-Founder of VoerEir AB. “This need has made it essential for us to join LF Edge and to initiate the new Feature Project “Kontour” under the Akraino umbrella. We are excited to collaborate with various industry leaders to define, standardize  and measure Edge KPIs.”

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.

The Linux Foundation has registered trademarks and uses trademarks. For a list of trademarks of The Linux Foundation, please see our trademark usage page: https://www.linuxfoundation.org/trademark-usage. Linux is a registered trademark of Linus Torvalds.

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Building an End-to-End NFV & Applications Stack Powered by Kubernetes and ONAP

By Akraino Edge Stack, 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.

Introduction

In this article, we’ll look at how open source projects like Kubernetes, ONAP and many others can be stacked to build a Network Function Virtualization (NFV) framework that is identified as an Akraino Integrated Cloud Network (ICN) blueprint.  We’ll outline the step-by-step inclusion of open source projects for various purposes (security, monitoring, orchestration, etc.). Readers will leave with an understanding of the role each open source project will play in the stack.

Glossary

Here are some key terms that I use throughout this article:

NFV: Network Function Virtualization

ONAP: Open Network Automation Framework

CNF: cloud-native network functions

VNF: Virtual Network Functions

Akraino ICN Blueprint: Akraino Integrated Cloud Network or Akraino Edge Stack is a Linux Foundations project for edge computing infrastructure. It is one of the internal projects or blueprints dedicated to the cloud native NFV stack.

CNI: container-native interface

What is NFV (Network Function Virtualization)?

NFV is a concept of transforming hardware-based network functions into software-based applications. It simply decouples network functions from proprietary hardware without impacting performance.

Why do we need NFV?

  • Management and orchestration of thousands of network resources from central location
  • Enable network programmability
  • Allow dynamic scaling of network resources
  • High level automation in the network
  • Monitoring of resources and network connectivity
  • Ability to integrate new services
  • Optimization of network performance

The main reasons for enterprises and service to adopt NFV include: a vast scale of network resources containing different types of network equipment from different vendors, reducing the CAPEX and OPEX for network infrastructure, delivering services in an agile manner and enabling scalability and elasticity of network infrastructure to support rapid technology innovation.

Open Source for NFV

Kubernetes and ONAP are the key open source projects for this NFV stack. Using Kubernetes at the edge is something that leading networking solution companies are evaluating to provide dynamic capabilities managed from a central cloud. If you aren’t familiar with ONAP, it is a platform for real-time, policy-driven orchestration and automation of physical and virtual network functions.

We’ve already seen how Kubernetes is used in NFV as a backbone for cloud-native evolvement. This push for Kubernetes to dive into the NFV stack opens up possibilities for other open-source projects to make up the NFV backbone of enterprise and telecom networks. And further, Kubernetes will enable more automation and dynamic orchestration of application and infrastructure resources across the NFV-powered network.

Additionally, since various edges or hubs are involved in the typical 5G and enterprise network backed by NFV architecture, open-source projects like ONAP and Akraino blueprints are coming up with specific modules for critical orchestration and monitoring tasks.

Now that we’ve acknowledged the major role of Kubernetes and ONAP, let’s focus on the exact needs for a complete end-to-end NFV stack that will innovate a software-driven network. Let’s also look at how we can address those needs by combining different open source projects to power a 5G network and enterprise WAN.

Why Do We Need an End-to-End NFV Stack?

Currently, the IT infrastructure of enterprises and communication service providers is transitioning from centrally managed to geographically distributed. 5G presents the prominent use case for edge nodes or hubs as the initial level data center to communicate with IoT devices and host application services. And enterprises are deploying SD-WAN with edge-like capabilities.

In such architectures, workloads types like microservices, virtual network functions (VNFs) and cloud-native network functions (CNFs) are distributed. All those workload types are orchestrated by different solutions like Kubernetes and commercial solutions provided by VMware, Red Hat and Rancher.

In Figure 1, we can see that it’s difficult to manage all the workloads with different orchestrators, for several reasons. Security policy enforcement and monitoring of distributed nodes differs from centralized ones. You’ll need to manage all clouds and applications deployed on them and get insights about the performance of resources deployed on different edge sites. Additionally, this transition will cost the enterprises and telecom network providers.

Last year at ONS Europe (Open Networking Summit), Srinivasa Adeppalli (Intel) and Ravi Chunduru (Verizon) discussed using Kubernetes with ONAP4K8S, a sub-project in ONAP. This stack would manage all the applications and network functions spread across multiple Kubernetes clusters hosted on different edge nodes or data center infrastructures. They showed how a single pane of glass can orchestrate different edge sites, multiple clouds and network traffic.

Let’s See How it Works

In the presentation, Srinivas and Ravi showed an SD-WAN enterprise edge with microservices deployed in clusters and VNFs and CNFs present in an NFV stack. A request for data access generates the traffic that steers from pods to the internet through different VNFs, CNFs and external routers. Some of the microservices can be user-facing, with low latency needs. In this case, you need a multi-traffic orchestrator that controls the traffic flow and prioritizes the user-facing applications to deliver optimal performance.

Figure 3 shows the stack with the traffic orchestrator. In this scenario, Istio service mesh framework couples the microservices deployed at different edge sites. IPAM Manager ensures that each site is assigned a unique IP subnet and avoids overlapping addresses to Microservices/functions.

As we have seen, microservices, along with VNFs and CNFs, span multiple edge sites or clouds. So, we need a multi-zone manager (Figure 4).

Edge sites may face targeted attacks by external threats that can compromise network communication channels, microservices-based apps, software, and SSD/HDD. In Figure 5, we’ll use a new orchestrator called Multi-security orchestrator that uses CA Service, key distribution and attestation. You can integrate Istio, Vault project and Keycloak project with the Multi-security orchestrator to protect sensitive data as well as manage identity and access. In fact, you can run Istio from the central multi-cluster security orchestrator.

Further, a Multi-Cluster Security Orchestrator lets you monitor all the applications, VNFs and CNFs to check the health status and performance of multi-cluster app visibility and monitoring modules. Figure 6 shows how you can integrate PrometheusJaeger and Fluentd  on each edge site for data monitoring and collect the data logs for analysis at a central location.

Now we have a complete NFV stack, called an Akraino ICN (Integrated Cloud Network) blueprint.

The major frameworks used in the end-to-end NFV stack include ONAP4K8sOVN4K8sNFV, Kubernetes and Akraino SD-EWAN.

You can use ONAP4K8s as a Multi-Cloud/Cluster orchestrator to perform the following tasks:

  • Single-click applications deployment
  • Auto-configuration of service meshes
  • Auto-configuration of SD-WAN to facilitate connectivity among micro-services in multiple clusters
  • Parent CA and Child CA cert/private key enrollment for each edge/zone

You can use Kubernetes to orchestrate microservices-based applications and NFV-specific components like Multus, OVN4K8SNFV and SRIOVNIC as well as application components including Istio and Prometheus. OVN4K8sNFV works as a CNI (container-native interface) that supports multiple types of workloads, such as apps, CNFs, VNFs, etc.

Finally, Akraino SD-EWAN provides overlay connectivity among the Kubernetes clusters.

Conclusion

In this article, I’ve highlighted several open source projects that can be useful at various NFV tasks. Most of these projects are mature and widely integrated into different domains on a different scale. Each of the open source project addresses various features in NFV stack. You need to determine key capabilities from open source projects for each NFV features. You can get more information about implementation details and ongoing development from Akraino ICN and learn more about the NFV stack.

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: 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!