According to a new Gartner report1, “Around 10% of enterprise-generated data is created and processed outside a traditional centralized data center or cloud. By 2022, Gartner predicts this
figure will reach 75%”. In addition to hosting new 5G era services, the other major network operator driver for edge compute and edge clouds is deploying virtualized network infrastructure, replacing many dedicated hardware-based elements with virtual network functions (VNFs) running on general purpose edge compute. Even portions of access networks are being virtualized, and many of these functions need to be deployed close to end users. The combination of these infrastructure and applications drivers is a major reason that so much of 5G era network transformation resolves around edge cloud distribution.
"A programmable, flexible and scalable network architecture will be required to support efficiently any Industrial-IoT solution. Vendor-Independent Software Defined Network will play a key role to address low latency, secure and real-time solutions. "
A Comparison of Cloud Execution Mechanisms Fog, Edge, and Clone Cloud Computing IJECEIAES
Cloud computing is a technology that was developed a decade ago to provide uninterrupted, scalable services to users and organizations. Cloud computing has also become an attractive feature for mobile users due to the limited features of mobile devices. The combination of cloud technologies with mobile technologies resulted in a new area of computing called mobile cloud computing. This combined technology is used to augment the resources existing in Smart devices. In recent times, Fog computing, Edge computing, and Clone Cloud computing techniques have become the latest trends after mobile cloud computing, which have all been developed to address the limitations in cloud computing. This paper reviews these recent technologies in detail and provides a comparative study of them. It also addresses the differences in these technologies and how each of them is effective for organizations and developers.
CONTAINERIZED SERVICES ORCHESTRATION FOR EDGE COMPUTING IN SOFTWARE-DEFINED W...IJCNCJournal
As SD-WAN disrupts legacy WAN technologies and becomes the preferred WAN technology adopted by corporations, and Kubernetes becomes the de-facto container orchestration tool, the opportunities for deploying edge-computing containerized applications running over SD-WAN are vast. Service orchestration in SD-WAN has not been provided with enough attention, resulting in the lack of research focused on service discovery in these scenarios. In this article, an in-house service discovery solution that works alongside Kubernetes’ master node for allowing improved traffic handling and better user experience when running micro-services is developed. The service discovery solution was conceived following a design science research approach. Our research includes the implementation of a proof-ofconcept SD-WAN topology alongside a Kubernetes cluster that allows us to deploy custom services and delimit the necessary characteristics of our in-house solution. Also, the implementation's performance is tested based on the required times for updating the discovery solution according to service updates. Finally, some conclusions and modifications are pointed out based on the results, while also discussing possible enhancements.
A review on orchestration distributed systems for IoT smart services in fog c...IJECEIAES
This paper provides a review of orchestration distributed systems for IoT smart services in fog computing. The cloud infrastructure alone cannot handle the flow of information with the abundance of data, devices and interactions. Thus, fog computing becomes a new paradigm to overcome the problem. One of the first challenges was to build the orchestration systems to activate the clouds and to execute tasks throughout the whole system that has to be considered to the situation in the large scale of geographical distance, heterogeneity and low latency to support the limitation of cloud computing. Some problems exist for orchestration distributed in fog computing are to fulfil with high reliability and low-delay requirements in the IoT applications system and to form a larger computer network like a fog network, at different geographic sites. This paper reviewed approximately 68 articles on orchestration distributed system for fog computing. The result shows the orchestration distribute system and some of the evaluation criteria for fog computing that have been compared in terms of Borg, Kubernetes, Swarm, Mesos, Aurora, heterogeneity, QoS management, scalability, mobility, federation, and interoperability. The significance of this study is to support the researcher in developing orchestration distributed systems for IoT smart services in fog computing focus on IR4.0 national agenda.
Security and Privacy Issues of Fog Computing: A SurveyHarshitParkar6677
Abstract. Fog computing is a promising computing paradigm that ex-
tends cloud computing to the edge of networks. Similar to cloud comput-
ing but with distinct characteristics, fog computing faces new security
and privacy challenges besides those inherited from cloud computing. In
this paper, we have surveyed these challenges and corresponding solu-
tions in a brief manner.
"A programmable, flexible and scalable network architecture will be required to support efficiently any Industrial-IoT solution. Vendor-Independent Software Defined Network will play a key role to address low latency, secure and real-time solutions. "
A Comparison of Cloud Execution Mechanisms Fog, Edge, and Clone Cloud Computing IJECEIAES
Cloud computing is a technology that was developed a decade ago to provide uninterrupted, scalable services to users and organizations. Cloud computing has also become an attractive feature for mobile users due to the limited features of mobile devices. The combination of cloud technologies with mobile technologies resulted in a new area of computing called mobile cloud computing. This combined technology is used to augment the resources existing in Smart devices. In recent times, Fog computing, Edge computing, and Clone Cloud computing techniques have become the latest trends after mobile cloud computing, which have all been developed to address the limitations in cloud computing. This paper reviews these recent technologies in detail and provides a comparative study of them. It also addresses the differences in these technologies and how each of them is effective for organizations and developers.
CONTAINERIZED SERVICES ORCHESTRATION FOR EDGE COMPUTING IN SOFTWARE-DEFINED W...IJCNCJournal
As SD-WAN disrupts legacy WAN technologies and becomes the preferred WAN technology adopted by corporations, and Kubernetes becomes the de-facto container orchestration tool, the opportunities for deploying edge-computing containerized applications running over SD-WAN are vast. Service orchestration in SD-WAN has not been provided with enough attention, resulting in the lack of research focused on service discovery in these scenarios. In this article, an in-house service discovery solution that works alongside Kubernetes’ master node for allowing improved traffic handling and better user experience when running micro-services is developed. The service discovery solution was conceived following a design science research approach. Our research includes the implementation of a proof-ofconcept SD-WAN topology alongside a Kubernetes cluster that allows us to deploy custom services and delimit the necessary characteristics of our in-house solution. Also, the implementation's performance is tested based on the required times for updating the discovery solution according to service updates. Finally, some conclusions and modifications are pointed out based on the results, while also discussing possible enhancements.
A review on orchestration distributed systems for IoT smart services in fog c...IJECEIAES
This paper provides a review of orchestration distributed systems for IoT smart services in fog computing. The cloud infrastructure alone cannot handle the flow of information with the abundance of data, devices and interactions. Thus, fog computing becomes a new paradigm to overcome the problem. One of the first challenges was to build the orchestration systems to activate the clouds and to execute tasks throughout the whole system that has to be considered to the situation in the large scale of geographical distance, heterogeneity and low latency to support the limitation of cloud computing. Some problems exist for orchestration distributed in fog computing are to fulfil with high reliability and low-delay requirements in the IoT applications system and to form a larger computer network like a fog network, at different geographic sites. This paper reviewed approximately 68 articles on orchestration distributed system for fog computing. The result shows the orchestration distribute system and some of the evaluation criteria for fog computing that have been compared in terms of Borg, Kubernetes, Swarm, Mesos, Aurora, heterogeneity, QoS management, scalability, mobility, federation, and interoperability. The significance of this study is to support the researcher in developing orchestration distributed systems for IoT smart services in fog computing focus on IR4.0 national agenda.
Security and Privacy Issues of Fog Computing: A SurveyHarshitParkar6677
Abstract. Fog computing is a promising computing paradigm that ex-
tends cloud computing to the edge of networks. Similar to cloud comput-
ing but with distinct characteristics, fog computing faces new security
and privacy challenges besides those inherited from cloud computing. In
this paper, we have surveyed these challenges and corresponding solu-
tions in a brief manner.
Capillary Networks – Bridging the Cellular and IoT WorldsEricsson
The Internet of Things (IoT) represents a new revolutionary era of computing technology that enables a wide variety of devices to interoperate through the existing Internet infrastructure.
Cisco Network Convergence System: Building the Foundation for the Internet of...Cisco Service Provider
Cisco Network Convergence System (NCS) is a family of integrated packet routing and transport systems designed to help service providers capture their share of the IoE Value at Stake. NCS is built on major innovations in silicon, optics and software and provides the building blocks of a multilayer converged network that intelligently manages and scales functions across its architecture.
ACG Research analyzed the business case for NCS and found it achieves massive scale via multichassis system architecture, the density and performance of its new chip set, and the extension of the control plane to virtual machines (VM) internally and externally.
The digital transformation underway is accelerating, enabling new business opportunities both for telecom operators and for enterprises from other industries. The main drivers are the need for increased efficiency, flexibility and new business models enabled by the introduction of 5G and increased adoption of cloud technologies. New services can be expected to be deployed at an unprecedented pace.
A Centralized Network Management Application for Academia and Small Business ...ITIIIndustries
Software-defined networking (SDN) is reshaping the networking paradigm. Previous research shows that SDN has advantages over traditional networks because it separates the control and data plane, leading to greater flexibility through network automation and programmability. Small business and academia networks require flexibility, like service provider networks, to scale, deploy, and self-heal network infrastructure that comprises of cloud operating systems, virtual machines, containers, vendor networking equipment, and virtual network functions (VNFs); however, as SDN evolves in industry, there has been limited research to develop an SDN architecture to fulfil the requirements of small business and academia networks. This research proposes a network architecture that can abstract, orchestrate, and scale configurations based on academia and small business network requirements. Our results show that the proposed architecture provides enhanced network management and operations when combined with the network orchestration application (NetO-App) developed in this research. The NetO-App orchestrates network policies, automates configuration changes, secures container infrastructure, and manages internal and external communication between the campus networking infrastructure.
Implementing K-Out-Of-N Computing For Fault Tolerant Processing In Mobile and...IJERA Editor
Despite the advances in hardware for hand-held mobile devices, resource-intensive applications (e.g., video and imagestorage and processing or map-reduce type) still remain off bounds since they require large computation and storage capabilities.Recent research has attempted to address these issues by employing remote servers, such as clouds and peer mobile devices.For mobile devices deployed in dynamic networks (i.e., with frequent topology changes because of node failure/unavailability andmobility as in a mobile cloud), however, challenges of reliability and energy efficiency remain largely unaddressed. To the best of ourknowledge, we are the first to address these challenges in an integrated manner for both data storage and processing in mobilecloud, an approach we call k-out-of-n computing. In our solution, mobile devices successfully retrieve or process data, in the mostenergy-efficient way, as long as k out of n remote servers are accessible. Through a real system implementation we prove the feasibilityof our approach. Extensive simulations demonstrate the fault tolerance and energy efficiency performance of our framework in largerscale networks.
http://www.ericsson.com
Imagine what you could do with a full multi-access data management solution that can also provide you a 360 degrees view of your user’s data assets - all in just one “box”?
It auditing to assure a secure cloud computingingenioustech
Dear Students
Ingenious techno Solution offers an expertise guidance on you Final Year IEEE & Non- IEEE Projects on the following domain
JAVA
.NET
EMBEDDED SYSTEMS
ROBOTICS
MECHANICAL
MATLAB etc
For further details contact us:
enquiry@ingenioustech.in
044-42046028 or 8428302179.
Ingenious Techno Solution
#241/85, 4th floor
Rangarajapuram main road,
Kodambakkam (Power House)
http://www.ingenioustech.in/
IMPROVEMENTS FOR DMM IN SDN AND VIRTUALIZATION-BASED MOBILE NETWORK ARCHITECTUREijmnct
The (r)evolution of wireless access infrastructure can be described as the convergence of the available radio communication systems towards a harmonized, more flexible and reconfigurable access system to match the current and upcoming demands. In recent years Softwarization and Virtualization technologies have moved from server and network domains to wireless domain and provides new perspectives of managing mobile networks functionalities. This paper provides evolution of the mobile network architecture in Software Defined Networking (SDN) and virtualization context and realizes it through the use of distribution of gateway function approach. Key improvements with proposed approach are to support efficient mobility management in heterogeneous access environments, remove the chains of IP
preservation and optimal data path management according to application needs. A functional setup
validates and assays the proposed evolution in terms of inter-system handover preparation, interruption and completion time relative to control plane delay requirements of the 5G networks.
IMPROVEMENTS FOR DMM IN SDN AND VIRTUALIZATION-BASED MOBILE NETWORK ARCHITECTUREijmnct
The (r)evolution of wireless access infrastructure can be described as the convergence of the available radio communication systems towards a harmonized, more flexible and reconfigurable access system to match the current and upcoming demands. In recent years Softwarization and Virtualization technologies have moved from server and network domains to wireless domain and provides new perspectives of
managing mobile networks functionalities. This paper provides evolution of the mobile network architecture in Software Defined Networking (SDN) and virtualization context and realizes it through the use of distribution of gateway function approach. Key improvements with proposed approach are to support efficient mobility management in heterogeneous access environments, remove the chains of IP preservation and optimal data path management according to application needs. A functional setup validates and assays the proposed evolution in terms of inter-system handover preparation, interruption
and completion time relative to control plane delay requirements of the 5G networks.
Improvements for DMM in SDN and Virtualization-Based Mobile Network Architectureijmnct
The (r)evolution of wireless access infrastructure can be described as the convergence of the available radio communication systems towards a harmonized, more flexible and reconfigurable access system to match the current and upcoming demands. In recent years Softwarization and Virtualization technologies have moved from server and network domains to wireless domain and provides new perspectives of managing mobile networks functionalities. This paper provides evolution of the mobile network architecture in Software Defined Networking (SDN) and virtualization context and realizes it through the use of distribution of gateway function approach. Key improvements with proposed approach are to support efficient mobility management in heterogeneous access environments, remove the chains of IP preservation and optimal data path management according to application needs. A functional setup validates and assays the proposed evolution in terms of inter-system handover preparation, interruption and completion time relative to control plane delay requirements of the 5G networks.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
The Internet of things (IoT) is the extension of Internet connectivity into physical devices and everyday objects.
Presentation cover below topics
How IoT works ? IoT Key Components. Enabling technologies for IoT, IoT Connectivity , Technology Road Map. Iot architecture, How to Choose the Right IoT Platform,Benefits of IoT, IoT adoption barriers, Challenges for IoT security:
Other Challenges
Fog Computing extends the Cloud Computing paradigm close to the edge of network, and thus enabling a new breed of applications and services.
This is why it is also sometimes called as Edge computing but the defining characteristics of the Fog are: Low latency, Mobility, High efficiency and performance.
In this presentation we will talk about What is Fog Computing, how is it different from Edge computing, its benefits and limitations and how it will shape the future of IoT.
Get Cloud Resources to the IoT Edge with Fog ComputingBiren Gandhi
Fog Computing as a foundational architectural concept for Internet of Things (IoT) and Internet of Everything (IoE).
Embedded devices in the IoT are hampered by the compute, storage, and service limitations of living life on the edge. As IoT edge devices comprise broader sensor networks for industrial automation, transportation, and other safety critical applications, their high uptime requirements are nonnegotiable and service latencies must be kept within realtime or near real time parameters. However, the size, weight, power, and cost constraints of edge platforms also inhibit the ondevice resources available for executing such functions. In this session, Gandhi will introduce Fog Computing, a new paradigm for the IoT that extends compute, storage, and application resources from the cloud to the network edge. Beyond the interplay between Fog and Cloud, Gandhi will show how Fog services can be leveraged across a range of heterogeneous platforms—from end user devices and access points to edge routers and switches—through software technology that facilitates the collection, storage, analysis, and fusion of data to drive success in your next IoT device deployment.
A revolution is going on at the Edge of the Network.
Why Edge is important?
How Edge Computing is shaping the way we do IoT, AR/VR, Big Data, Machine Learning and Analytics applications.
What are the important problems and who’s problem is this?
What solutions Industry is looking into right now?
This review of the "Industry report by SDxCentral" summarizes what is going on in the Industry.
Capillary Networks – Bridging the Cellular and IoT WorldsEricsson
The Internet of Things (IoT) represents a new revolutionary era of computing technology that enables a wide variety of devices to interoperate through the existing Internet infrastructure.
Cisco Network Convergence System: Building the Foundation for the Internet of...Cisco Service Provider
Cisco Network Convergence System (NCS) is a family of integrated packet routing and transport systems designed to help service providers capture their share of the IoE Value at Stake. NCS is built on major innovations in silicon, optics and software and provides the building blocks of a multilayer converged network that intelligently manages and scales functions across its architecture.
ACG Research analyzed the business case for NCS and found it achieves massive scale via multichassis system architecture, the density and performance of its new chip set, and the extension of the control plane to virtual machines (VM) internally and externally.
The digital transformation underway is accelerating, enabling new business opportunities both for telecom operators and for enterprises from other industries. The main drivers are the need for increased efficiency, flexibility and new business models enabled by the introduction of 5G and increased adoption of cloud technologies. New services can be expected to be deployed at an unprecedented pace.
A Centralized Network Management Application for Academia and Small Business ...ITIIIndustries
Software-defined networking (SDN) is reshaping the networking paradigm. Previous research shows that SDN has advantages over traditional networks because it separates the control and data plane, leading to greater flexibility through network automation and programmability. Small business and academia networks require flexibility, like service provider networks, to scale, deploy, and self-heal network infrastructure that comprises of cloud operating systems, virtual machines, containers, vendor networking equipment, and virtual network functions (VNFs); however, as SDN evolves in industry, there has been limited research to develop an SDN architecture to fulfil the requirements of small business and academia networks. This research proposes a network architecture that can abstract, orchestrate, and scale configurations based on academia and small business network requirements. Our results show that the proposed architecture provides enhanced network management and operations when combined with the network orchestration application (NetO-App) developed in this research. The NetO-App orchestrates network policies, automates configuration changes, secures container infrastructure, and manages internal and external communication between the campus networking infrastructure.
Implementing K-Out-Of-N Computing For Fault Tolerant Processing In Mobile and...IJERA Editor
Despite the advances in hardware for hand-held mobile devices, resource-intensive applications (e.g., video and imagestorage and processing or map-reduce type) still remain off bounds since they require large computation and storage capabilities.Recent research has attempted to address these issues by employing remote servers, such as clouds and peer mobile devices.For mobile devices deployed in dynamic networks (i.e., with frequent topology changes because of node failure/unavailability andmobility as in a mobile cloud), however, challenges of reliability and energy efficiency remain largely unaddressed. To the best of ourknowledge, we are the first to address these challenges in an integrated manner for both data storage and processing in mobilecloud, an approach we call k-out-of-n computing. In our solution, mobile devices successfully retrieve or process data, in the mostenergy-efficient way, as long as k out of n remote servers are accessible. Through a real system implementation we prove the feasibilityof our approach. Extensive simulations demonstrate the fault tolerance and energy efficiency performance of our framework in largerscale networks.
http://www.ericsson.com
Imagine what you could do with a full multi-access data management solution that can also provide you a 360 degrees view of your user’s data assets - all in just one “box”?
It auditing to assure a secure cloud computingingenioustech
Dear Students
Ingenious techno Solution offers an expertise guidance on you Final Year IEEE & Non- IEEE Projects on the following domain
JAVA
.NET
EMBEDDED SYSTEMS
ROBOTICS
MECHANICAL
MATLAB etc
For further details contact us:
enquiry@ingenioustech.in
044-42046028 or 8428302179.
Ingenious Techno Solution
#241/85, 4th floor
Rangarajapuram main road,
Kodambakkam (Power House)
http://www.ingenioustech.in/
IMPROVEMENTS FOR DMM IN SDN AND VIRTUALIZATION-BASED MOBILE NETWORK ARCHITECTUREijmnct
The (r)evolution of wireless access infrastructure can be described as the convergence of the available radio communication systems towards a harmonized, more flexible and reconfigurable access system to match the current and upcoming demands. In recent years Softwarization and Virtualization technologies have moved from server and network domains to wireless domain and provides new perspectives of managing mobile networks functionalities. This paper provides evolution of the mobile network architecture in Software Defined Networking (SDN) and virtualization context and realizes it through the use of distribution of gateway function approach. Key improvements with proposed approach are to support efficient mobility management in heterogeneous access environments, remove the chains of IP
preservation and optimal data path management according to application needs. A functional setup
validates and assays the proposed evolution in terms of inter-system handover preparation, interruption and completion time relative to control plane delay requirements of the 5G networks.
IMPROVEMENTS FOR DMM IN SDN AND VIRTUALIZATION-BASED MOBILE NETWORK ARCHITECTUREijmnct
The (r)evolution of wireless access infrastructure can be described as the convergence of the available radio communication systems towards a harmonized, more flexible and reconfigurable access system to match the current and upcoming demands. In recent years Softwarization and Virtualization technologies have moved from server and network domains to wireless domain and provides new perspectives of
managing mobile networks functionalities. This paper provides evolution of the mobile network architecture in Software Defined Networking (SDN) and virtualization context and realizes it through the use of distribution of gateway function approach. Key improvements with proposed approach are to support efficient mobility management in heterogeneous access environments, remove the chains of IP preservation and optimal data path management according to application needs. A functional setup validates and assays the proposed evolution in terms of inter-system handover preparation, interruption
and completion time relative to control plane delay requirements of the 5G networks.
Improvements for DMM in SDN and Virtualization-Based Mobile Network Architectureijmnct
The (r)evolution of wireless access infrastructure can be described as the convergence of the available radio communication systems towards a harmonized, more flexible and reconfigurable access system to match the current and upcoming demands. In recent years Softwarization and Virtualization technologies have moved from server and network domains to wireless domain and provides new perspectives of managing mobile networks functionalities. This paper provides evolution of the mobile network architecture in Software Defined Networking (SDN) and virtualization context and realizes it through the use of distribution of gateway function approach. Key improvements with proposed approach are to support efficient mobility management in heterogeneous access environments, remove the chains of IP preservation and optimal data path management according to application needs. A functional setup validates and assays the proposed evolution in terms of inter-system handover preparation, interruption and completion time relative to control plane delay requirements of the 5G networks.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
The Internet of things (IoT) is the extension of Internet connectivity into physical devices and everyday objects.
Presentation cover below topics
How IoT works ? IoT Key Components. Enabling technologies for IoT, IoT Connectivity , Technology Road Map. Iot architecture, How to Choose the Right IoT Platform,Benefits of IoT, IoT adoption barriers, Challenges for IoT security:
Other Challenges
Fog Computing extends the Cloud Computing paradigm close to the edge of network, and thus enabling a new breed of applications and services.
This is why it is also sometimes called as Edge computing but the defining characteristics of the Fog are: Low latency, Mobility, High efficiency and performance.
In this presentation we will talk about What is Fog Computing, how is it different from Edge computing, its benefits and limitations and how it will shape the future of IoT.
Get Cloud Resources to the IoT Edge with Fog ComputingBiren Gandhi
Fog Computing as a foundational architectural concept for Internet of Things (IoT) and Internet of Everything (IoE).
Embedded devices in the IoT are hampered by the compute, storage, and service limitations of living life on the edge. As IoT edge devices comprise broader sensor networks for industrial automation, transportation, and other safety critical applications, their high uptime requirements are nonnegotiable and service latencies must be kept within realtime or near real time parameters. However, the size, weight, power, and cost constraints of edge platforms also inhibit the ondevice resources available for executing such functions. In this session, Gandhi will introduce Fog Computing, a new paradigm for the IoT that extends compute, storage, and application resources from the cloud to the network edge. Beyond the interplay between Fog and Cloud, Gandhi will show how Fog services can be leveraged across a range of heterogeneous platforms—from end user devices and access points to edge routers and switches—through software technology that facilitates the collection, storage, analysis, and fusion of data to drive success in your next IoT device deployment.
A revolution is going on at the Edge of the Network.
Why Edge is important?
How Edge Computing is shaping the way we do IoT, AR/VR, Big Data, Machine Learning and Analytics applications.
What are the important problems and who’s problem is this?
What solutions Industry is looking into right now?
This review of the "Industry report by SDxCentral" summarizes what is going on in the Industry.
All the details of Fog Computing is discussed in this PPT, its better to get knowledge about this ppt,All the details of applications and examples are covered..
There has been no shortage of edge computing activities during 2017, in both the telco and web-scale
domains. Several Tier One communication service providers (CSPs), including AT&T, China Mobile, and
Deutsche Telecom (DT), have announced that edge computing will be a key component of their future
network strategies and expect that several new use cases will be powered by edge servers. In the cloud
domain, Amazon, Facebook, and Google are pushing further toward the edge of their own networks, creating
more points of presence throughout the world. Amazon’s acquisition of Whole Foods in the United States
could also be interpreted as a first attempt to obtain real estate across the U.S. market that can be used
for Amazon’s edge servers. In fact, all major web-scale companies—Amazon, Google, and Microsoft—have
announced edge computing services that are driven by IoT use cases.
A Comprehensive Exploration of Fog Computing.pdfEnterprise Wired
This article delves into the intricacies of Fog computing, exploring its definition, key components, benefits, and its transformative impact on various industries.
Edge computing, trends and drivers to enable critical use cases for the digital economy. Types of edge and scale factors are mentioned in this article.
A Guide to Edge Computing Technology For Business OperationsCerebrum Infotech
Edge computing services enable us to generate more data at a faster rate and distribute it to a range of networks and devices located at or near the consumer. For further details, see our website.
Whitepaper: Mobile Networks in a smart digital future - deploying a platform ...Petr Nemec
The Internet of Things poses particular challenges on the mobile networks of the future - this Whitepaper gives an outlook on what CSPs need to consider when choosing a viable upgrade path and migration strategy towards meeting IoT and NB-IoT (narrow band IoT) requirements.
Tiarrah Computing: The Next Generation of ComputingIJECEIAES
The evolution of Internet of Things (IoT) brought about several challenges for the existing Hardware, Network and Application development. Some of these are handling real-time streaming and batch bigdata, real- time event handling, dynamic cluster resource allocation for computation, Wired and Wireless Network of Things etc. In order to combat these technicalities, many new technologies and strategies are being developed. Tiarrah Computing comes up with integration the concept of Cloud Computing, Fog Computing and Edge Computing. The main objectives of Tiarrah Computing are to decouple application deployment and achieve High Performance, Flexible Application Development, High Availability, Ease of Development, Ease of Maintenances etc. Tiarrah Computing focus on using the existing opensource technologies to overcome the challenges that evolve along with IoT. This paper gives you overview of the technologies and design your application as well as elaborate how to overcome most of existing challenge.
The evolution of Internet of Things (IoT) brought about several challenges for the existing Hardware, Network and Application development. Some of these are handling real-time streaming and batch bigdata, real- time event handling, dynamic cluster resource allocation for computation, Wired and Wireless Network of Things etc. In order to combat these technicalities, many new technologies and strategies are being developed. Tiarrah Computing comes up with integration the concept of Cloud Computing, Fog Computing and Edge Computing. The main objectives of Tiarrah Computing are to decouple application deployment and achieve High Performance, Flexible Application Development, High Availability, Ease of Development, Ease of Maintenances etc. Tiarrah Computing focus on using the existing opensource technologies to overcome the challenges that evolve along with IoT. This paper gives you overview of the technologies and design your application as well as elaborate how to overcome most of existing challenge.
Ericsson Technology Review: Creating the next-generation edge-cloud ecosystemEricsson
The surge in data volume that will come from the massive number of devices enabled by 5G has made edge computing more important than ever before. Beyond its abilities to reduce network traffic and improve user experience, edge computing will also play a critical role in enabling use cases for ultra-reliable low-latency communication in industrial manufacturing and a variety of other sectors.
This Ericsson Technology Review article explores the topic of how to deliver distributed edge computing solutions that can host different kinds of platforms and applications and provide a high level of flexibility for application developers. Rather than building a new application ecosystem and platform, we strongly recommend reusing industrialized and proven capabilities, utilizing the momentum created with Cloud Native Computing Foundation, and ensuring backward compatibility.
The AI Index is an independent initiative at the Stanford Institute for Human-Centered Artificial Intelligence (HAI), led by the AI Index Steering Committee, an interdisciplinary group of experts from across academia and industry. The annual report tracks, collates, distills, and visualizes data relating to artificial intelligence, enabling decision-makers to take meaningful action to advance AI responsibly and ethically with humans in mind.
Intel Blockscale ASICs are built for the demanding environment of cryptocurrency mining. Each ASIC has built-in temperature and voltage sensor capabilities. The accelerator can be operated across a range of frequencies, enabling system designers to balance performance and efficiency.
Cryptography Processing with 3rd Gen Intel Xeon Scalable ProcessorsDESMOND YUEN
Cryptographic operations are amongst the most compute intensive and critical operations applied to data as it is stored, moved, and processed. Comprehending Intel's cryptography processing acceleration is essential to optimizing overall platform workload, and service performance.
At Intel, security comes first both in the way we work and in what we work on. Our culture and practices guide everything we build, with the goal of delivering the highest performance and optimal protections. As with previous reports, the 2021 Intel Product Security Report demonstrates our Security First Pledge and our endless efforts to proactively seek out and mitigate security issues.
How can regulation keep up as transformation races ahead? 2022 Global regulat...DESMOND YUEN
As the pandemic drags into its third year, financial services firms face a range of challenges, from increased operational complexity and an evolving regulatory directive to address environmental and social issues to new forms of competition
and evolving technologies, such as digital assets and cryptocurrencies. Banks, insurers, asset managers and other financial services firms (collectively referred to as “firms” in
the rest of this document) must innovate more effectively — and rapidly — to keep up with the pace of change while still identifying emerging risks and building appropriate governance and controls.
NASA Spinoffs Help Fight Coronavirus, Clean Pollution, Grow Food, MoreDESMOND YUEN
NASA's mission of exploration requires new technologies, software, and research – which show up in daily life. The agency’s Spinoff 2022 publication tells the stories of companies, start-ups, and entrepreneurs transforming these innovations into cutting-edge products and services that boost the economy, protect the planet, and save lives.
“The value of NASA is not confined to the cosmos but realized throughout our country – from hundreds of thousands of well-paying jobs to world-leading climate science, understanding the universe and our place within it, to technology transfers that make life easier for folks around the world,” NASA Administrator Bill Nelson said. “As we combat the coronavirus pandemic and promote environmental justice and sustainability, NASA technology is essential to address humanity’s greatest challenges.”
Spinoff 2022 features more than 45 companies using NASA technology to advance manufacturing techniques, detoxify polluted soil, improve weather forecasting, and even clean the air to slow the spread of viruses, including coronavirus.
"NASA's technology portfolio contains many innovations that not only enable exploration but also address challenges and improve life here at home," said Jim Reuter, associate administrator of the agency’s Space Technology Mission Directorate (STMD) in Washington. "We’ve captured these examples of successful commercialization of NASA technology and research, not only to share the benefits of the space program with the public, but to inspire the next generation of entrepreneurs."
This year in Spinoff, readers will learn more about:
How companies use information from NASA’s vertical farm to sustainably grow fresh produce
New ways that technology developed for insulation in space keeps people warm in the great outdoors
How a system created for growing plants in space now helps improve indoor air quality and reduces the spread of airborne viruses like coronavirus
How phase-change materials – originally developed to help astronauts wearing spacesuits – absorb, hold, and release heat to help keep race car drivers cool
A Survey on Security and Privacy Issues in Edge Computing-Assisted Internet o...DESMOND YUEN
Internet of Things (IoT) is an innovative paradigm
envisioned to provide massive applications that are now part of
our daily lives. Millions of smart devices are deployed within
complex networks to provide vibrant functionalities including
communications, monitoring, and controlling of critical infrastructures. However, this massive growth of IoT devices and the corresponding huge data traffic generated at the edge of the network created additional burdens on the state-of-the-art
centralized cloud computing paradigm due to the bandwidth and
resources scarcity. Hence, edge computing (EC) is emerging as
an innovative strategy that brings data processing and storage
near to the end users, leading to what is called EC-assisted IoT.
Although this paradigm provides unique features and enhanced
quality of service (QoS), it also introduces huge risks in data security and privacy aspects. This paper conducts a comprehensive survey on security and privacy issues in the context of EC-assisted IoT. In particular, we first present an overview of EC-assisted IoT including definitions, applications, architecture, advantages, and challenges. Second, we define security and privacy in the context of EC-assisted IoT. Then, we extensively discuss the major classifications of attacks in EC-assisted IoT and provide possible solutions and countermeasures along with the related research efforts. After that, we further classify some security and privacy issues as discussed in the literature based on security services and based on security objectives and functions. Finally, several open challenges and future research directions for secure EC-assisted IoT paradigm are also extensively provided.
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Nevertheless, it is an overstatement to say that
demography determines all, as it downplays the
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Intel Corporation (“Intel”) designs and manufactures
advanced integrated digital technology platforms that power
an increasingly connected world. A platform consists of
a microprocessor and chipset, and may be enhanced by
additional hardware, software, and services. The platforms
are used in a wide range of applications, such as PCs, laptops,
servers, tablets, smartphones, automobiles, automated
factory systems, and medical devices. Intel is also in the midst
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This report provides economic impact estimates for Intel in terms of employment, labor income, and gross domestic product (“GDP”) for the most recent historical year, 2019.1
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This whitepaper is a blueprint for developing an Open RAN solution. It provides an overview of the main
technology elements that Telefónica is developing
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Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
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Length: 30 minutes
Session Overview
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During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
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The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
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Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
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This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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2. TABLE OF
CONTENTS
5G Architecture View of Edge Computing......................................................1
Technologies & Standards: Definition and Work Related to Edge Computing ...........3
Use Cases Related to Mobile Edge Computing ................................................4
How Edge Computing Will Evolve the Communications Network ..........................8
Glossary - Definitions ...............................................................................9
3. 5G Architecture View of Edge Computing
Edge computing refers to locating applications – and the general-purpose compute, storage, and
associated switching and control functions needed to run them - relatively close to end users
and/or IoT endpoints. This greatly benefits applications performance and associated QoE, and it
can also improve efficiency and thus the economics depending on the nature of the specific
application.
Distributed edge computing is analogous to, and can be regarded as an extension of, the
evolution of content distribution over the last few decades. To improve the performance and
efficiency of delivering content – especially the video content dominating broadband traffic –
global CDN operators’ nodes are widely distributed down to network peering points, and in
many cases down to CDN appliances located well inside BIAS networks. Broadband service
providers also typically deploy distributed CDNs for their own in-network content distribution.
While distributed CDNs mostly revolve around storage caches, enabling applications with edge
compute extends this to both compute and storage, and the more general cloud service stack
necessary to on-board and run 3rd
party applications.
Enabling applications to be localized in edge compute close to end users first and foremost
improves network transit latency. Latency is a significant driver in improved performance as is
high reliability, e.g. through setting up radio bearers that allow low block error rate tolerance.
Edge compute combined with the optimized latency performance of 5G NR air interface and
5G Core processing can reduce round-trip-time by up to two orders of magnitude in situations
where there is tight control over all parts of the communication chain. This will enable new
classes of cloud applications, in such areas as industrial robotic/drone automation, V2X, and
AR/VR infotainment, and associated innovative business models.
Edge compute is also important for localization of data and efficient data processing. Industry
and Government regulations may require localization of data for security and privacy reasons.
Certain application scenarios may pose restrictions on the use of excessive transport bandwidth
or may require transport to external sites to be scheduled by time-of-day, requiring local storage
or caching of information. Additionally, there may need to be local processing of information to
reduce the volume of traffic over transport resources.
Edge clouds are expected to be deployed at different levels of distribution, which may be
phased in over time. Core data centers exist in networks today, typically at regional levels (a
4. 2
few per country), and will continue to host centralized network functions. Metro level edge
clouds, both network operator owned as well as operator-neutral entities, will host low latency
broad-based consumer and enterprise applications. ‘Far-edge clouds will be located within a
few 10’s of km of end users in network Central Offices or cell towers and will host ultra-low
latency and/or high reliability applications and may initially be targeted opportunistically at
high value industrial automation and IoT users. On-premise clouds sit within enterprise
locations and serve similarly stringent applications; they exist as fully-owned private clouds
today but are expected to increasingly be addressed by webscale cloud operators and network
operators extending their cloud capabilities to the very edge.
In addition to hosting new 5G era services, the other major network operator driver for edge
compute and edge clouds is deploying virtualized network infrastructure, replacing many
dedicated hardware-based elements with virtual network functions (VNFs) running on general
purpose edge compute. Even portions of access networks are being virtualized, and many of
these functions need to be deployed close to end users. The combination of these infrastructure
and applications drivers is a major reason that so much of 5G era network transformation
resolves around edge cloud distribution.
According to a new Gartner report1
, “Around 10% of enterprise-generated data is created and
processed outside a traditional centralized data center or cloud. By 2022, Gartner predicts this
figure will reach 75%”. Gartner defines edge computing as solutions that facilitate data
processing at or near the source of data generation. For example, in the context of the Internet
of Things (IoT), the sources of data generation are usually things with sensors or embedded
devices. Edge computing serves as the decentralized extension of the campus networks, cellular
networks, data center networks or the cloud.
1
https://www.gartner.com/smarterwithgartner/what-edge-computing-means-for-infrastructure-
and-operations-leaders/
5. 3
Technologies & Standards: Definition and Work Related to Edge Computing
Edge compute for 5G era networks builds on innovations from many different parts of the
information and communications technology (ICT) sector. Modern compute, storage and
switching technologies are, of course, the hardware foundation of any type of cloud
implementation. Cloud virtualization, orchestration and management software is similarly
essential to be able to offer and on-board any cloud services. And Software Defined
Networking (SDN) is also key to virtualize the interconnectivity of functions within and between
clouds.
More specifically for network edge clouds, Network Functions Virtualization (NFV) enables
cloud levels of dynamics and flexibility for network implementation, which in turn is a key
enabler for providing dynamic network slicing vital for 5G services. Many of these network
functions, as well as the applications running in the edge cloud, require hardware acceleration
(in the form of network processors, GPUs, ARM processor arrays, and/or even dedicated ASICs,
depending on functionality) to handle the high computational, signal processing, throughput
and low latency demands.
A key architectural innovation for the packet core (vEPC and 5GC) is ‘control & user plane
separation’ (CUPS), which allows multiple levels of user plane gateways corresponding to
multiple levels of edge cloud distribution and applications placement. Further, the ETSI Multi-
Access Edge Compute (MEC) ISG has defined enablement functions to support application
placement in distributed edge clouds. This includes an application hosting environment and
APIs to provide network intelligence to applications (e.g. current loading levels on different
access types, mobility event triggers for applications that need to transfer state to another
application instance in a new serving edge cloud).
6. 4
Use Cases Related to Mobile Edge Computing
Edge computing and processing aren’t new concepts, so why are we talking about the edge?
Existing and upcoming next-generation technologies such as the Internet of Things (IoT),
software-defined networking (SDN), blockchain, and 5G are fueling innovations in the
development of software applications across several industries. These emerging technologies
require massive amounts of near real-time computation to deliver content to users and relay
real-time data to centralized computing centers. To adapt and digitally transform, enterprises
must develop effective strategies for navigating the opportunities and challenges of edge
intelligence.
Edge computing brings multiple benefits to telecommunications companies2
:
• reducing backhaul traffic by keeping right content at the edge,
• maintaining Quality of Experience (QoE) to subscribers with edge processing,
• reducing TCO by decomposing and dis-aggregating access functions,
• reducing cost by optimizing the current infrastructure hosted in central offices with low cost
edge solutions,
• improving the reliability of the network by distributing content between edge and
centralized datacenters,
• creating an opportunity for 3rd party cloud providers to host their edge clouds on the telco
real estate.
The computational resources can be distributed geographically in a variety of location types
(e.g., central offices, public buildings, customer premises, etc.,) depending on the use case
requirements.
As more computing power is deployed in technologies at the network edge, it’s clear that
computing resources will become more widely distributed across the networking landscape.
Centralized cloud compute environments will continue to operate and will be augmented with
edge computing resources, which will be reliant on network capacity that supports edge
technologies’ traffic and services.
Enterprises are deriving benefits from edge computing in the form of enhanced security, lower
latency that enables faster analysis and decision-making, and more efficient utilization of
2
https://about.att.com/content/dam/innovationdocs/Edge_Compute_White_Paper%20FINAL2.pdf
7. 5
network capacity enabled by sending less data to the centralized data center for processing.
However, for these advantages to be achieved, network capacity needs to be easy to manage,
flexible and agile so it can be dimensioned to support the computing needs of the enterprise
efficiently.
As more computing power is sent to the network edge, it will need a foundation in order to be
utilized. A software-defined infrastructure may be the launch pad to a fully virtualized network
and functions. A virtualized network is dynamic, flexible and supports the rapid instantiation of
functions to support customer demands.
Many industry experts are pushing back on the notion that cloud and edge computing are in
competition with each other. Instead, forward-looking organizations and, even many public
cloud service providers, are beginning to consider how to selectively employ both. While cloud
adoption remains a critical focus for many organizations, a new era of connected devices is
simultaneously transferring data collection and computing power to the edge of networks.
Both cloud and edge computing have their advantages and challenges. The next hurdle for IT
teams is determining how to get the best of both. While cloud adoption remains a critical focus
for many organizations, a new era of connected devices is simultaneously transferring data
collection and computing power to the edge of networks.
Small-scale data centers offer another approach. By deploying these data centers in strategic
geographic locations, companies can move data processing closer to the end-user or device.
Doing so provides similar benefits as edge computing, while still maintaining the centralized
management benefits that enterprises love about the cloud.
The strategy is certainly gaining momentum. Sales of so-called micro-modular data centers
(MMDCs) may reach nearly $30 million this year, up from $18 million in 2017, according to
451 Research3
. The report notes that while the overall spend may seem small, MMDCs are
playing a significant role in thousands of expensive projects aimed at localizing computer
processing power.
Edge computing isn’t an all-or-nothing proposition. Centralized cloud services aren’t going
anywhere, but there is a need for complementary edge computing capabilities to enable next-
generation devices. It’s possible to process most important data at the edge, and then shift
3
https://www.networkworld.com/article/3238476/data-center/micro-modular-data-centers-set-
to-multiply.html
8. 6
remaining data to centralized facilities. A hybrid solution can allow an industry such as
financial services to thrive: edge technologies deliver real-time, fast experiences to customers
and provide the flexibility to meet industry requirements with centralized data storage.
For enterprises, the data deluge will continue. Going forward, edge technologies will often be
part of the solution stack for organizations overwhelmed by their computing needs – but likely
not the only answer.
Today’s applications – and those just on the horizon – are high-performance and power hungry.
They generate significant amounts of data and require real-time computing power. Consider
how much computation will be required to put self-driving cars on the road. Certain systems,
like braking, will be controlled by the car’s internal systems and require immediate responses.
With traditional networks, a device sends information to a data center that may be hundreds of
miles away. Data takes time to travel across large physical distances. As a result, delays can
occur. With edge computing, critical functions can be processed at the network’s edge in real-
time. Data from secondary systems, such as updating the car’s maps or managing the onboard
infotainment system, can be processed in the cloud.
Edge technologies make it feel like every device is a supercomputer. Digital processes become
lightning fast. Critical data is processed the edge of the network, right on the device. Secondary
systems and less urgent data are sent to the cloud and processed there. With SDN,
organizations have more flexibility to define rules on where and how data is processed to
optimize application performance and the user experience.
When paired with 5G, which promises faster speeds and lower latency, edge computing offers
a future with near real-time, back-and-forth connections.
Moving data processing closer to the network edge has security implications. With software-
defined networking, it’s possible to develop a multi-layered approach to security that takes the
communication layer, hardware layer and cloud security into consideration simultaneously.
There are multiple edge open source and standard initiatives (e.g., ONAP, Open Stack, ONF,
CNCF, ETSI MEC, OPNFV, Open Compute Project, LNF Akraino, 3GPP, etc.,) that are
converging to create an ecosystem that will support edge computing and services.
9. 7
Use cases where edge computing can bring new value4
:
• Autonomous Vehicles
o Self-driving cars need to be able to learn things without having to connect back to the
cloud to process data
o According to some third-party estimates, self-driving cars will generate as much as 3.6
terabytes of data per hour from the clusters of cameras and other sensors. Some functions
like braking, turning and acceleration will likely always be managed by the computer
systems in the cars themselves. But what if we could offload some of the secondary systems
to the cloud? These include things like updating and accessing detailed navigation maps.
• Industrial Automation
o Help create machines that sense, detect, learn things without having to be programmed
o Edge computing could spark the next generation of robotic manufacturing. The future 5G
service could play a vital role in what’s called "Industry 4.0 – Digital Manufacturing". The
anticipated low-latency wireless connections could eliminate traditional wired connections
to robotic assemblers. Updates come quicker. Products can get to market faster.
• Augmented reality (AR) and virtual reality (VR)
o Creating entirely virtual worlds or overlaying digital images and graphics on top of the real
world in a convincing way also requires a lot of processing power. Even when phones can
deliver that horsepower, the tradeoff is extremely short battery life.
o Edge computing addresses those obstacles by moving the computation into the cloud in a
way that feels seamless. It’s like having a wireless supercomputer follow you everywhere.
• Retail
o Creating more immersive in-store environments with technologies like AR
• Connected homes and offices
o Complete tasks like turning on lights on command or changing the temperature. With edge
computing, it will be possible for them to happen in near real-time
• Predictive Maintenance
o Help detect machines that are in danger of breaking, and find the right fix before they do
• Video monitoring
o Handle data at the edge rather than sending to the cloud
• Software-defined networking
o Require local processing to find the best route to send data at each point of the journey
• Fog computing
o Uses edge devices to connect to a distributed computing model
4
https://www.zdnet.com/google-amp/article/10-scenarios-where-edge-computing-can-bring-
new-value/
10. 8
How Edge Computing Will Evolve the Communications Network
Because of the twin drivers of network function virtualization and new latency sensitive end
user applications both requiring cloud infrastructure distributed to the edge of the network, edge
computing is having a central transformational impact on the way the networks are
implemented. Edge clouds will host virtualized access functions (e.g. Cloud RAN baseband
processing and control) and the core user plane and service chaining functions needed to
terminate traffic destined for applications present at each cloud level.
It is likely that the low latency - high reliability applications at the metro cloud level, and the
ultra-low latency/high reliability applications at the far-edge and on-premise levels, will
represent only a fraction of overall applications. The larger share of relatively latency-
insensitive generic applications is expected to continue to be hosted in large centralized clouds
with their economies of scale. However, the more specialized 5G era applications promise to
be high value use cases that will drive innovative business models and new transformative
value creation. An implication of this is that partnership business models between ‘application
and content providers’ (ACPs) and network providers and/or edge cloud providers will become
very important to realizing this new 5G era services potential.
11. 9
Glossary - Definitions
Term Description
2G Second Generation Mobile Network
3G Third Generation Mobile Network GSM
3GPP Third Generation Partnership Project
4G Fourth Generation Mobile Network
5G Fifth Generation Mobile Network
5G NR 5G New Radio
5GC 5G Core Network
5GNB Fifth Generation NodeB
5GPPP Fifth Generation Private Public Partnership
5GS Fifth Generation System IMT
ACP Application and Content Provider
API Application Program Interface
AR Augmented Reality
ARM Advanced RISC Machine
ASIC Application-Specific Integrated Circuit
BIAS Broadband Internet Access Service
CDN Content Delivery Network
CNCF Cloud Native Computing Foundation
CUPS Control Plane – User Plane Separation
ETSI European Telecommunications Standards Institute
fog extended concept of cloud computing at the network edge
GPU Graphics Processing Unit
ICT Information and Communications Technology
IoT Internet of Things
ISG Industry Specification Group (ETSI)
LNF Akraino Linus Foundation Software Stack Supporting
High-Availability Cloud Services Optimized for Edge
MEC Multi-Access Edge Compute
12. 10
MMDC Micro-Modular Data Center
NFV Network Function Virtualization
ONAP Open Networking Automation Platform
ONF Open Networking Foundation
OPNFV Open Platform for Network Function Virtualization
OTT Over the Top
PSTN Public Switched Telephone Network
QoE Quality of Experience
QoS Quality of Service
RAN Radio Access Network
SDN Software-Defined Network
TCO Total Cost of Ownership
TDM Time Division Multiplexing
V2X Vehicle to Vehicle or Infrastructure
vEPC virtual Evolved Packet Core
VLAN Virtual Local Area Network
VNF Virtual Network Function
VPN Virtual Private Network
VR Virtual Reality