In this video on Edge Computing, you will learn what is edge computing, the Origin of edge computing, how edge computing works, edge computing benefits, and a lot more interesting concepts.
Edge IoT is a technology Witekio believes in. It is now reaching an inflexion point. The need for responsiveness, local computing capacity (especially for data crunching, AI and machine learning), security, IoT bandwidth makes this«trend » relevant to face B2B and industrial challenges.
Through this presentation, you will get to know about Edge computing and explore the fields where it is needed.
You can start exploring the technical knowledge by seeing what industries are working on now-days
Gartner defines edge computing as "a part of a distributed computing topology in which information processing is located close to the edge - where things and people produce or consume that information."
In other words, it brings and gathers information and data nearer to the device, so that latency issues could be solved.
Edge IoT is a technology Witekio believes in. It is now reaching an inflexion point. The need for responsiveness, local computing capacity (especially for data crunching, AI and machine learning), security, IoT bandwidth makes this«trend » relevant to face B2B and industrial challenges.
Through this presentation, you will get to know about Edge computing and explore the fields where it is needed.
You can start exploring the technical knowledge by seeing what industries are working on now-days
Gartner defines edge computing as "a part of a distributed computing topology in which information processing is located close to the edge - where things and people produce or consume that information."
In other words, it brings and gathers information and data nearer to the device, so that latency issues could be solved.
Edge computing is becoming a key architectural component for industrial IoT deployments. Gartner Group identifies edge computing as one of their top Tech Trends for 2019. The opportunity to process data at the edge of the network, closer to the sensors and actuators, before data is sent to the cloud results in improved security, more efficient data movement, and better performance for industrial IoT use cases.
This presentation will explore three aspects of edge computing:
The benefits of edge computing for industrial IoT use cases
The key features delivered in edge computing solutions
A survey of different edge computing options available to customers.
A talk presented at IEEE ComSoc workshop on Evolution of Data-centers in the context of 5G.
Discuss about what is edge computing and management issues in Edge Computing
The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge computing. Finally, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction.
Edge computing refers to the enabling technologies allowing computation to be performed at the edge of the network, on downstream data on behalf of cloud services and upstream data on behalf of IoT services. Here we define “edge” as any computing and network resources along the path between data sources and cloud data centers. For example, a smart phone is the edge between body things and cloud, a gateway in a smart home is the edge between home things and cloud, a micro data center and a cloudlet is the edge between a mobile device and cloud. The rationale of edge computing is that computing should happen at the proximity of data sources. From our point of view, edge computing is interchangeable with fog computing, but edge computing focus more toward the things side, while fog computing focus more on the infrastructure side. Edge computing could have as big an impact on our society as has the cloud computing.
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider. For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network .This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
Edge computing allows data produced by internet of things (IoT) devices to be processed closer to where it is created instead of sending it across long routes to data centers or clouds.
Doing this computing closer to the edge of the network lets organizations analyze important data in near real-time – a need of organizations across many industries, including manufacturing, health care, telecommunications and finance.Edge computing deployments are ideal in a variety of circumstances. One is when IoT devices have poor connectivity and it’s not efficient for IoT devices to be constantly connected to a central cloud.
Other use cases have to do with latency-sensitive processing of information. Edge computing reduces latency because data does not have to traverse over a network to a data center or cloud for processing. This is ideal for situations where latencies of milliseconds can be untenable, such as in financial services or manufacturing.
legal issues in cloud computing,cloud computing and law,cyberlaw and cloud computing in india,prashant mali,cloud computing issues,cloud computing security
IoT Meets the Cloud: The Origins of Edge ComputingMaria Gorlatova
History of edge computing: IoT meets the cloud. Lecture delivered as part of Duke University Electrical and Computer Engineering / Computer Science Special Topics course on Edge Computing designed and developed by the instructor.
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This ppt contains everything about Edge Computing Starting from its Definition, needs, terms involved to its merits, demerits and application use cases
The term “fog computing” or “edge computing” means that rather than hosting and working from a centralized cloud, fog systems operate on network ends. It is a term for placing some processes and resources at the edge of the cloud, instead of establishing channels for cloud storage and utilization.
Edge computing is a method of enabling small processing units near to the source of the data from sensors and central data servers. It utilizes cloud computing systems by performing data processing at the edge of the network, near the source of the data. This reduces the communications bandwidth needed between sensors by performing analytics and data processing.
Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks.
Edge Computing: An Extension to Cloud ComputingRamneek Kalra
This presentation was shared by Shally Gupta (PhD Research Scholar | IEEE Graduate Member) & Ramneek Kalra (IEEE Impact Creator) at IEEE MRU Student Branch, Faridabad, Haryana, India.
Edge computing is becoming a key architectural component for industrial IoT deployments. Gartner Group identifies edge computing as one of their top Tech Trends for 2019. The opportunity to process data at the edge of the network, closer to the sensors and actuators, before data is sent to the cloud results in improved security, more efficient data movement, and better performance for industrial IoT use cases.
This presentation will explore three aspects of edge computing:
The benefits of edge computing for industrial IoT use cases
The key features delivered in edge computing solutions
A survey of different edge computing options available to customers.
A talk presented at IEEE ComSoc workshop on Evolution of Data-centers in the context of 5G.
Discuss about what is edge computing and management issues in Edge Computing
The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge computing. Finally, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction.
Edge computing refers to the enabling technologies allowing computation to be performed at the edge of the network, on downstream data on behalf of cloud services and upstream data on behalf of IoT services. Here we define “edge” as any computing and network resources along the path between data sources and cloud data centers. For example, a smart phone is the edge between body things and cloud, a gateway in a smart home is the edge between home things and cloud, a micro data center and a cloudlet is the edge between a mobile device and cloud. The rationale of edge computing is that computing should happen at the proximity of data sources. From our point of view, edge computing is interchangeable with fog computing, but edge computing focus more toward the things side, while fog computing focus more on the infrastructure side. Edge computing could have as big an impact on our society as has the cloud computing.
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider. For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network .This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
Edge computing allows data produced by internet of things (IoT) devices to be processed closer to where it is created instead of sending it across long routes to data centers or clouds.
Doing this computing closer to the edge of the network lets organizations analyze important data in near real-time – a need of organizations across many industries, including manufacturing, health care, telecommunications and finance.Edge computing deployments are ideal in a variety of circumstances. One is when IoT devices have poor connectivity and it’s not efficient for IoT devices to be constantly connected to a central cloud.
Other use cases have to do with latency-sensitive processing of information. Edge computing reduces latency because data does not have to traverse over a network to a data center or cloud for processing. This is ideal for situations where latencies of milliseconds can be untenable, such as in financial services or manufacturing.
legal issues in cloud computing,cloud computing and law,cyberlaw and cloud computing in india,prashant mali,cloud computing issues,cloud computing security
IoT Meets the Cloud: The Origins of Edge ComputingMaria Gorlatova
History of edge computing: IoT meets the cloud. Lecture delivered as part of Duke University Electrical and Computer Engineering / Computer Science Special Topics course on Edge Computing designed and developed by the instructor.
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This ppt contains everything about Edge Computing Starting from its Definition, needs, terms involved to its merits, demerits and application use cases
The term “fog computing” or “edge computing” means that rather than hosting and working from a centralized cloud, fog systems operate on network ends. It is a term for placing some processes and resources at the edge of the cloud, instead of establishing channels for cloud storage and utilization.
Edge computing is a method of enabling small processing units near to the source of the data from sensors and central data servers. It utilizes cloud computing systems by performing data processing at the edge of the network, near the source of the data. This reduces the communications bandwidth needed between sensors by performing analytics and data processing.
Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks.
Edge Computing: An Extension to Cloud ComputingRamneek Kalra
This presentation was shared by Shally Gupta (PhD Research Scholar | IEEE Graduate Member) & Ramneek Kalra (IEEE Impact Creator) at IEEE MRU Student Branch, Faridabad, Haryana, India.
What Is Edge Computing? Everything You Need to KnowDigital Carbon
Edge computing is transforming the way we process and utilize data in the era of 5G. This groundbreaking technology is redefining the rules for businesses by bringing computing resources closer to the data source, reducing latency, and enabling real-time decision-making.
IoT Building Blocks_ From Edge Devices to Analytics in the Cloud Amazon Web Services
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Implementing Multi-Region AWS IoT, ft. Analog Devices (IOT401) - AWS re:Inven...Amazon Web Services
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Top 5 In-demand technologies to Learn in 2020Intellipaat
Intellipaat Online Courses on top trending IT technologies : https://intellipaat.com/course-cat/big-data-analytics-courses/
Expert written Tutorials : https://intellipaat.com/blog/tutorials/
Latest Blogs : https://intellipaat.com/blog/blog-category/
Top 5 In-demand Technologies to Learn in 2020Intellipaat
Youtube Link : https://www.youtube.com/watch?v=-tmEE2KsvzM
Intellipaat Online Courses on top trending IT technologies : https://intellipaat.com/course-cat/big-data-analytics-courses/
Expert written Tutorials : https://intellipaat.com/blog/tutorials/
Latest Blogs : https://intellipaat.com/blog/blog-category/
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Cloud is all the buzz...what is it really?!?!Michael Maharas
I'm sure that you've had the word "cloud" lobbed towards you many times in the past couple years. However not all cloud is created equal. So rather than only share all the ways AT&T's cloud is among the best. I am going to share a deck which will shed some much needed light on what cloud is and why it's going to be vital to your business
Level: Introductory
The infinite computing power of cloud is creating new business models and driving operational efficiencies in every sector. But how can you extend cloud capabilities to the edge? Join this webinar for real-world examples of how AWS customers are exploiting both IoT data and the power of the cloud. We'll also discuss how you can deploy analytics and machine learning at the edge through AWS building blocks such as AWS Greengrass and Amazon Sagemaker.
Customer use cases to be explored include:
- Nokia optimises communications to oil platforms by processing data nearer to the source
- Stanley Black&Decker performs predictive maintenance by identifying faulty parts before they fail
- Pentair overcomes intermittent connectivity issues to automate its water filtration plants
Who Should Attend: Business Directors, Business Leaders, Project Managers, IT Managers, Business Consultants, Heads of Innovation, Data Scientists and Product Marketeers.
In this presentation, Derek Granath from Extreme Networks presents: Accelerating HPC with Ethernet.
"High Performance Computing (HPC) requires high-speed, high bandwidth, low latency network infrastructures. Converged Ethernet networks are now displacing dedicated compute, storage and data networks of the past in today's HPC deployments. Top industry institutions; petroleum, human genome, finance and universities have partnered with Extreme Networks to solve their toughest HPC networking challenges."
Learn more: http://extremenetworks.com
Watch the video presentation: http://insidehpc.com/2013/12/13/slidecast-accelerating-hpc-ethernet/
Presentation from OpenStack Summit Tokyo
Online video link is below.
https://www.openstack.org/summit/tokyo-2015/videos/presentation/approaching-open-source-hyper-converged-openstack-using-40gbit-ethernet-network
Application developers are key to the success of an edge compute strategy. They are the backbone for any digital ecosystem and their requirements drive the platform architecture. Edge computing is no different. In this talk, we will focus on some key requirements, challenges and possible solutions for a developer centric architecture for multi-access edge computing including abstraction of the service provider’s network complexity, low footprint cloud native builder models, micro-services, hardware abstractions, intelligence layers and massive monitoring of application instances.
About the speaker: Shamik Mishra is currently Assistant Vice President (AVP), Technology and Innovation at Aricent. He is a practice leader for new product architectures. He has extensive experience and contributions in software development in cloud, wireless technologies, edge computing and platform software. His research interests are Network Function Virtualization (NFV), Cloud and edge computing and Machine Learning (ML). He has spoken in several conferences and his work is regularly covered in the media. Shamik has a bachelor’s and a master’s degree from Indian Institute of Technology (IIT) Kharagpur, India.
In a world of business that has increasingly become more and more distributed, and with our relationship with data having changed, we need to begin expanding the way we look at innovation in IT from solely focusing on the data center, to considering the requirements, challenges and costs associated with the edge. This presentation focuses on extending data center investments to all remote sites, and new opportunities to connect IT with today's business requirements through a Software-Defined Edge.
IoT is one of the biggest topics in IT system today.
In this session, we will discuss how we can achieve an effective IoT system on OpenStack.
Firstly we'll describe IoT use cases, and summarize some generic requirements for IoT backend.
Secondly, we'll present our reference design of IoT backend on OpenStack IaaS.
Finally, we'll discuss the result of fit and gap analysis of OpenStack itself as a platform for IoT backend.
This session includes following items.
* What kind of components we need to enable IoT backend
* How to design and create network model to gather up all data from distributed sources
* How to support flexible data gathering, storing and processing of massive data
* How to achieve multi-tenanty required for IoT platform
https://openstacksummitoctober2015tokyo.sched.org/event/0ca80f968b4e1e3dd23137405a7deb15#.VjSxm2s3LJA
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4. Copyright Intellipaat. All rights reserved.
Agenda
02 Origin of Edge
Computing
01 What is Edge Computing?
5. Copyright Intellipaat. All rights reserved.
Agenda
02 Origin of Edge
Computing
03 How does Edge Computing
Work?
01 What is Edge Computing?
6. Copyright Intellipaat. All rights reserved.
Agenda
02 Origin of Edge
Computing
03 How does Edge Computing
Work?
01 What is Edge Computing?
04 Edge Computing use cases and
examples
7. Copyright Intellipaat. All rights reserved.
Agenda
02 Origin of Edge
Computing
03 How does Edge Computing
Work?
01 What is Edge Computing?
04 Edge Computing use cases and
examples
05 Benefits and challenges of Edge
Computing
9. Copyright IntelliPaat, All rights reserved
What is Edge Computing?
As the name suggests, the client data is processed at the edge of the network as close as
possible. The computing of data is performed where it is generated.
13. Copyright IntelliPaat, All rights reserved
How does Edge Computing Work?
If you can't get the data closer to the data center, get
the data center closer to the data.
“
”
14. Copyright IntelliPaat, All rights reserved
How does Edge Computing Work?
If you can't get the data closer to the data center, get
the data center closer to the data.
“
”
15. Copyright IntelliPaat, All rights reserved
How does Edge Computing Work?
Edge computing puts storage and servers where the
data is, often requiring a partial rack of gear to
operate on the remote LAN to collect and process
the data locally.
24. Copyright IntelliPaat, All rights reserved
Benefits of Edge Computing
Autonomy
• Ex - oil rigs, ships at
sea, remote farms,
rainforest or desert.
• Compute work on site
or using edge device.
• Reduced amount of
data to be sent.
25. Copyright IntelliPaat, All rights reserved
Benefits of Edge Computing
Autonomy
• Ex - oil rigs, ships at
sea, remote farms,
rainforest or desert.
• Compute work on site
or using edge device.
• Reduced amount of
data to be sent.
Data Sovereignty
• Long Data journey can
pose problems for
data security.
• Edge computing keeps
data close to its
source.
• securing any sensitive
data before sending.
26. Copyright IntelliPaat, All rights reserved
Benefits of Edge Computing
Autonomy
• Ex - oil rigs, ships at
sea, remote farms,
rainforest or desert.
• Compute work on site
or using edge device.
• Reduced amount of
data to be sent.
Data Sovereignty Edge Security
• Long Data journey can
pose problems for
data security.
• Edge computing keeps
data close to its
source.
• securing any sensitive
data before sending.
• Edge implement and
ensure data security.
• Safety and security of
data after leaving the
edge.
• Secured through
encryption, and can
be hardened against
hackers.
28. Copyright IntelliPaat, All rights reserved
Challenges of Edge Computing
Limited Capability
Deploying an infrastructure
at the edge can be
effective, but the scope and
purpose of the edge
deployment must be clearly
defined
29. Copyright IntelliPaat, All rights reserved
Challenges of Edge Computing
Connectivity
It's critical to design an
edge deployment that
accommodates poor or
erratic connectivity and
consider what happens at
the edge when connectivity
is lost.
30. Copyright IntelliPaat, All rights reserved
Challenges of Edge Computing
Security
It's vital to design an edge
computing deployment
that will emphasize proper
device management. Edge
security isn't automatic
when building an edge site
from scratch.
31. Copyright IntelliPaat, All rights reserved
Challenges of Edge Computing
Data Lifecycle
The problem with today's
data glut is that so much of
that data is unnecessary.
Most of the data involved in
real-time analytics is short-
term data that isn't kept
over the long term.