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Fog computing
- 1. FOG COMPUTING Prepared byAbdul Qadir
- 2. prepared by PrashanthPeddabbu
- 3. FOG COMPUTING Conceptthat is given by SISCO (on January 2014) which extends the concept of Cloud Computing but at the edge level. Fog Computing, Edge Computing, Mist Computing, Fogging or Cloudlets Fog computing is making use of decentralized servers in between network core and network edge for data processing and to serve the immediate requirements of the end systems. Processing and storing of data between Cloud and End device Fog computing is a way of providing compute and storage services more immediately and close to physical devices Prepared by Abdul Qadir
- 4. FOG COMPUTING FogComputing virtualized platform that provides compute, storage and networking services between end devices and traditional clouds It is a paradigm that extends the cloud computing services to the edge of the network to adjust the emerging IoT vision. Cloud environment may be geographically a long way away from the organization and rely heavily on the wider internet bandwidth Fog services are much closer to the end user Fog Computing reduce the need of the bandwidth by not sending every bit of information over Cloud channels The metaphor fog comes from the meteorological term for a cloud close to the ground, just as fog concentrates on the edge of the network Prepared by Abdul Qadir
- 5. FOG NODES Networkedge: applications and hosts, routers close to end systems in the internet; Network core: interconnected routers in the internet, network of networks fog nodes can be deployed anywhere with a network connection: on a factory floor, on top of a power pole, Any device with computing, storage, and network connectivity can be a fog node. Examples include industrial controllers, switches, routers, embedded servers, and Prepared by Abdul Qadir
- 6. CLOUD COMPUTING Prepared byAbdul Qadir
- 7. FOG COMPUTING Prepared byAbdul Qadir
- 8. FOG COMPUTING prepared byAbdul Qadir
- 9. NEED FOR FOGCOMPUTING Iot is generating unprecedented volume and variety of data, by the time it makes to the cloud for analysis, the opportunity to act upon the data might be gone. Loads of useless data are been pushed to the cloud. Fog filters out and sends useful data to clouds. Why can’t do all in cloud? Cloud computing frees the enterprise and the end user from many details. This bliss becomes a problem for latency-sensitive applications. Why can’t do all in end systems? Physical constraints: Energy, space, etc., Prepared by Abdul Qadir
- 10. Does this replacethe Cloud? Prepared by Abdul Qadir
- 11. THINGSTO REMEMBER Fogcomputing is non-trivial extension of Cloud computing paradigm to the edge of the network. In a fog environment, the processing takes place in a data hub on a smart device, or in a smart router or gateway, thus reducing the amount of data sent to the cloud. It is important to note that fog networking complements—not replaces—cloud computing; fogging allows for short-term analytics at the edge, and the cloud performs resource-intensive, longer-term analytics. Prepared by Abdul Qadir
- 12. USE CASE 1:A SMARTTRAFFIC LIGHT SYSTEM(STLS) System Outline: STLS calls for deployment of a STL at each intersection. The STL is equipped with sensors that 1. Measure the distance and speed of approaching vehicles from every direction. 2. Detect presence of pedestrians/other vehicles crossing the street. - Issues “Slow down” warnings to vehicles at risk to crossing in red and even modifies its own cycle to prevent collisions. Prepared by Abdul Qadir
- 13. STLS: SYSTEM OUTLINECONTINUED.. STLS has 3 major goals: 1. Accidents prevention 2. Maintenance of steady flow of traffic(green waves along the main roads) 3. Collection of relevant data to evaluate and improve the system Note: Goal (1) requires real-time reaction, (2) near-real time, and (3) relates to the collection and analysis of global data over long periods. Prepared by Abdul Qadir
- 14. KEY REQUIREMENTS DRIVENBY STLS 1. Local Subsystem latency:- Reaction time needed is in the order of < 10 milliseconds 2. Interplay with the cloud:- Data must be injected into a Data center/ cloud for deep analysis to identify patterns in traffic, city pollutants. Prepared by Abdul Qadir
- 15. KEY ATTRIBUTES OFFOG COMPUTING The Use Cases that were discussed brings up a # of attributes that differentiate Fog computing platform from the Cloud. Applications that require very low and predictable latency. (STLS, SCV) Geo-distributed applications (pipeline monitoring, STLS) Fast mobile applications (Smart connected vehicle, rail) Large-scale distributed control systems (STLS, smart grid) IoT also brings Big Data with a twist: rather than high volume, the number of data sources distributed geographically Prepared by Abdul Qadir
- 16. USE CASES SmartHome and Cities Fog Computing enables getting sensors data at all levels of the activities of homes as well as from the entire cities, integrating the mutually independent network entities within the homes and cities and faster processing to create more adaptive user environments for better human conditions and quality of living. Connected vehicles Fogging provides an ideal architecture for vehicle-to-vehicle (V2V) communication, because of proximity of devices embedded in cars, roads and access points. Fogging, with context awareness, makes real-time interactions between cars, access points and traffic lights much safer and more efficient. Prepared by Abdul Qadir
- 17. CLOUD COMPUTINGVERSUS FOG COMPUTING Cloud Computing is the practice of using a network of remote servers hosted on the internet to store, manage and process data A generic term for anything that involves delivering hosted services over the internet It is a paradigm based on pay as you go. Cloud based Service (SaaS, PaaS, IaaS) Prepared by Abdul Qadir
- 18. CLOUD BENEFITS Costsaving with respect to capital investment reduction in cost with respect to developing and delivering IT services Reduction in management responsibilities, personnel focus only on production Increased business agility to allow enterprise to meet the needs of rapidly changing markets On demand self service Resource pooling (hardware, software, processing, network, bandwidth) Rapid elasticity and scalability Measured provision to optimize resource allocation Prepared by Abdul Qadir
- 19. CLOUD BASED SERVICES Storage-as-a-Service Database-as-a-Service Security-as-a-Service Communication-as-a-Service Management/Governance-as-a-Service Integration-as-a-Service Testing-as-a-Service Business-as-a-Service Prepared by Abdul Qadir
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- 22. FOGVERSUS EDGE COMPUTING Often mean the same architecture the main difference is to do with exactly where the intelligence and processing are placed. Fog Computing pushes intelligence down to the local area network level of the network architecture, processing data in a Fog node or the IoT gateway Edge Computing places the intelligence, processing and communication capabilities of an Edge gateway directly into the smart devices In Fog Computing, there is a single centralised device responsible for processing data from different end-points in the network In the Edge architecture, IoT data is collected and analysed directly by the connected devices Prepared by Abdul Qadir
- 23. ADVANTAGES OF FOG Preparedby Abdul Qadir
- 24. FUTURE OF FOGCOMPUTING “Fog as a Service” (FaaS) Prepared by Abdul Qadir
- 25. FUTURE OF FOGCOMPUTING “Fog as a Service” (FaaS), where a service provider builds out an array of fog nodes across its geographic footprint Each fog node hosts local computation, networking, and storage capabilities The nodes can be packaged for outdoor deployment, perhaps in street corner cabinets, on rooftops. fog computing is going to be a key enabler for future IoT service infrastructures—and Fog as a Service will be a key opportunity for service providers Prepared by Abdul Qadir
- 26. Having aworld-class fog network directly attached to a traditional mobile network opens up vast revenue opportunities Fog is a multi-billion dollar opportunity for network service revenue, and a “network killer” if your fog deployment falls behind competing networks’ fog capabilities. (Copied) https://blogs.cisco.com/innovation/huge-opportunities-for-service- providers-at-the-intersection-of-fog-and-mobility Prepared by Abdul Qadir
- 27. OPENFOG CONSORTIUM TheOpenFog Consortium was founded in November 2015 by members from Cisco, Dell, Intel, Microsoft, ARM and Princeton University; its mission is to develop an open reference architecture and convey the business value of fog computing. https://www.openfogconsortium.org/ Prepared by Abdul Qadir
- 28. CONCLUSION: We lookedat Fog computing and key aspects of it. How fog complements and extends cloud computing. We looked at use cases that motivated the need for fog. Seen a high-level description of Fog’s architecture. Fog Computing aims to reduce processing burden of cloud computing. Fog computing is bringing data processing, networking, storage and analytics closer to devices and applications that are working at the network’s edge. that’s why Fog Computing today’s trending technology mostly for IoT Devices. Prepared by Abdul Qadir
- 29. Thank you Prepared byAbdul Qadir
Editor's Notes
- #3 No of end devices that are connected to internet are expected to rise above 50+ billion by 2020. cloud computing architectures won’t be able to handle the demand of the Internet of things So only cloud is not the optimal solution to handle this massive explosion. Fog is needed in between to optimize – need for an interplay of cloud and fog.
- #7 By now everyone knows what cloud computing is? May years ago the IoT started its communication with the centralized server in the cloud like this, as shown in the figure. Basically it is making use of Centralized servers hosted in the core internet rather than using a local sever or personal system for huge processing/computation or storage of data. In the present times almost all the organizations uses cloud.
- #8 Fog computing is making use of decentralized servers in between network core and network edge for data processing and to serve the immediate requirements of the end systems. Does this replace the cloud? No, Fog computing is non-trivial extension of Cloud computing paradigm to the edge of the network. Network edge: applications and hosts, routers close to end systems in the internet; Network core: interconnected routers in the internet, network of networks fog nodes can be deployed anywhere with a network connection: on a factory floor, on top of a power pole, alongside a railway track, in a vehicle, or on an oil rig. Any device with computing, storage, and network connectivity can be a fog node. Examples include industrial controllers, switches, routers, embedded servers, and video surveillance cameras.
- #9 Fog Computing typically involves components of an application running both in Cloud as well as in the Edge Devices in the Fog
- #10 Iot is generating unprecedented volume and variety of data, by the time it makes to the cloud for analysis, the opportunity to act upon the data might be gone. Also, Loads of useless data are been pushed to the cloud. Fog filters out and sends useful data to clouds. Anyway, these are a few examples, we see key attributes of fog computing later in the slides. End systems might be sensors, actuators could be stolen.
- #13 STLS: smart traffic light system STLS is a small piece of the full-fledged system envisioned by smart connected vehicle(SCV). Meaning… Anyway, the system outline…
- #14 May be to give idea: https://www.youtube.com/watch?v=kh7X-UKm9kw To be effective, the local control loop subsystem must react within a few milliseconds – thus illustrating the role of the Fog in supporting low latency applications.
- #15 Orchestration is the automated arrangement, coordination, and management of computer systems, middleware, and services. Orchestration also provides centralized management of the resource pool, including billing, metering, and chargeback for consumption. For example, orchestration reduces the time and effort for deploying multiple instances of a single application. And as the requirement for more resources or a new application is triggered, automated tools now can perform tasks that previously could only be done by multiple administrators operating on their individual pieces of the physical stack
- #16 These attributes do not apply uniformly to every use case. Mobility, for instance, a critical attribute in Smart Connected Vehicle and Connected Rail, plays no role in STLS and Wind Farm cases. Analyzing data close to the device that collected the data can make the difference between averting disaster and a cascading system failure.
- #18 Only certain useful data is being sent to the cloud from fog for further processing, instead of bombarding clouds with irrelevant data.
- #23 Latency and delay are intrinsically linked and sometimes interchangeably used. However, they are not always the same. Delay is the time it takes for data to travel from one endpoint to another. Latency, though, may be one of two things. Latency is sometimes considered the time a packet takes to travel from one endpoint to another, the same as the one-way delay. More often, latency signifies the round-trip time. Round-trip time encompasses the time it takes for a packet to be sent plus the time it takes for it to return back. This does not include the time it takes to process the packet at the destination