2. Whereas the cloud is "up there" in the sky somewhere, distant and remote and
deliberately abstracted. The "fog" is close to the ground, right where things are
getting done.
Just like the cloud, fog computing is expected to open new business models.
But what a fog computing is?
3. EXISTING SYSTEM
CLOUD COMPUTING
In past couple of years, the main idea was given to build mega
data center architecture with the demand of centralized
computing services called centralize cloud computing (CC)
model.
Examples of cloud computing are:
Google, Amazon, IBM, and Microsoft Azure.
Cloud computing has provided many opportunities for
enterprises by offering their customer a range of computing
services. Current “pay as you go” Cloud computing model
becomes an efficient alternative to owning and managing
private data centres for customers facing Web Applications.
4. PROBLEMS WITH CLOUD COMPUTING
As the Internet of Things grows, businesses face a growing need to analyze data from sources at the edge of a network, whether mobile phones,
gateways, or IoT sensors. Cloud computing has a disadvantage:
➢It can’t process data quickly enough for modern business applications. The IoT owes its explosive growth to the connection of physical things
and operation technologies (OT) to analytics and machine learning applications, which can help glean insights from device-generated data and
enable devices to make “smart” decisions without human intervention. Currently, such resources are mostly being provided by cloud service
providers, where the computation and storage capacity exists.
➢ However, despite its power, the cloud model is not applicable to environments where operations are time-critical or internet connectivity is poor.
This is especially true in scenarios such as telemedicine and patient care, where milliseconds can have fatal consequences.
➢The same can be said about vehicle to vehicle communications, where the prevention of collisions and accidents can’t afford the latency caused
by the roundtrip to the cloud server. “The cloud paradigm is like having your brain command your limbs from miles away — it won’t help you
where you need quick reflexes.”
➢Moreover, having every device connected to the cloud and sending raw data over the internet can have privacy, security and legal implications,
especially when dealing with sensitive data that is subject to separate regulations in different countries. IoT nodes are closer to the action, but for
the moment, they do not have the computing and storage resources to perform analytics and machine learning tasks. Cloud servers, on the other
hand, have the horsepower, but are too far away to process data and respond in time.
5. PROPOSED SYSTEM
➢Fog computing
or fog networking, also known as fogging, is an architecture that uses
edge device to carry out a substantial amount of computation, storage,
and communication locally and routed over the Internet backbone.
➢Fog computing is a decentralized computing infrastructure in which
data, compute, storage and applications are located somewhere
between the data source and the cloud. Like edge computing, fog
computing brings the advantages and power of the cloud closer to
where data is created and acted upon. Many people use the terms fog
computing and edge computing interchangeably because both involve
bringing intelligence and processing closer to where the data is
created. This is often done to improve efficiency, though it might also
be done for security and compliance reasons.
➢ CISCO recently delivered the vision of fog computing to enable
applications on billions of connected devices, already connected in
the Internet of Things (IoT), to run directly at the network edge.
Customers can develop, manage and run software applications on
Cisco IOx framework of networked devices, including hardened
routers, switches and IP video cameras. Cisco IOx brings the open
source Linux and Cisco IOS network operating system together in a
single networked device (initially in routers).
Data Centres
End-Devices
Nodes
7. HOW FOG COMPUTING WORKS
Fog networking complements -- doesn't replace -- cloud computing; fogging enables short-term analytics at the edge,
while the cloud performs resource-intensive, longer-term analytics.
Fog computing uses the concept of ‘fog nodes.’ These fog nodes are located closer to the data source and have higher
processing and storage capabilities. Fog nodes can process the data far quicker than sending the request to the cloud
for centralized processing.
The cloud is getting cluttered due to the enormous number of devices connecting to the internet. Since cloud
computing is not viable in some cases, it has become necessary to use fog computing for IoT devices. It can handle
the enormous data generated by these devices.
When implemented, fog-empowered devices locally analyze time-critical data that includes alarm status, device
status, fault warnings, and so on. This minimizes latency and prevents major damage. Fog computing can effectively
reduce the amount of bandwidth required, which in turn speeds up the communication with the cloud and various
sensors.
8. WHEN TO USE FOG COMPUTING?
Fog Computing can be used in the following scenarios:
➢It is used when only selected data is required to send to the cloud. This selected data is chosen for long term storage
and is less frequently accessed by the host.
➢It is used whenever a large number of services need to be provided over a large area at different geographical
locations.
➢Devices that are subjected to rigorous computations and processing's must use fog computing.
➢Real-world examples where fog computing is used are in IoT devices (e.g. Car-to-Car communication), Devices
with Sensors, Cameras (IIoT-Industrial Internet of Things), etc.
9. STEP-BY-
STEP FOG
COMPUTING
PROCESS:
Signals are wired from IoT
devices to an automation
controller which executes
a control system program
to automate those
devices.
A control system program
wires data through a
protocol gateway.
Data is converted into a
protocol such as HTTP so
that it can be understood
easily by internet-based
services.
A fog node collects the
data for further analysis.
It filters the data and saves
it for later use.
10. Cloud Architecture with and without Fog Computing
Cloud Architecture before the advent of fog computing
Cloud Architecture after the advent of fog computing
11. FOG COMPUTING CHARACTERISTICS
1. Geographical distribution:
The services and application
objective of the fog is widely
distributed.
2. Support for mobility:
Fog devices provide mobility
techniques like decouple host
identity to location identity.
3. Real time interactions:
Fog computing requires real
time interactions for speedy
service.
4. Heterogeneity:
Fog nodes can be deployed in a
wide variety of environments.
5. Interoperability Fog
components must be able to
interoperate in order to give
wide range of services like
streaming.
6. Decentralization:
The fog computing
architecture is decentralized.
There is no central server to
manage computing resources
and services. Therefore, fog
nodes are self-organizing and
collaborate to provide end
users with real-time IoT
applications
Save storage space:
Fog computing is one of the
best options to avoid improper
or unrelated data to move to
the whole network, thus will
save storage space and
decrease the latency.
12. ADVANTAGES OF FOG COMPUTING
➢It offers better security.
➢Fog nodes can be protected using same procedures followed in IT environment.
➢It processes selected data locally instead of sending them to the cloud for processing. Hence it can save network bandwidth. This leads to
lower operational costs.
➢It reduces latency requirements and hence quick decisions can be made. This helps in avoiding accidents.
➢It offers better privacy to the users data as they are analyzed locally instead of sending them to the cloud. Moreover IT team can manage
and control the devices.
➢It is easy to develop fog applications using right tools which can drive machines as per customers need.
➢Fog nodes are mobile in nature. Hence they can join and leave the network at any time.
➢ Fog nodes can withstand harsh environmental conditions in places such as tracks, vehicles, under sea, factory
floors etc. Moreover it can be installed in remote locations.
➢ Fog computing offers reduction in latency as data are analyzed locally. This is due to less round trip time and less amount of data
bandwidth.
13. DISADVANTAGES OF FOG COMPUTING
➢ Encryption algorithms and security policies make it more difficult for arbitrary devices to exchange data. Any
mistakes in security algorithms lead to exposure of data to the hackers.
➢Other security issues are IP address spoofing, man in the middle attacks, wireless network security etc.
➢To achieve high data consistency in the the fog computing is challenging and requires more efforts.
➢Fog computing will realize global storage concept with infinite size and speed of local storage but data management is
a challenge.
➢Trust and authentication are major concerns.
➢Scheduling is complex as tasks can be moved between client devices, fog nodes and back end cloud servers.
➢Power consumption is high in fog nodes compare to centralized cloud architecture.
14. Advantages of FOG computing over CLOUD computing:
CLOUD COMPUTING FOG COMPUTING
Data and applications are processed in a cloud, which is
time consuming task for large data.
Rather than presenting and working from a centralized
cloud, fog operates on network edge. So it consumes
less time.
Problems of bandwidth, as a result of sending every bit
data over cloud computing
Less demand of bandwidth, as every bit of data’s were
aggregated at certain access point instead of sending
over cloud channels
Slow response time and scalability problem as a result
of depending servers that are located at remote places.
By setting small servers called edge servers in visibility
of user, it is possible for a fog computing platform to
avoid response time and scalability issues
15. CHALLENGES OF FOG COMPUTING
➢Privacy: Privacy concern is always there when there are many networks involved. Since fog computing is based on wireless technology, there
is a huge concern regarding network privacy. There are so many fog nodes that each end-user is accessible to them and because of this more
sensitive information passes from end-users to the fog nodes.
➢Security: Fog computing security challenge arise as there are many devices connected to fog nodes and at different gateways. Each device has
a different IP address, and any hacker can fake your IP address to gain access to your personal information that is stored in that particular fog
node.
➢Fog Servers: The right placement of fog servers should be there so that it can deliver its maximum service. The company should analyze the
demand and work done by the fog node before placing it will help in reducing the maintenance cost.
➢Energy consumption: Energy consumption is very high in fog computing as the number of fog nodes present in the fog environment are high
and require energy to work. Companies should try to minimize the energy requirement by the fog nodes so that they should become more
energy-efficient and save costs.
➢Delay in Computing: Delays due to Data aggregation, Resource over-usage reduces the effectives of services provided by the fog servers,
causing delay in computing data. Data Aggregation should take place before data processing, Resource-limited fog nodes should be designed
scheduling by using priority and mobility model.
16. FOG COMPUTING TECHNOLOGY
➢5G Technologies: Fog computing focuses on serving customized location-based applications to mobile users. The Fog layers
can be adapted by using the existing accessing networks, e.g., WiFi, or emerging 5G wireless technologies with a virtualized
architecture.
➢Network Function Virtualization (NFV): In contrast NFV which targets to enabled virtualized network functions inside
network nodes, e.g., switches and routers, Fog computing aims at enabling virtualized location-based applications at the edge
device and providing desirable services to localized mobile users.
➢Software-defined Networking (SDN): The Fog computing, as the local surrogate of cloud, needs to synchronize frequently
with cloud for data update and support. With a global network view, the cloud can manage the entire network using a SDN
approach.
18. Smart health gadgets and devices can
receive best services from fog
devices at network edge. No need to
send service request to cloud server.
HEALTHCARE:
19. Fog device enables cars to talk
with each other to avoid accidents.
It also helps in getting information
about low crowded path.
CAR
COMMUNICATION:
20. Fog computing would be able to
obtain sensor data on all the levels,
and integrate all the mutually
independent network entities
within.
Smart city:
21. Smart electric devices can switch
to other energy sources like solar
and winds based on demand for
energy, its attainability and low
cost.
SMART GRID:
22. Lights Fog enables automatic
opening of signals based on
dynamic situation of traffic signals.
Also, it can detect ambulance and
open lanes for it.
SMART TRAFFIC:
23. All sensors in the building can
communicate and exchange with each
other and with Fog device. Fog device
performs analysis on combined data.
Connected devices may react in
response to data analysis and distributed
decision making.
SMART BUILDING
Control:
25. FOG COMPUTING IN HEALTHCARE
CHALLENGES FOR HEALTHCARE:
➢Healthcare system is most countries face enormous challenges that will increase due to aging population
and the rise of chronic diseases.
➢Growing nursing staff shortage.
➢Much time wasted in hospitals by manually measuring biometric parameters and transferring the data
between systems.
26. REQUIREMENTS OF HEALTHCARE APPLICATIONS
BANDWIDTH of at least 20.48 kbit/s and 96 kbit/s. Bandwidth For ECG, latencies of up to 2 to 4
seconds in real-time monitoring are acceptable.
Latency some in-body sensors rely on energy-harvesting, either by heat or kinetic energy. some
sensors may require an operation of the patient when battery needs replacement.
Energy-Efficiency Depending on what data is used for, system failures have different consequences, from
minor inconvenience to serious threat to the patients’ lives.
Dependability the security requirements in healthcare are high. Security Systems, even when provided
by different vendors, should be interoperable with each other.
Interoperability system even when provided by the different vendors, should be interoperable with each
other.
27. VISION OF FOG COMPUTING IN HEALTHCARE
➢Flexibility of Computation locus: The location can be dynamic and depend on the current context, environment
and application requirements.
➢ Integration: Within fog computing architecture, new sensors can be added to the existing infrastructure.
• Fog computing can also serve as a compatibility layer to translate between various standards.
➢Patient mobility: Application-specific infrastructure also limits the area where patients can be monitored.
• The transitions between different environments can be managed more gradually.
➢New Applications: Fog computing will provide latency and response time improvements, as well as energy
savings for wearable and low-cost devices, while performing complex tasks such as fall detection.
• Internet of Health care things.
30. SECURITY ISSUES
The main security issues are authentication at different levels of gateways as well as in case of smart grids at the
smart meters installed in the consumer’s home. Each smart meter and smart appliance has an IP address. A
malicious user can either tamper with its own smart meter, report false readings, or spoof IP addresses.
31. Example: MAN-IN –MIDDLE-ATTACK
In this subsection, we take man- in-the-middle attack as an example to expose the security problems in Fog
computing. In this attack, gateways serving as Fog devices may be compromised or replaced by fake ones .
32. CONCLUSION
Fog computing advantages for services in several domains, such
as Smart Grid, wireless sensor networks, Internet of Things (IoT)
and software defined networks (SDNs). We examine the state-
of-the-art and disclose some general issues in Fog computing
including security, privacy, trust, and service migration among
Fog devices and between Fog and Cloud.
33. FUTURE ENCHANCEMENT
Since fog as itself a newer concept, implanting this will takes a little time but once done, it would make IoT devices a lot smarter.
The extended work on fog computing & cloud computing could be on the impact of heterogeneous storage and overall
performance on the basis of diverse applications.
Fog computing has several advantages over cloud computing. Fog computing can boost usability and accessibility in various
computing environments. Soon, cloud computing for IoT may fade away but fog computing will take over. IoT is seeing an
impressive growth rate and so it needs a special infrastructure base that can handle all its requirements. Fog computing is the key
to accomplish this critical work.
