Module 4

Question 1

definition/concept of edge computing

Answer 1

1. decentralization of networks
2. concept of edge computing is that instead of getting the data close to the data center, the data center is brought close to the source

Question 2

cloud layer

Answer 2

1. cloud layer and edge layer complement each other
2. edge servers pass on data to the cloud layer for complex processing
3. edge servers will also pass a part of the data for storage and comprehensive analysis

Question 3

edge layer

Answer 3

1. layer mainly consists of edge servers larger in quantity and vastly deployed
2. edge layer considered to be core
3. data which cannot be processed in the edge layer is sent to and analyzed in the cloud layer

Question 4

device layer

Answer 4

1. amongst the three layers it contains the most number of devices
2. through sensors, devices in the device layer collect and capture data used to help products achieve the purposes they are designed for
3. edge and cloud possess better computing skills but device layer can also do small levels of processing

Question 5

Security risks and its measures
(edge computing-explain points also)

Answer 5

1. Data breach
2. Frequent Updates
3. Scalability
4. Cloud adoption risk
5. Edge and IoT security risks

Question 6

How to secure edge computing ?
(explain points also)

Answer 6

1. Keep your devices and your data safe
2. Secure your network connection
3. Implement security measures at the edge level
4. Protect against IoT security risks
5. Monitor and log all edge activities

Question 7

Advantages of edge computing

Answer 7

1. Faster response time
2. Security and compliance
3. Cost-Effective Solution
4. Reliable Operation with intermittent connectivity
5. Reduced latency

Question 8

Limitations of edge computing

Answer 8

1. Complexity
2. Limited Resources
   3.. Dependence on connectivity
3. Security concern

Question 9

Challenges in edge computing

Answer 9

1. Privacy and security of data
2. Scalability
3. Reliability
4. Speed
5. Efficiency

Question 10

Fog computing

Answer 10

-> it is a distributed computing paradigm that extends the cloud services to the edge of the network
-> It facilitates management and programming of compute, networking and storage services between data services and end devices

Question 11

edge devices

Answer 11

->devices which are at the edge of the network or a bridge between two networks which works by being near the source of the data it manages.
->main function includes transmission, routing, processing, filtering, translation and storage of data between two networks.
eg: sensors, actuators and iot gateways

Question 12

architecture of fog computing
(remember the functions of each layer)

Answer 12

1. Sensors, Edge Devices, Gateways and apps
2. Network
3. Cloud Services
4. Resource management
5. Application

Question 13

(wrt fog computing)
Security risk 1:
Increased attack surface due to distributed nature of the technology

Answer 13

-> Securing the individual devices and systems that make up the fog network, as well as the connections bw them
-> to use encryption and authentication protocols so that only authorized people can access and data transmitted can be saved from eavesdropping and tampering

Question 14

(wrt fog computing)
Security risk 2:
Privacy, as the technology often involves collection and processing personal data

Answer 14

-> Organizations need to be transparent about their data collection practices and allow users to opt out if needed

Question 15

(wrt fog computing)
Security risk 3:
Fog computing introduces new challenges in terms of compliance with data protection regulations such as General Protection Regulation(GDPR) in the union

Answer 15

-> should work closely with legal and compliance experts
-> this may include implementing data protection by design principles, conducting regular risk assessments and maintaining detailed record of data processing activities.

Question 16

Advantages of fog computing
(explain points also)

Answer 16

1.Reduction of network traffic
2. Suitable for iot tasks and queries
3. low-latency requirements
4.Scalability

Question 17

limitations of fog computing
(explain points also)

Answer 17

1. Bandwidth
   2.latency
   3.congestion

Question 18

Application of fog computing
(explain points also)

Answer 18

1.Healthcare
2.Augmented reality

Question 19

difference between edge computing and fog computing

Answer 19

remember the points

Question 20

edge routers (edge device)

Answer 20

manages data traffic to an IP address so multiple devices can operate using a single internet connection

Question 21

WAN devices

Answer 21

devices extend over a large area even global

Question 22

routing switches

Answer 22

can perform the same functions as router but also allow connections across different devices

Question 23

firewalls

Answer 23

firewalls monitor all network traffic for security

Question 24

multiplexers

Answer 24

merge data from multiple data sources over a single signal

Question 25

intelligent iot devices

Answer 25

1.Sensors 2. actuators 3.iot gateways 4. M2M devices

Question 26

M2M devices

Answer 26

-> Machine to Machine communication -> direct communication system between the devices using wired or wireless communication channels without human interaction ->allows internet connection. collects data and shares it with other connected devices

Question 27

benefits of edge devices

Answer 27

1. Improved performance 2. Empowering AI ml 3. Better regulatory and compliance performance 4. Greater interoperability

Question 28

Edge computing gateway

Answer 28

An edge computing gateway processes data from the edge devices, sending back relevant data, providing network translation between networks using different protocols and ultimately reducing bandwidth needs

Question 29

function of an iot gateway

Answer 29

-> Connects sensors and nodes at one end, provides one or multiple local functions and extends bidirectional communications to the cloud -> can sometimes be used to preprocess data locally at the edge devices before sending them to the cloud, reducing volume of data sent to the cloud

Question 30

Edge AI

Answer 30

edge AI is the class ML architecture in which AI algorithms process the data on the edge of the network instead of sending it to the cloud

Question 31

why do we need edge AI?

Answer 31

->in ML large heaps of data collected to predict something. by running ML algorithms on edge devices we can produce such predictions faster without the need to transmit large amounts of raw data across the network ->

Question 32

advantages of edge ML or AI

Answer 32

1. Operational efficiency : enhancing the real time decision making capabilities 2. Enhanced security: increased level of security through local processing. data no longer shared in centralized cloud. 3.Decentralization of workloads: makes all distributed systems efficient and self sustained.

Question 33

performing ML on low power devices as an advantage

Answer 33

1. Less network BW 2. less communication means reduced power usage 3. prediction results are available immediately 4.inference can be performed without any connection to the network

Question 34

Applications of edge AI/ML

Answer 34

1. Agriculture 2. Smart buildings 3. Environment conservation 4. Health and fitness 5. Human computer interaction 6. Industry