Edge computing is a distributed computing architecture that processes data closer to where it is generated, at the edge of the network, rather than sending all data to centralized cloud data centers for processing. It aims to provide quicker response times and reduce issues like hacking and random failures. Edge computing is geographically distributed, scalable, autonomous, and processes data locally with low latency for real-time interactions. While it has advantages like increased speed and reliability, it also has disadvantages like limited scalability and interoperability compared to cloud computing. Applications of edge computing include smart cities, manufacturing, healthcare, and augmented reality devices.

1. Introduction to
Edge Computing

2. Cloud Computing
 Cloud computing is a distributed technology which
delivers hosted services over the internet to provide easy
access, scalable (and elastic) IT services

3. What is Edge Computing
• Edge
•Any computing and network resources along the path
between data sources centers

5. The Edge Computing Characteristics
• Geographically distributed
• Scalable
• Autonomous and distributed
• Edge computing is contextual and low latency
• Real-time interactions
• Heterogeneous

6. Edge Computing Architecture
 Edge computing architecture helps by moving
application and data closer to the user. As a
distributed IT architecture, edge computing aims
to meet end-user demands and expectations for
quicker response times by processing data closer
to them.

8. Advantages of Edge Computing
• Speed is increased.
• Reliability is increased.
• The random issue is reduced.
• The compliance issue is reduced.
• Hacking issues are reduced.
• Random issues are reduced

9. Disadvantages of Edge Computing
• It is operations can not be extended to IT/OT team
• It can not perform resource pooling
• It is interconnected through proprietary network with
custom security and little interoperability.
• It is limited to smaller number of peripheral layers

10. Applications of Edge Computing
• Smart Cities
• Manufacturing
• Healthcare
• Augmented Reality Devices
• AI Virtual Assistant

11. Future Directions of Computing for the
Internet of Things (IoT)
▶ Edge-to-Cloud data exchange capabilities
▶ Common-on-Edge data exchange capabilities
▶ Streaming Data Analytics and Batch frameworks and APIs
▶ Controlled rolling and Versioning upgrades of applications
▶ Status of application monitoring from an Ad-Hoc Cloud Dashboard
▶ Cloud-Based Deployments of Edge Computing Applications