Basic Concept of Edge-Computing and its applications

Basic concept of Edge-Computing and its applications
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1. Edge Computing Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, improving response times and saving bandwidth. In this presentation, we will explore what edge computing is, and how it is changing the world of technology. Dr.Irshad Ahmed

2. Definition of Edge Computing What is Edge Computing? Edge computing is a network architecture which enables data processing to be done at the edge of the network, this means that it’s done closer the users and devices, rather than in a central location. Data is processed locally on edge devices or servers, minimizing latency, reducing data transfer and bandwidth cost, while improving response times and overall user experience. Why Edge Computing? The rise of edge computing is driven by the emergence of new technologies such as IoT, real-time analytics, 5G networks, and autonomous vehicles. These technologies generate and rely on a vast amount of data, which requires fast and efficient processing with low latency. With Edge computing, this processing happens closer to the source, reducing the time delay from transferring data to a central cloud location. Examples of Edge Devices Edge devices range from consumer smart devices like home assistants, smart thermostats, door locks, and surveillance cameras to industrial devices like drones, autonomous machines, and remote sensors.

3. Difference between Edge Computing and Cloud Computing 1 Centralized vs. Distributed Cloud computing is a centralized model of computing where central servers in data centers run applications and store data. Edge computing is a distributed model of computing where processing is done locally at the edge of the network. 2 Latency and Response Times Cloud computing interactions rely solely on the network connection which can be slow and unreliable. Edge computing provides low latency and high bandwidth, enabling faster data processing, and better user experience. 3 Bandwidth and Network Control Cloud computing requires high bandwidth and centralized network control, which creates a bottleneck for data transmission while edge computing minimizes the amount of data transmitted over the network, reducing costs and improving data privacy.

4. Use cases of Edge Computing Smart Cities Edge computing can be used to power IoT-enabled smart cities, improving traffic management, public safety, energy efficiency, and overall quality of life. Autonomous Systems Edge computing can enable autonomous systems like drones, self-driving cars, and robots to make real-time decisions in remote locations without the need for a stable internet connection.

5. Use cases of Edge Computing Edge computing can drive industry 4.0, by enabling real-time analytics on the factory floor, improving productivity, quality control, and predictive maintenance. Industry 4.0 Edge computing can be used in healthcare, for remote patient monitoring, managing medical devices, and improving patient care with real-time analytics. Healthcare

6. Benefits of Edge Computing 1 Faster Response Times Local data processing reduces latency and improves response times. 2 Lower Network Costs Reduced bandwidth usage lowers network costs, especially in remote locations. 3 Improved Reliability Edge computing reduces the reliance on central servers and increases the reliability of the system as it can operate autonomously in case of network failure. 4 Better Data Privacy Edge computing processes data locally, reducing the need to send sensitive data over the network, providing better data privacy and security.

7. Challenges of Implementing Edge Computing Challenge Solution Scalability Adopting cloud-managed edge computing solutions can ease management and scalability challenges. Data Security Ensuring edge devices are secured from hacking, and vulnerabilities are minimized through regular maintenance and software updates. Interoperability Standardization of edge devices and cloud communication standards can help to address interoperability challenges.

8. Future of Edge Computing 1 5G Rollout The deployment of 5G networks will be a significant catalyst in the edge computing adoption, enabling higher bandwidth, lower latency, and faster data processing, ultimately driving innovative technologies like AR and VR. 2 Edge AI The integration of edge computing and AI will enable real-time decision making, autonomous control, and intelligent automation in various industries. Edge AI will power the growth of the IoT and will transform industries. 3 Autonomous Systems Edge computing is critical to the adoption of autonomous systems like self-driving cars, drones, and robots, which rely on real-time data processing and decision-making in remote locations.

9. Conclusion Transforming Technology Edge computing is a paradigm shift in computing that is transforming how we use technology. It has immense potential to create new business models, enhance customer experiences, and unlock new revenue streams. Connected World As edge computing evolves, it will provide more powerful and efficient computing capabilities, connecting people, devices, and systems Even more closely, delivering new services and experiences that were previously thought impossible. Speeding up the future The possibilities of edge computing are infinite, from smart cities to autonomous systems, from AI to VR, and they will only be limited by our imagination. Edge computing is undoubtedly opening a new chapter of the tech world, and it’s only just getting started.