Mod 1 edge

Course Overview

  • Institution: BMS Institute of Technology & Mgmt

  • Program: 21IS744 Edge Computing AY: 2024-25 Odd

Course Outcomes

  1. Understand the paradigms of Edge Computing.

  2. Apply a conceptual framework for optimization problems and data management in Edge Computing.

  3. Analyze the core principles of Edge Cloud with reference architecture.

  4. Evaluate case studies to assess the need for Edge Computing.

Module 1: Edge Computing

  • Concepts Covered:

    • Completing the cloud with Edge Computing.

    • Advantages of Fog Edge Computing (FEC): SCALE

    • Hierarchical structure of Fog and Edge Computing.

    • Various business models in Edge Computing.

    • Opportunities and challenges in Edge Computing.

    • Strategies to address challenges in federating Edge resources.

What is Edge Computing?

  • Definition: Distributed IT architecture where client data is processed at the network's edge, close to the data source.

    • Reduces the need for data transmission to central data centers.

    • Data processing occurs at locations like retail stores, factory floors, or smart cities.

Need for Edge Computing

  • Transforming Industries: Catalyzes the next industrial revolution by optimizing data capture at the edge.

  • Characteristics:

    • Creates scalable, secure, and automated technology environments.

    • Emerged due to rapid growth in IoT devices requiring efficient information management.

    • Fosters an agile ecosystem, enhancing performance and cost efficiency.

Key Terms and Definitions

  • Edge: Varies based on use cases (e.g., telecommunication, automotive).

  • Edge Devices: Devices generating data, including machines, sensors, and laptops.

Integration of IoT and Edge Computing

  • Internet of Things (IoT): A system of interconnected objects that collect and transfer data autonomously.

    • Edge computing enhances IoT by moving intelligence closer to the source, reducing latencies and improving responsiveness.

5G Technology and its Impact on Edge Computing

  • Comparison with 4G: 5G features low latency (1ms) and significantly faster download speeds (1.4x 4G).

    • Enhanced connectivity for numerous devices, exceeding 1 million devices in small areas.

    • Utilizes advanced data encoding techniques like OFDM.

Edge Computing vs. Cloud Computing

  • Cloud Computing: Centralized hosting in data centers.

  • Edge Computing: Localized hosting closer to users, leading to significant adoption trends.

Importance of Cloud Computing

  • Provides cost-effective data storage and processing.

  • Public clouds (e.g., Microsoft Azure, AWS) leverage economies of scale to lower costs for users.

Advantages of Edge Computing over Cloud Computing

  • Reduces latency, enabling new use cases:

    • Augmented/Virtual Reality (AR/VR), Autonomous Vehicles, Cloud Gaming, Smart Grids.

Edge Computing Architecture

  • Composed of multi-layer distributed architectures balancing workloads among:

    • Edge Layer

    • Edge Cloud or Network Layer

    • Enterprise Layer

Example Use Case

  • CCTV Systems:

    • Traditional: Heavy bandwidth consumption due to constant data transfer to the cloud.

    • With Edge Computing: Local processing reduces bandwidth usage by filtering data before it reaches the cloud.

Edge Computing Use Case Examples

  1. Autonomous Vehicles: Enhances communication for convoy travel, optimizing fuel use and congestion.

  2. Remote Asset Monitoring in Oil & Gas: Enables real-time analytics in remote environments, reducing reliance on stable connectivity.

  3. Smart Grid Management: Improves energy use monitoring and smart grid technology, allowing more flexible energy management.

  4. Predictive Maintenance: Enables real-time health monitoring of equipment to prevent failures.

  5. In-Hospital Patient Monitoring: Enhances data processing at the local hospital level to maintain patient data privacy and analytics.

Federated Edge Computing (FEC)

Advantages of FEC: SCALE

  • Security: Enhances overall IoT security through timely updates and trustworthy transactions.

  • Cognition: Supports autonomous decision-making in edge deployments.

  • Agility: Increases agility in large-scale IoT deployments.

  • Latency: Assures ultra-low latency for real-time applications.

  • Efficiency: Improves overall efficiency, especially in healthcare systems.

FEC Achieves Advantages via SCANC

  1. Storage: Temporary data caching enhances content delivery.

  2. Compute: Offers services like I/PaaS and SaaS.

  3. Acceleration: Facilitates networking and compute acceleration.

  4. Networking: Supports vertical and horizontal connectivity.

  5. Control: Includes mechanisms for deployment, actuation, mediation, and security.

Hierarchical Structure of Edge Computing

  • Inner-Edge: Constitutes geographical WANs enhancing service quality.

  • Middle-Edge: Layer includes LAN and cellular networks.

  • Outer-Edge: Comprises devices with limited processing power such as sensors and actuators.

Business Models and Support Services

  • Emerging business models include X as a Service (XaaS) and IndieFog.

  • Support services encompass traditional IT system management, application service provision, and application-based solutions like Digital Twinning.