YoVDO

Coding to Enable the Tactile Internet

Offered By: Open Data Science via YouTube

Tags

Mesh Networks Courses

Course Description

Overview

Explore the potential of Network Coding algorithms in revolutionizing the Internet of Things (IoT) infrastructure in this conference talk from BDF 2015. Delve into Random Linear Network Coding (RLNC) and its applications in various IoT use cases, focusing on enhancing security, reliability, and efficiency in dynamic systems. Learn how these innovative coding techniques can extend battery life in embedded devices, improve meshing capabilities, and bring order-of-magnitude performance improvements to data storage and transportation. Gain insights from Laila Partridge, a seasoned entrepreneur and former Intel Capital executive, as she discusses the critical role of network coding in enabling the Tactile Internet and addressing the massive network requirements of IoT. Examine the context of coding algorithms, understand the simplification offered by Network Coding, and discover the unique versatility of RLNC in multipath/multicloud scenarios, heterogeneous networks, and edge caching applications.

Syllabus

Intro
TOT Requires a Network Revolution
lot's Massive Network Requirements
Coding Algorithm Context
Simplify using Network Coding Network Coding new class of coding algorithms
Random Linear Network Coding
Any RLNC Mixture is Useful
Multipath/ Multicloud
Sample IoT Use Cases for Multipath
Heterogeneous Channels / Networks
Coded Multicast
The Value of Re-Coding
Coded Mesh / Distributed Storage
Coded Mesh with Helper Nodes
Sample loT Use Cases for Mesh Networks
Edge Caching / Dynamic Distributed Storage
More Distributed → More Secure
Unique Coding Versatility
How is RLNC different?
How Does RLNC Work?


Taught by

Open Data Science

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