From Data to Decisions: Knowledge Discoverability in Edge Infrastructure
Organization
Mobile & Cloud Computing Laboratory
Abstract
The knowledge/intelligence discoverability in the edge computing infrastructure pertains to the capacity of edge devices to autonomously discern and act upon patterns and insights from localized data processing. By situating computation closer to data sources, such as IoT devices, edge computing facilitates real-time analytics, mitigating the latency inherent in centralized cloud systems. This immediate processing empowers edge devices to make informed, autonomous decisions based on the knowledge they extract. For instance, a smart traffic management system at an intersection can leverage edge computing to analyze traffic patterns in real-time and autonomously adjust signal timings to optimize flow, without relaying data to a central server. Over time, these devices not only accumulate domain-specific knowledge but can also collaboratively share insights with other edge nodes or central systems, enhancing the collective intelligence of the entire network. Thus, edge infrastructures transition from mere data processing nodes to pivotal hubs of dynamic knowledge and adaptability.
Graduation Theses defence year
2023-2024
Supervisor
Chinmaya Dehury
Spoken language (s)
English
Requirements for candidates
Level
Masters
Keywords
Application of contact
Name
Chinmaya Kumar Dehury
Phone
E-mail