Analysis of Software Applications Computing Resources Usage on the Edge: A Case Study of Speech Recognition

Bilal Abdullah
Billions of sensors are currently deployed around the world. Some are standalone sensors while others can be found in smart-phones, wearables, cars, machinery, buildings, street lights, wind turbines and other places too numerous to mention. These sensors are connected to intermediate edge devices which provides connectivity to the core network. The amount of data generated by sensors is staggering and with the rapid growth of sensors deployed, generated data will only continue to increase. The traditional way of handling data where generated data is sent to the network for analysis and decision made is already inefficient and completely impractical in most applications. A better approach would be to perform these analytics and decision making tasks on the edge devices. But due to the very limited available resources on edge devices, it is important to first analyze the computing resource utilization of sample applications running on edge device in order to understand what computational tasks are possible on these edge devices. This thesis aims to take Speech Recognition as a case study and analyze its resource consumption on an edge device. The thesis further aims to explore the possibility of implementing long running tasks on the edge without significantly impacting the limited edge resources. Finally, we investigate the possible impact of performing additional speech analytics tasks on the edge.
Graduation Thesis language
Graduation Thesis type
Master - Software Engineering
Alo Peets
Defence year