NEWS Today, many apps and systems are used to watch and analyze videos, for example in the case of traffic control and surveillance systems. These apps need to quickly make decisions based on what they see in the videos. Ali Rahmanian, a doctoral student at the Department of Computing Science and the Industrial Doctoral School, wants to revolutionize this technology. "My research could be particularly useful for cities and factories that use video analytics to control processes," he says.
Ali Rahmanian, doctoral student at the Department of Computing Science and the Industrial Doctoral School.
ImageMattias PetterssonIn today's fast-paced digital landscape, the demand for real-time insights from video analytics applications is greater than ever. Processing capabilities need to be fast so that apps can make decisions in a fraction of a second.
Ali Rahmanian's research focuses on revolutionizing so-called edge computing, which means that the data is placed at the edge of a network – close to where it will be used. The advantage of edge computing is that you get lower latency, i.e. faster access to the data, because it literally has to travel a shorter distance.
“The faster you can access the data, the faster the apps can make their decisions. By harnessing the power of resources closer to data sources and end users, my thesis aims to significantly reduce latency and improve performance,” says Ali Rahmanian.
Ali Rahmanian proposes innovative methods to get different programs to work together in a good way. He also looks at how important it is that both individual programs and the entire system are well optimized. By making improvements on both small and large levels, he shows how they can work well together.
Ali Rahmanian explores how to use edge orchestration to make it easier to analyze live videos. His ideas can help improve the way we use videos to make quick decisions. The research could be particularly useful for cities and factories that use video analytics to control processes.
“It enables smoother and faster applications for smart cities and factories by improving resource usage at the of the network. By making the process faster and more efficient, it can also help save time, energy and reduce our impact on the environment,” says Ali Rahmanian.
Ali Rahmanian's doctoral project has been funded by the Industrial Doctoral School at Umeå University and Ericsson Research.
Ali Rahmanian, Department of Computing Science, Umeå University, defends his thesis entitled Edge Orchestration for Latency-Sensitive Applications on Monday 29 April. The defense will take place at 02.00 pm in Hörsal UB.A.240 – Lindellhallen 4. The faculty opponent is Professor Ada Gavrilovska from Georgia Institute of Technology, Atlanta, GA, USA.
The Industrial Doctoral School is based on collaboration between the University, researchers and businesses or organisations. The aim is to combine benefits for both society and the external party while training new high-quality researchers. The doctoral student also receives a tailored academic course package. The doctoral school is open to all disciplines and the doctoral student is employed at Umeå University.
