Mitigating Climate Change Through Quality-driven Management of Future Telecommunications
The major challenge in future connected and autonomous vehicles (CAVs) is reducing CO2 emissions and energy consumption associated with Internet multimedia streaming services delivery over 5G networks without adversely affecting end users’ video watching or entertainment experiences. Dr Alcardo's research focuses on developing energy-efficient approaches and quality-driven management of internet video streaming services in CAVs for 5G and beyond networks.
Given that substantial transport emissions reductions are required to help mitigate ongoing climate change, Dr Alcardo hopes that developing AI-dynamic delivery control mechanisms for multimedia services will help to meet in-vehicle end users’ quality of experience (QoE) and energy-efficient demands on 6G and 2030 systems.
A Career Dedicated to Future Telecommunications
Dr Alcardo earned his PhD in computing and communications from the University of Plymouth, UK in March 2020. He has worked as a postdoctoral fellow in the School of Computer Science, University College Dublin (UCD), Ireland, where he made scientific advances in future network and services management over 5G, multimedia and QoE–related research. He has also worked as a Marie Curie Fellow in MSCA-ITN QoE-Net and was a visiting researcher in the Department of Electrical and Electronics Engineering, University of Cagliari, Italy and the ITU-T-Standardization Department, Geneva, Switzerland in 2016 and 2017 respectively.
Dr Alcardo has published several research papers on multimedia streaming, 5G and beyond networks and big data. He has more than 60 publications in international peer-reviewed conferences and journals with a total of 1788 citations as of June 2024. He has made significant contributions since 2016–2018 in the areas of SDN/NFV, future network performance, QoS and QoE. He was awarded the Best ICT Young Researcher of Tanzania, an award that is given by the Tanzania Commission of Science and Technology.
A Sustainable Future Telecommunication System in CAVs
Dr Alcardo’s DIA-supported project addresses climate concerns resulting from energy consumption and CO2 emissions in future telecommunication systems such as 6G networks. The project will investigate multimedia streaming QoE use cases, scenarios and prototypes in CAVs over future 5G and beyond networks as a proof of concept for enhancing QoE for in-vehicle users and making video streaming services faster and more energy-efficient in the context of 2030 networks.
Dr Alcardo believes that quality-driven management and energy-efficient approaches are required to mitigate energy consumption and CO2 emissions associated with future telecommunication systems in CAVs. Collaborating with Dr Trung Q. Duong from Queen’s University Belfast, Dr Alcardo is developing a testing platform for software-defined autonomous vehicles over 5G networks. His DIA-supported project aims to provide continuous QoE-energy efficient, CO2-emissions reductions and AI-dynamic delivery control mechanisms of multimedia services to meet in-vehicle end-users’ QoE demands on 6G and 2030 systems.
The DIA program improves my collaborative teamwork and helps to increase networking potential in the thematic area of technologies for the future
Enhancing Sustainable Telecommunication Networks
Dr Alcardo envisions a transport system with improved quality of experience for end-users as well as reduced environmental pollution and CO2 emissions. He is working on developing a proposal regarding multimedia streaming services in software-defined CAVs in future 2030 networks and also sharing his research activities and findings with research communities through training, workshops and conferences. Through collaborations with research communities focusing on future telecommunication networks such as machine-to-machine communications and the Internet of Things (IoT), Dr Alcardo aims to further enable vehicle-to-everything (V2X) network communication efficiency while reducing network congestion and CO2 emission through intelligent CAV traffic flow management.