Key research themes
1. How can intelligent resource management and load balancing in Internet of Multimedia Things (IoMT) improve energy efficiency and service quality?
This theme investigates the challenges posed by the exponential increase in multimedia devices and traffic within the IoMT ecosystem, focusing on optimizing resource allocation in the face of load imbalance and energy losses. It examines network softwarization approaches, such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV), as facilitators for dynamic, energy-efficient, and load-balanced resource management to enhance the Quality of Service (QoS) and Quality of Experience (QoE) for multimedia applications.
2. What role do edge computing architectures play in addressing latency, bandwidth, and privacy challenges in real-time IoT data processing?
This research area focuses on overcoming the limitations of centralized cloud architectures in IoT ecosystems by leveraging edge computing. By processing data closer to the source, edge computing enables reduced latency, decreased network congestion, improved scalability, enhanced energy efficiency, and stronger data security. It addresses the specific needs of real-time IoT applications such as smart cities, industrial automation, and healthcare through decentralized architectures combining edge and cloud resources.
3. How does security and privacy engineering address vulnerabilities inherent to the scalable and heterogeneous nature of IoT systems?
This theme explores the emerging security and privacy challenges in IoT arising from its vast scale, diversity of connected devices, and integration with data-driven cloud platforms. It reviews qualitative evaluations of existing security approaches, highlighting their limitations in face of distributed architectures and pervasive connectivity. Key concerns include protecting user data, ensuring device authentication, and securing communication channels amidst the dynamic IoT landscape.