Public defence in Computer Science, M.Sc. Thaha Mohammed

Title of the doctoral thesis: Heterogeneous Resource Management for Services based on Artificial Intelligence

Doctoral student: Thaha Mohammed
Opponent: Prof. Jiannong Cao, Hong Kong Polytechnic University, Hong Kong 
Custos: Prof. Mario Di Francesco, Aalto University School of Science, Department of Computer Science

A large number of emerging wireless applications in the Internet of Things (IoT), including those for smart cities and intelligent transportation systems, leverage artificial intelligence (AI) through machine learning (ML) and have heterogeneous resource requirements. To this end, several novel computing and communication paradigms have been proposed, including cloud, fog, edge, and network slicing. However, satisfying a given quality of service (QoS) or quality of experience (QoE) requires minimal latency and efficient management of computing resources. Furthermore, the heterogeneous resource demands of the applications should be efficiently satisfied while guaranteeing the service level agreements (SLAs) of service providers as well as the privacy of the stakeholders.

This dissertation addresses the challenges arising from heterogeneous resource management for AI-based services within the context of distributed processing and IoT scenarios, as discussed above. It specifically proposes novel approaches for efficient distributed offloading in edge and fog networks. We develop distributed solutions to improve the inference time of DNNs; a tool to enhance the computation of pruned DNNs; incentivize the market to trade existing knowledge among service providers; and a mechanism for joint multi-resource allocation to improve network utilization and service providers' profits.

Thesis available for public display 10 days prior to the defence at: https://aaltodoc.aalto.fi/doc_public/eonly/riiputus/

Contact information:

Doctoral theses in the School of Science: https://aaltodoc.aalto.fi/handle/123456789/52