• Funding : Artois, Marocan
  • Start year :
  • 2025

Joint PhD with Cadi Ayyad university, Morocco

Mobile Edge Computing (MEC) using the Internet of Things (IoT) is a promising technology for delivering low-latency, high-speed services to end users. Resource allocation and Quality of Service (QoS) optimization are critical challenges in MEC systems due to the large number of devices and applications involved. The result is low latency with minimal throughput and energy consumption, as well as high delay rates. The limited battery and computing resources of mobile devices (MDs) lead to performance limitations in MEC networks. IT offloading has the capacity to provide computing and storage resources to MDs for the execution of resource-intensive tasks. Therefore, to minimize energy consumption and service delays, MDs offload resource-intensive tasks to a nearby Mobile Edge Server (MES) for execution. However, due to time-varying network conditions and the MES’s limited computing resources, the decision made by DMs may not achieve the lowest cost.

In this research work, we will propose and validate advanced approaches based on Artificial Intelligence techniques to improve the security of MECs and next-generation networks.