Analysis and improvement of QoS and security of Mobile Edge Computing based networks

Abstract

The rapid evolution of mobile technologies and connected objects (IoT) has led to a massive increase in the volume of data to be processed and secured. Traditional cloud architectures, while efficient for large-scale storage and processing, no longer meet current requirements in terms of latency, bandwidth, and security. To address these challenges, the Mobile Edge Computing (MEC) paradigm is emerging as an innovative solution that brings computing and storage resources closer to end users while improving the performance of distributed services. This thesis offers a series of contributions aimed at optimizing the processing, security, and storage of sensitive data in MEC environments through the integration of complementary technologies such as Software-Defined Networking (SDN), Blockchain, Network Functions Virtualization (NFV), and IPFS. In the first part, we design a secure mobile data offloading architecture in small cell networks (SCN), combining SDN, public/private blockchain, and Wi-Fi and D2D communications. This solution aims to guarantee ultra-low latency while ensuring the integrity and confidentiality of data transferred from mobile devices to the cloud. Secondly, we address the issue of secure edge video streaming management. We propose a distributed model based on dynamic orchestration of security tasks via NFV, allowing for optimized resource allocation while ensuring consistent quality of service, even under performance constraints. Finally, we present a secure storage solution for video surveillance systems, based on blockchain and IPFS, with a MEC layer enabling local preprocessing. The use of mechanisms such as Segregated Witness and smart contracts ensures the integrity, traceability, and efficient storage of critical video data. All the proposals are validated by simulations and experimental evaluations that demonstrate their effectiveness in terms of latency reduction, security improvement, data resilience, and resource optimization. This thesis thus paves the way towards intelligent, secure, and efficient edge environments, adapted to the growing needs of modern mobile applications, particularly in the fields of IoT, multimedia services, and urban security.