5G networks promote integrating Multi-access Edge Computing (MEC) capabilities in Dense Small Cell (DSC) networks in order to address the strict latency requirement of Smart Mobile Devices (SMDs) services. This article investigates the contribution of a split-cache method integrated within a secure blockchain based MEC system and present a novel method to enhance service provision by distributing the containers’ base image chunks among multiple Edge-Cloud Nodes (ECNs). The objective of this study is to minimize the service starting/restarting time by collecting, verifying and compiling the best chunks candidates while resources allocation is considered at each request slot. The formulated problem is a mixed-integer nonlinear program, subject to network bandwidth capacity, base image chunks availability, and services starting deadlines constraint. Finally, the numerical results of the proposed two solutions demonstrate its benefits regarding service provision operations while taking bandwidth,timing and resources into consideration.

2D medical images resolution from the current hardware becomes more important. The reconstruction of a 3D model from these images generates a large number of polygons, which leads to problems with the amount of information stored and also in terms of the complexity of calculations for display viewing in real-time. Our approach to 3D reconstruction of the human anatomy, from a sequence of 2D images is based on a low mesh resolution. This mesh is obtained by using the marching cubes algorithm of these medical images. Small reliefs lost in the base mesh are calculated from the information we have in 2D images. These reliefs are shown in the form of 2D vectors, which allows a very important optimisation of the 3D model storage. Details of each polygon mesh base are calculated in an independent manner, which facilitator the automatic generation of the displacement map for this mesh. The use of this card with the latest GPU accelerates the real-time calculations of visualisation.

Healthcare collaborative processes still encounter major challenges, particularly regarding the interoperability of heterogeneous information systems, the traceability of medical interventions, and the secure sharing of patient data under strict privacy regulations such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA). This paper presents a patient-centric, blockchain-based framework designed to overcome these limitations. The proposed solution integrates smart contracts and non-fungible tokens (NFTs) within the Ethereum blockchain to ensure data integrity, traceability, and privacy preservation. Furthermore, a compliance-by-design mechanism is embedded into the smart contracts to enable self-supervision of collaborative workflows without third-party intervention. A Proof-of-Authority (PoA) consensus protocol is also adopted to optimize validation efficiency and significantly reduce computational and energy costs.