Ali Al Housseini
Efficient Service Provisioning in the Musical Metaverse Using a Custom Network Simulator.
Rel. Cristina Emma Margherita Rottondi. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2025
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Abstract
This thesis addresses the critical challenge of efficiently allocating network resources to support the demanding requirements of the Musical Metaverse. Leveraging the principles of Network Virtualization and Virtual Network Embedding (VNE), this work proposes a novel framework for optimizing the placement and routing of musical metaverse services. The unique characteristics of the Musical Metaverse, including ultra-low latency communication, stringent Quality of Service (QoS) requirements, and the need for precise synchronization in multi-user interactions, necessitate a specialized approach beyond traditional VNE solutions. To this end, the thesis introduces the Musical Metaverse Optimization (MusMOPT) model, which extends classical VNE to account for these specific demands.
Furthermore, a dedicated simulation environment, SiMusMet, is developed to rigorously evaluate the proposed models and algorithms
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