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ORCID
https://orcid.org/0009-0003-7311-5378
Access Type
Campus-Only Access for Five (5) Years
Document Type
thesis
Embargo Period
1-16-2024
Degree Program
Electrical & Computer Engineering
Degree Type
Master of Science in Electrical and Computer Engineering (M.S.E.C.E.)
Year Degree Awarded
2024
Month Degree Awarded
February
Abstract
As the Metaverse evolves with developments in AI, semantic communication, edge computing, and blockchain, it faces the challenge of adapting to dynamic environments and increasing communication and computational needs. In this paper, we propose an edge blockchain architecture for the dynamic Metaverse that relies on unmanned aerial vehicle (UAV) swarms comprising a central collection UAV and several UAV servers. We optimize the selection of UAV servers and computing resource allocation to match the characteristics of tasks from different semantic environments with their respective communication and computational needs. To solve the problem, we develop a particle swarm optimization-based collection-edge mobility algorithm (PSO-CEMA) to optimize UAV server deployment and adapt their positions to meet the task requirements. Additionally, we present a dual-queue system and a Lyapunov drift function-based dynamic programming task allocation algorithm (LDF-DPTAA) to facilitate timely task allocation with reduced complexity. Furthermore, to optimize the allocation of computational resources dynamically, we adopt lifelong learning and design a collection-edge joint training and processing algorithm (LL-CJTPA). Simulation results show that our approach effectively optimizes edge servers' positions and task allocation, reduces the collection UAV's training time in new task environments, and enhances the stability and efficiency of the network in dynamic settings while reducing congestion.
First Advisor
Beatriz Lorenzo
Second Advisor
Hossein Pishro-Nik
Third Advisor
Fatima Anwar
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.
Recommended Citation
Wang, Ning, "Semantic-Aware Blockchain Architecture Design for Lifelong Edge-enabled Metaverse" (2024). Masters Theses. 1420.
https://scholarworks.umass.edu/masters_theses_2/1420