User Connection and Resource Allocation Optimization in Blockchain Empowered Metaverse over 6G Wireless Communications

Fuente: arXiv
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Main Authors: Qian, Liangxin, Liu, Chang, Zhao, Jun
Format: Preprint
Published: 2024
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author Qian, Liangxin
Liu, Chang
Zhao, Jun
author_facet Qian, Liangxin
Liu, Chang
Zhao, Jun
contents The convergence of blockchain, Metaverse, and non-fungible tokens (NFTs) brings transformative digital opportunities alongside challenges like privacy and resource management. Addressing these, we focus on optimizing user connectivity and resource allocation in an NFT-centric and blockchain-enabled Metaverse in this paper. Through user work-offloading, we optimize data tasks, user connection parameters, and server computing frequency division. In the resource allocation phase, we optimize communication-computation resource distributions, including bandwidth, transmit power, and computing frequency. We introduce the trust-cost ratio (TCR), a pivotal measure combining trust scores from users' resources and server history with delay and energy costs. This balance ensures sustained user engagement and trust. The DASHF algorithm, central to our approach, encapsulates the Dinkelbach algorithm, alternating optimization, semidefinite relaxation (SDR), the Hungarian method, and a novel fractional programming technique from a recent IEEE JSAC paper [2]. The most challenging part of DASHF is to rewrite an optimization problem as Quadratically Constrained Quadratic Programming (QCQP) via carefully designed transformations, in order to be solved by SDR and the Hungarian algorithm. Extensive simulations validate the DASHF algorithm's efficacy, revealing critical insights for enhancing blockchain-Metaverse applications, especially with NFTs.
format Preprint
id arxiv_https___arxiv_org_abs_2403_05116
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle User Connection and Resource Allocation Optimization in Blockchain Empowered Metaverse over 6G Wireless Communications
Qian, Liangxin
Liu, Chang
Zhao, Jun
Emerging Technologies
Networking and Internet Architecture
Signal Processing
The convergence of blockchain, Metaverse, and non-fungible tokens (NFTs) brings transformative digital opportunities alongside challenges like privacy and resource management. Addressing these, we focus on optimizing user connectivity and resource allocation in an NFT-centric and blockchain-enabled Metaverse in this paper. Through user work-offloading, we optimize data tasks, user connection parameters, and server computing frequency division. In the resource allocation phase, we optimize communication-computation resource distributions, including bandwidth, transmit power, and computing frequency. We introduce the trust-cost ratio (TCR), a pivotal measure combining trust scores from users' resources and server history with delay and energy costs. This balance ensures sustained user engagement and trust. The DASHF algorithm, central to our approach, encapsulates the Dinkelbach algorithm, alternating optimization, semidefinite relaxation (SDR), the Hungarian method, and a novel fractional programming technique from a recent IEEE JSAC paper [2]. The most challenging part of DASHF is to rewrite an optimization problem as Quadratically Constrained Quadratic Programming (QCQP) via carefully designed transformations, in order to be solved by SDR and the Hungarian algorithm. Extensive simulations validate the DASHF algorithm's efficacy, revealing critical insights for enhancing blockchain-Metaverse applications, especially with NFTs.
title User Connection and Resource Allocation Optimization in Blockchain Empowered Metaverse over 6G Wireless Communications
topic Emerging Technologies
Networking and Internet Architecture
Signal Processing
url https://arxiv.org/abs/2403.05116