  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.
