Blockchain-based Edge Resource Sharing for Metaverse
Blockchain-based Edge Resource Sharing for Metaverse
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DOI：
10.1109/mass56207.2022.00092
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发表时间：
2022-08
期刊：
影响因子：
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通讯作者：
Zhilin Wang;Qin Hu;Minghui Xu;Honglu Jiang
中科院分区：
文献类型：
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作者：
Zhilin Wang;Qin Hu;Minghui Xu;Honglu Jiang
虽然Metaverse近年来得到了广泛的研究，但其实际应用仍面临着许多挑战。严峻的挑战之一是本地设备上缺乏足够的计算和通信资源，导致无法访问Metaverse服务。为了解决这个问题，本文提出了一个实用的基于区块链的移动的边缘计算（MEC）平台，用于资源共享和优化利用，以完成请求的卸载任务，考虑到服务器的可用资源和用户的任务请求的异构性。具体来说，我们首先详细说明我们提出的系统的设计，然后深入研究任务分配机制，将卸载任务分配给适当的服务器。为了在多项式时间内解决多任务分配问题，我们设计了一个基于学习的算法。由于MTA的目标函数和约束条件受到上传任务的服务器的显著影响，我们将其重新表示为强化学习问题，并考虑服务器的影响计算每个状态和动作的奖励。最后，大量的实验证明了我们提出的系统和算法的有效性和效率。
Although Metaverse has recently been widely stud-ied, its practical application still faces many challenges. One of the severe challenges is the lack of sufficient resources for computing and communication on local devices, resulting in the inability to access the Metaverse services. To address this issue, this paper proposes a practical blockchain-based mobile edge computing (MEC) platform for resource sharing and optimal utilization to complete the requested offloading tasks, given the heterogeneity of servers' available resources and that of users' task requests. To be specific, we first elaborate the design of our proposed system and then dive into the task allocation mechanism to assign offloading tasks to proper servers. To solve the multiple task allocation (MTA) problem in polynomial time, we devise a learning-based algorithm. Since the objective function and constraints of MTA are significantly affected by the servers uploading the tasks, we reformulate it as a reinforcement learning problem and calculate the rewards for each state and action considering the influences of servers. Finally, numerous experiments are conducted to demonstrate the effectiveness and efficiency of our proposed system and algorithms.