The metaverse is regarded as a new wave of technological transformation that provides a virtual space for people to interact with each other through digital avatars. To achieve immersive user experiences in the metaverse, real-time rendering is the key technology. However, computing intensive tasks of real-time graphic and audio rendering from metaverse service providers cannot be processed efficiently on a single resource-limited mobile and Internet of Things (IoT) device. Alternatively, such devices can adopt the collaborative computing paradigm based on Coded Distributed Computing (CDC) to support metaverse services. Therefore, this paper introduces a reliable collaborative CDC framework for metaverse. In the framework, idle resources from mobile devices, acting as CDC workers, are aggregated to handle intensive computation tasks in the metaverse. A coalition can be formed among reliable workers based on a reputation metric which is maintained in a double blockchains database. The framework also considers an incentive to attract reliable workers to participate and process computation tasks of metaverse services. Moreover, the framework is designed with a hierarchical structure composed of coalition formation and Stackelberg games in the lower and upper levels to determine stable coalitions and rewards for reliable workers, respectively. The simulation results illustrate that the proposed framework is resistant to malicious workers. Compared with the random worker selection scheme, the proposed coalition formation and Stackelberg game can improve the utilities of both metaverse service providers and CDC workers.
翻译:元体被视为一种新的技术变革浪潮,它为人们通过数字变异器相互交流提供了虚拟空间。为了实现用户在全新、实时转换中的沉浸式用户经验,关键技术是关键技术。然而,在单一的资源有限的移动和物联网(IoT)设备上,无法高效地处理元体服务提供者的实时图形和音频转换的密集任务。或者,这些装置可以采用基于编码分布式计算机(CDC)的合作计算模式,以支持元体服务。因此,本文件引入了一个可靠的CDC合作元体框架。在这个框架中,移动设备作为CDC工人的闲置资源被集中起来,以便在元体中处理密集的计算任务。可以基于双链数据库所维护的声誉计量标准,在可靠的工人中组成一个联盟。框架还考虑了吸引可靠的工人参与和处理计算元体体服务任务的一种激励因素。此外,框架的设计结构由联盟组成,以及上下层和上层的斯塔克尔格游戏组成一个可靠的合作框架。在这个框架中,移动设备的闲置资源资源,作为CDC的工人在元体中处理密集计算任务; 提议的Stailal 系统选择工人的模型可以分别用来说明稳定的联盟和标准结构,用以衡量和标准。提议的Stailal的工人的升级的工人的升级的升级的计算结果。提议,可以改进。