边缘计算支持的元宇宙资源分配综合调查

IF 13.3 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Computer Science Review Pub Date : 2024-09-09 DOI:10.1016/j.cosrev.2024.100680
Tanmay Baidya, Sangman Moh
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引用次数: 0

摘要

随着虚拟现实和增强现实技术的快速发展,大规模物联网网络和即将到来的 6 G 通信催生了一个名为 "元宇宙 "的新兴概念,它有望通过提供介于现实和虚拟之间的沉浸式体验,彻底改变我们与数字世界的交互方式。边缘计算是另一种新模式,它通过增强实时交互和减少延迟,提供反应灵敏、无缝衔接的虚拟环境,从而推动元宇宙功能的发展。然而,要充分发挥元宇宙的潜力,需要动态、高效的资源分配策略,以应对各种应用对通信、计算和存储资源的巨大需求。本研究全面探讨了边缘计算支持的元宇宙背景下的资源分配策略,研究了这一快速发展领域的各种挑战、现有技术和新兴趋势。我们首先探讨了元宇宙的基本特征和边缘计算的关键作用,然后研究了各种类型的资源及其关键问题和挑战。我们还简要讨论了卸载和缓存策略,这也是这方面最突出的研究课题。在本研究中,我们对 35 种不同的资源分配策略进行了比较和分析,对 19 种算法进行了基准测试,并调查了它们在各种元数据场景中的适用性,提供了比现有调查更广泛的范围。该调查旨在为研究人员和从业人员提供全面指导,帮助他们应对元海外资源分配的复杂性,支持开发更高效、可扩展和以用户为中心的虚拟环境。
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Comprehensive survey on resource allocation for edge-computing-enabled metaverse

With the rapid evaluation of virtual and augmented reality, massive Internet of Things networks and upcoming 6 G communication give rise to an emerging concept termed the “metaverse,” which promises to revolutionize how we interact with the digital world by offering immersive experiences between reality and virtuality. Edge computing, another novel paradigm, propels the metaverse functionality by enhancing real-time interaction and reducing latency, providing a responsive and seamless virtual environment. However, realizing the full potential of the metaverse requires dynamic and efficient resource-allocation strategies to handle the immense demand for communicational, computational, and storage resources required by its diverse applications. This survey comprehensively explores resource-allocation strategies in the context of an edge-computing-enabled metaverse, investigating various challenges, existing techniques, and emerging trends in this rapidly expanding field. We first explore the underlying metaverse characteristics and pivotal role of edge computing, after which we investigate various types of resources and their key issues and challenges. We also provide a brief discussion on offloading and caching strategies, which are the most prominent research issues in this context. In this study, we compare and analyze 35 different resource-allocation strategies, benchmark 19 algorithms, and investigate their suitability across diverse metaverse scenarios, offering a broader scope than existing surveys. The survey aims to serve as a comprehensive guide for researchers and practitioners, helping them navigate the complexities of resource allocation in the metaverse and supporting the development of more efficient, scalable, and user-centric virtual environments.

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来源期刊
Computer Science Review
Computer Science Review Computer Science-General Computer Science
CiteScore
32.70
自引率
0.00%
发文量
26
审稿时长
51 days
期刊介绍: Computer Science Review, a publication dedicated to research surveys and expository overviews of open problems in computer science, targets a broad audience within the field seeking comprehensive insights into the latest developments. The journal welcomes articles from various fields as long as their content impacts the advancement of computer science. In particular, articles that review the application of well-known Computer Science methods to other areas are in scope only if these articles advance the fundamental understanding of those methods.
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