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Osmotic computing-based service migration and resource scheduling in Mobile Augmented Reality Networks (MARN)

机译:移动增强现实网络(MARN)中基于渗透计算的服务迁移和资源调度

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Resources and services between the servers in Mobile Augmented Reality Networks (MARN) are tedious to manage. These networks comprise users possessing Augmented Reality (AR)-Virtual Reality (VR) applications. Low latency, robustness, and tolerance are the key requirements of these networks, which can be attained by using near-user solutions such as edge computing. However, management of services and scheduling them to near-user servers in an integrated environment of edge and public/private infrastructure are complex tasks. These require an optimal solution, which can be obtained by using "Osmotic Computing", that has been recently proposed as a paradigm for the integration of edge and public/private cloud. This paper uses osmotic computing for effectively migrating and scheduling the services between the servers of the different layers. The paper also presents the details on various components that are used for applying osmotic computing to a network followed by core applications, types, service classification, migration, and scheduling through the rules of osmotic game formulated for its operations. The evaluations are conducted on 100,000 requests and the proposed approach shows significant performance with the probability of the error being 0.1 at 55.72% conservation of the energy and memory resources for the entire network despite the increasing number of users. The proposed approach also satisfies the conditions of the joint optimization functions presented in the system model and demonstrates that the system holds true even with varying users, thus, proving its robustness and tolerance against the number of users. (C) 2019 Published by Elsevier B.V.
机译:移动增强现实网络(MARN)中服务器之间的资源和服务管理起来很繁琐。这些网络包括拥有增强现实(AR)-虚拟现实(VR)应用程序的用户。低延迟,鲁棒性和容忍度是这些网络的关键要求,这可以通过使用边缘计算等近用户解决方案来实现。但是,在边缘和公共/私有基础结构的集成环境中管理服务并将它们调度到附近的用户服务器是复杂的任务。这些需要一种最佳解决方案,该解决方案可以通过使用“渗透计算”来获得,最近已提出该解决方案作为边缘与公共/私有云集成的范例。本文使用渗透计算来有效地迁移和调度不同层服务器之间的服务。本文还介绍了用于将渗透计算应用于网络的各种组件的详细信息,然后通过为其操作制定的渗透游戏规则,介绍了核心应用,类型,服务分类,迁移和调度。评估是针对100,000个请求进行的,所提出的方法显示出显着的性能,尽管用户数量不断增加,但整个网络的能源和内存资源节省率达到55.72%时,错误概率为0.1。所提出的方法还满足了系统模型中提出的联合优化功能的条件,并证明了即使用户变化,该系统也适用,从而证明了其鲁棒性和对用户数量的耐受性。 (C)2019由Elsevier B.V.发布

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