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Resource Allocation for Edge Computing without Using Cloud Center in Smart Home Environment: A Pricing Approach

机译:边缘计算资源分配而不使用智能家庭环境中的云中心:定价方法

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摘要

Recently, more and more smart homes have become one of important parts of home infrastructure. However, most of the smart home applications are not interconnected and remain isolated. They use the cloud center as the control platform, which increases the risk of link congestion and data security. Thus, in the future, smart homes based on edge computing without using cloud center become an important research area. In this paper, we assume that all applications in a smart home environment are composed of edge nodes and users. In order to maximize the utility of users, we assume that all users and edge nodes are placed in a market and formulate a pricing resource allocation model with utility maximization. We apply the Lagrangian method to analyze the model, so an edge node (provider in the market) allocates its resources to a user (customer in the market) based on the prices of resources and the utility related to the preference of users. To obtain the optimal resource allocation, we propose a pricing-based resource allocation algorithm by using low-pass filtering scheme and conform that the proposed algorithm can achieve an optimum within reasonable convergence times through some numerical examples.
机译:最近,越来越多的智能家居已成为家庭基础设施的重要部分之一。但是,大多数智能家庭应用程序都不互连并保持孤立。他们使用云中心作为控制平台,这增加了链路拥塞和数据安全的风险。因此,在未来,基于边缘计算的智能家庭而不使用云中心成为重要的研究区域。在本文中,我们假设智能家庭环境中的所有应用程序都由边缘节点和用户组成。为了最大化用户的效用,我们假设所有用户和边缘节点都放在市场上,并用实用程序最大化制定定价资源分配模型。我们应用拉格朗日方法来分析模型,因此基于资源价格和与用户偏好相关的公用事业的资源价格以及与用户偏好相关的公用事业的边缘节点(市场提供商)将其资源分配给用户(市场)。为了获得最佳资源分配,我们通过使用低通滤波方案提出基于定价的资源分配算法,并符合所提出的算法可以通过一些数值示例在合理的收敛时间内实现最佳。

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