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智能家居环境中不使用云中心的边缘计算资源分配:一种定价方法。

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

机构信息

School of Economics and Management, Yanshan University, Qinhuangdao 066004, China.

出版信息

Sensors (Basel). 2020 Nov 16;20(22):6545. doi: 10.3390/s20226545.

Abstract

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.

摘要

最近,越来越多的智能家居已成为家庭基础设施的重要组成部分之一。然而,大多数智能家居应用并未实现互联互通,仍处于孤立状态。它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,未来基于边缘计算而不使用云中心的智能家居将成为一个重要的研究领域。在本文中,我们假设智能家居环境中的所有应用程序均由边缘节点和用户组成。为了使用户的效用最大化,我们假设所有用户和边缘节点都位于一个市场中,并制定了一个以效用最大化为目标的定价资源分配模型。我们应用拉格朗日方法对模型进行了分析,因此,边缘节点(市场中的供应商)根据资源价格和与用户偏好相关的效用,向用户(市场中的客户)分配资源。为了获得最佳资源分配,我们提出了一种基于定价的资源分配算法,该算法使用低通滤波方案,并通过一些数值示例证明了该算法可以在合理的收敛时间内达到最优。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9296/7698201/bbad04a0f1da/sensors-20-06545-g001.jpg

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