Resource Allocation for Edge Computing without Using Cloud Center in Smart Home Environment: A Pricing Approach
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. Th...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/22/6545 |
| _version_ | 1797547704035835904 |
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| author | Huan Liu Shiyong Li Wei Sun |
| author_facet | Huan Liu Shiyong Li Wei Sun |
| author_sort | Huan Liu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T14:48:58Z |
| format | Article |
| id | doaj.art-90e2f501814b4407be8e1f6296cda083 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T14:48:58Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-90e2f501814b4407be8e1f6296cda0832023-11-20T21:10:15ZengMDPI AGSensors1424-82202020-11-012022654510.3390/s20226545Resource Allocation for Edge Computing without Using Cloud Center in Smart Home Environment: A Pricing ApproachHuan Liu0Shiyong Li1Wei Sun2School of Economics and Management, Yanshan University, Qinhuangdao 066004, ChinaSchool of Economics and Management, Yanshan University, Qinhuangdao 066004, ChinaSchool of Economics and Management, Yanshan University, Qinhuangdao 066004, ChinaRecently, 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.https://www.mdpi.com/1424-8220/20/22/6545edge computingsmart homesresource pricingresource allocationutility optimization |
| spellingShingle | Huan Liu Shiyong Li Wei Sun Resource Allocation for Edge Computing without Using Cloud Center in Smart Home Environment: A Pricing Approach Sensors edge computing smart homes resource pricing resource allocation utility optimization |
| title | Resource Allocation for Edge Computing without Using Cloud Center in Smart Home Environment: A Pricing Approach |
| title_full | Resource Allocation for Edge Computing without Using Cloud Center in Smart Home Environment: A Pricing Approach |
| title_fullStr | Resource Allocation for Edge Computing without Using Cloud Center in Smart Home Environment: A Pricing Approach |
| title_full_unstemmed | Resource Allocation for Edge Computing without Using Cloud Center in Smart Home Environment: A Pricing Approach |
| title_short | Resource Allocation for Edge Computing without Using Cloud Center in Smart Home Environment: A Pricing Approach |
| title_sort | resource allocation for edge computing without using cloud center in smart home environment a pricing approach |
| topic | edge computing smart homes resource pricing resource allocation utility optimization |
| url | https://www.mdpi.com/1424-8220/20/22/6545 |
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