Pratik Goswami, A. Mukherjee, Pushpita Chatterjee, Lixia Yang
{"title":"An Optimal Resource Allocation Method for IIoT Network","authors":"Pratik Goswami, A. Mukherjee, Pushpita Chatterjee, Lixia Yang","doi":"10.1145/3427477.3429988","DOIUrl":null,"url":null,"abstract":"The recent technical evolution is revolving around Internet of Things (IoT). The Internet of Softwarized Things (IoST) as a subset of IoT, is making its mark mostly towards industrial applications to connect all the devices and improve the computation capability and networking flexibility. The Industrial IoT (IIoT) consists of a large network, where the multiple works are processed continuously at a time. Therefore, multi-objective interference issue in the path remains as obstacle, for which the networking resources are lost. The existing works were performed with fixed resources and dedicated channel states which make the network less flexible with more time response. In this paper, the problem is addressed with optimal resource allocation using convolutional neural network (CNN) to extract the optimal channel state for different applications, which ease the computations along with efficiency. Furthermore, the proposed method is validated with the mathematical analysis and simulation.","PeriodicalId":435827,"journal":{"name":"Adjunct Proceedings of the 2021 International Conference on Distributed Computing and Networking","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Adjunct Proceedings of the 2021 International Conference on Distributed Computing and Networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3427477.3429988","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
The recent technical evolution is revolving around Internet of Things (IoT). The Internet of Softwarized Things (IoST) as a subset of IoT, is making its mark mostly towards industrial applications to connect all the devices and improve the computation capability and networking flexibility. The Industrial IoT (IIoT) consists of a large network, where the multiple works are processed continuously at a time. Therefore, multi-objective interference issue in the path remains as obstacle, for which the networking resources are lost. The existing works were performed with fixed resources and dedicated channel states which make the network less flexible with more time response. In this paper, the problem is addressed with optimal resource allocation using convolutional neural network (CNN) to extract the optimal channel state for different applications, which ease the computations along with efficiency. Furthermore, the proposed method is validated with the mathematical analysis and simulation.