{"title":"雾计算中时变多维资源分配与定价的组合拍卖机制","authors":"Shiyong Li, Yanan Zhang, Wei Sun, Jia Liu","doi":"10.34768/amcs-2023-0024","DOIUrl":null,"url":null,"abstract":"Abstract It is a hot topic to investigate resource allocation in fog computing. However, currently resource allocation in fog computing mostly supports only fixed resources, that is, the resource requirements of users are satisfied with a fixed amount of resources during the usage time, which may result in low utility of resource providers and even cause a waste of resources. Therefore, we establish an integer programming model for the time-varying multidimensional resource allocation problem in fog computing to maximize the utility of the fog resource pool. We also design a heuristic algorithm to approximate the solution of the model. We apply a dominant-resource-based strategy for resource allocation to improve resource utilization as well as critical value theory for resource pricing to enhance the utility of the fog resource pool. We also prove that the algorithm satisfies truthful and individual rationality. Finally, we give some numerical examples to demonstrate the performance of the algorithm. Compared with existing studies, our approach can improve resource utilization and maximize the utility of the fog resource pool.","PeriodicalId":50339,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"6 1","pages":"327 - 339"},"PeriodicalIF":1.6000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Combinatorial Auction Mechanism for Time–Varying Multidimensional Resource Allocation and Pricing in Fog Computing\",\"authors\":\"Shiyong Li, Yanan Zhang, Wei Sun, Jia Liu\",\"doi\":\"10.34768/amcs-2023-0024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract It is a hot topic to investigate resource allocation in fog computing. However, currently resource allocation in fog computing mostly supports only fixed resources, that is, the resource requirements of users are satisfied with a fixed amount of resources during the usage time, which may result in low utility of resource providers and even cause a waste of resources. Therefore, we establish an integer programming model for the time-varying multidimensional resource allocation problem in fog computing to maximize the utility of the fog resource pool. We also design a heuristic algorithm to approximate the solution of the model. We apply a dominant-resource-based strategy for resource allocation to improve resource utilization as well as critical value theory for resource pricing to enhance the utility of the fog resource pool. We also prove that the algorithm satisfies truthful and individual rationality. Finally, we give some numerical examples to demonstrate the performance of the algorithm. Compared with existing studies, our approach can improve resource utilization and maximize the utility of the fog resource pool.\",\"PeriodicalId\":50339,\"journal\":{\"name\":\"International Journal of Applied Mathematics and Computer Science\",\"volume\":\"6 1\",\"pages\":\"327 - 339\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Applied Mathematics and Computer Science\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.34768/amcs-2023-0024\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Applied Mathematics and Computer Science","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.34768/amcs-2023-0024","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
A Combinatorial Auction Mechanism for Time–Varying Multidimensional Resource Allocation and Pricing in Fog Computing
Abstract It is a hot topic to investigate resource allocation in fog computing. However, currently resource allocation in fog computing mostly supports only fixed resources, that is, the resource requirements of users are satisfied with a fixed amount of resources during the usage time, which may result in low utility of resource providers and even cause a waste of resources. Therefore, we establish an integer programming model for the time-varying multidimensional resource allocation problem in fog computing to maximize the utility of the fog resource pool. We also design a heuristic algorithm to approximate the solution of the model. We apply a dominant-resource-based strategy for resource allocation to improve resource utilization as well as critical value theory for resource pricing to enhance the utility of the fog resource pool. We also prove that the algorithm satisfies truthful and individual rationality. Finally, we give some numerical examples to demonstrate the performance of the algorithm. Compared with existing studies, our approach can improve resource utilization and maximize the utility of the fog resource pool.
期刊介绍:
The International Journal of Applied Mathematics and Computer Science is a quarterly published in Poland since 1991 by the University of Zielona Góra in partnership with De Gruyter Poland (Sciendo) and Lubuskie Scientific Society, under the auspices of the Committee on Automatic Control and Robotics of the Polish Academy of Sciences.
The journal strives to meet the demand for the presentation of interdisciplinary research in various fields related to control theory, applied mathematics, scientific computing and computer science. In particular, it publishes high quality original research results in the following areas:
-modern control theory and practice-
artificial intelligence methods and their applications-
applied mathematics and mathematical optimisation techniques-
mathematical methods in engineering, computer science, and biology.