{"title":"A new multi-agent group-buying auction for automated VM-to-Customer mapping","authors":"Puria Rad Jahanbani, Sepideh Adabi, A. Rezaee","doi":"10.1080/10919392.2020.1838847","DOIUrl":null,"url":null,"abstract":"ABSTRACT This paper aims to allocate cloud resources (i.e., Virtual Machines: VM) to customers by using an auction-based multi-agent system. Adding the concept of group-buying to auction makes the possibility of having more winners. Group-buying offers resources at a reduced price on the condition that the number of purchases reaches a minimum number. Subsequently, the rate of successful deals, the speed of reaching agreements and monetary utility of the participants (i.e., providers and customers) will be increased. Due to having a massive number of clients with different characteristics and providers with various VM types in the cloud environment, it is obligatory to make the process of group-buying auction fully automated. By doing this automation, customers will be relieved of serious troubles such as coalition for group-buying, comparing the resources, bidding at auctions and so on. Three main requirements of this automation are as follows: (1) clustering similar customers in rational groups, (2) selecting the most suitable resource for each customer/group of customers, and (3) bidding during auctions on behalf of each customer/group of customers. A particular algorithm for each one of these requirements is presented in this paper. Through simulation experiments, the results of evaluations showed how significantly the proposed cloud market system improved the success rate of customers, the average time taken in resource selection, the average of providers’ financial utility, and the average of customers’ financial utility.","PeriodicalId":54777,"journal":{"name":"Journal of Organizational Computing and Electronic Commerce","volume":"31 1","pages":"35 - 58"},"PeriodicalIF":2.0000,"publicationDate":"2021-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10919392.2020.1838847","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Organizational Computing and Electronic Commerce","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/10919392.2020.1838847","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 2
Abstract
ABSTRACT This paper aims to allocate cloud resources (i.e., Virtual Machines: VM) to customers by using an auction-based multi-agent system. Adding the concept of group-buying to auction makes the possibility of having more winners. Group-buying offers resources at a reduced price on the condition that the number of purchases reaches a minimum number. Subsequently, the rate of successful deals, the speed of reaching agreements and monetary utility of the participants (i.e., providers and customers) will be increased. Due to having a massive number of clients with different characteristics and providers with various VM types in the cloud environment, it is obligatory to make the process of group-buying auction fully automated. By doing this automation, customers will be relieved of serious troubles such as coalition for group-buying, comparing the resources, bidding at auctions and so on. Three main requirements of this automation are as follows: (1) clustering similar customers in rational groups, (2) selecting the most suitable resource for each customer/group of customers, and (3) bidding during auctions on behalf of each customer/group of customers. A particular algorithm for each one of these requirements is presented in this paper. Through simulation experiments, the results of evaluations showed how significantly the proposed cloud market system improved the success rate of customers, the average time taken in resource selection, the average of providers’ financial utility, and the average of customers’ financial utility.
期刊介绍:
The aim of the Journal of Organizational Computing and Electronic Commerce (JOCEC) is to publish quality, fresh, and innovative work that will make a difference for future research and practice rather than focusing on well-established research areas.
JOCEC publishes original research that explores the relationships between computer/communication technology and the design, operations, and performance of organizations. This includes implications of the technologies for organizational structure and dynamics, technological advances to keep pace with changes of organizations and their environments, emerging technological possibilities for improving organizational performance, and the many facets of electronic business.
Theoretical, experimental, survey, and design science research are all welcome and might look at:
• E-commerce
• Collaborative commerce
• Interorganizational systems
• Enterprise systems
• Supply chain technologies
• Computer-supported cooperative work
• Computer-aided coordination
• Economics of organizational computing
• Technologies for organizational learning
• Behavioral aspects of organizational computing.