Revenue maximizing auction for perishable IoT resources

Maria Barbara Safianowska, Robert Gdowski, Ching-Yao Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

In near future autonomous things will trade services on IoT marketplaces. However, in the resulting recurrent combinatorial auctions, the bidder drop causes the market collapse in a low competition scenario. Adding fairness can prevent this, however the resulting revenue is not optimal. We show that revenue may be improved above fairness solution by alternating winners only within minimum set of strongest bidders. We introduce and compare two algorithms: Proportional Fair Auction and Revenue Maximizing Auction. The second algorithm performs the best in both high and low competition scenario, making it best suited to IoT when revenue maximization is a goal.

Original languageEnglish
Title of host publication2016 International Conference on Information and Communication Technology Convergence, ICTC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages417-422
Number of pages6
ISBN (Electronic)9781509013258
DOIs
StatePublished - 30 Nov 2016
Event2016 International Conference on Information and Communication Technology Convergence, ICTC 2016 - Jeju Island, Korea, Republic of
Duration: 19 Oct 201621 Oct 2016

Publication series

Name2016 International Conference on Information and Communication Technology Convergence, ICTC 2016

Conference

Conference2016 International Conference on Information and Communication Technology Convergence, ICTC 2016
CountryKorea, Republic of
CityJeju Island
Period19/10/1621/10/16

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