Preventing market collapse in auctions for perishable Internet of Things resources
Maria B Safianowska,
Robert Gdowski and
ChingYao Huang
International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 11, 1550147717743693
Abstract:
We are entering the era of digital business moments where autonomous things will buy and sell services from each other in order to make people’s life easier. They will also negotiate in order to achieve the best price for their services which will result in Internet of Things auctions. Such auctions will be combinatorial and recurrent. Recurrent auctions pose a problem of bidder drop which leads to market collapse. Moreover, in Internet of Things, bidders will employ different strategies according to their pattern of consuming resources. We describe two bidding strategies which may lead to market collapse or very low revenue: opportunistic and periodic bidding. We devise two algorithms: revenue maximizing auction and highest bid lock auction, analyze their performance under these two bidding strategies, and compare them to traditional combinatorial auction. We find out that the revenue maximizing auction prevents market collapse under opportunistic bidding while highest bid lock auction provides the highest revenue under both strategies.
Keywords: Combinatorial auction; recurrent auction; bidding strategy; Internet of Things (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:
Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1550147717743693 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:11:p:1550147717743693
DOI: 10.1177/1550147717743693
Access Statistics for this article
More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().