Revenue Maximizing Auction for Perishable IoT Resources

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.