Tender of computational works in heterogeneous distributed environment

Nowadays, applying various market-based methods for regulating supply and demand of resources for distributed computing is becoming increasingly relevant. In particular, different forms of standard auctions are actively used. However, their basic capabilities often do not enable to fully solve the complicated problems of resource allocation in a heterogeneous distributed computing environment. In this regard, a tender of computational works based on a combinatorial Vickrey auction has been designed. It is applied within multi-agent computing management. For the tender, new models are proposed to rank the criteria of resources owners and users. The tender use advantages are shown in comparison with traditional meta-schedulers.

Robust Auctions for Revenue via Enhanced Competition

In “Robust Auctions for Revenue via Enhanced Competition,” T. Roughgarden, I. Talgam-Cohen, and Q. Yan revisit the classic Bulow–Klemperer result. This result compares the revenues of two well-known auction formats: the welfare-maximizing Vickrey auction and the revenue-maximizing Myerson auction. It shows that, with an extra bidder competing for the item, the Vickrey auction becomes as good as the Myerson auction in terms of revenue while maintaining independence from prior distributional information about bidders’ valuations. Unfortunately, Myerson’s toolbox for revenue-optimal auction design does not extend to combinatorial auctions with multiple heterogenous items, for which optimizing revenue remains a challenge—especially if we want auction designs that are simple and robust enough to use in practice. This paper extends the Bulow–Klemperer result to multiple heterogenous items by showing that a prior-independent, simple, welfare-maximizing auction with additional competing bidders achieves as much revenue as the ill-understood optimal auction.

VCG under Sybil (False-Name) Attacks - A Bayesian Analysis

VCG is a classical combinatorial auction that maximizes social welfare. However, while the standard single-item Vickrey auction is false-name-proof, a major failure of multi-item VCG is its vulnerability to false-name attacks. This occurs already in the natural bare minimum model in which there are two identical items and bidders are single-minded. Previous solutions to this challenge focused on developing alternative mechanisms that compromise social welfare. We re-visit the VCG auction vulnerability and consider the bidder behavior in Bayesian settings. In service of that we introduce a novel notion, termed the granularity threshold, that characterizes VCG Bayesian resilience to false-name attacks as a function of the bidder type distribution. Using this notion we show a large class of cases in which VCG indeed obtains Bayesian resilience for the two-item single-minded setting.

Efficient multiunit auctions for normal goods

I study multiunit auction design when bidders have private values, multiunit demands, and non‐quasilinear preferences. Without quasilinearity, the Vickrey auction loses its desired incentive and efficiency properties. I give conditions under which we can design a mechanism that retains the Vickrey auction's desirable incentive and efficiency properties: (1) individual rationality, (2) dominant strategy incentive compatibility, and (3) Pareto efficiency. I show that there is a mechanism that retains the desired properties of the Vickrey auction if there are two bidders who have single‐dimensional types. I also present an impossibility theorem that shows that there is no mechanism that satisfies Vickrey's desired properties and weak budget balance when bidders have multidimensional types.