The market economy deals with many interacting agents such as buyers and sellers who are autonomous intelligent agents pursuing their own interests. One such multi-agent system (MAS) that plays an important role in auctions is the combinatorial auctioning system (CAS). We use this framework to define our concept of fairness in terms of what we call as "basic fairness" and "extended fairness". The assumptions of quasilinear preferences and dominant strategies are taken into consideration while explaining fairness. We give an algorithm to ensure fairness in a CAS using a Generalized Vickrey Auction (GVA). We use an algorithm of Sandholm to achieve optimality. Basic and extended fairness are then analyzed according to the dominant strategy solution concept.
A Distributed Combinatorial Auctioning System (DCAS) consisting of auctioneers and bidders who communicate by message passing has been proposed @cite_2 . Their work uses a fair division algorithm that is based on DCAS concept and model. It also discusses how basic and extended fairness implementations may be achieved in distributed resource allocation.
@cite_2
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Combinatorial Auctions are auctions where bidders can place bids on combinations of items, called packages or bundles, rather than just on individual items. In this paper we extend this concept to distributed system, by proposing a Distributed Combinatorial Auctioning System consisting of auctioneers and bidders who communicate by message-passing. We also propose a fair division algorithm that is based on our DCAS concept and model. Our model consist of auctioneers that are distributed in the system each having local bidders. Auctioneers collect local bids for the bundles. One of the auctioneers acts obtains all the bids from other auctioneers, and performs the computations necessary for the combinatorial auction. We also briefly discuss how basic and extended fairness are implemented in resource allocation by our algorithm. In this paper, we present a novel combinatorial auction (CA) based trading infrastructure to enable the supply and demand of Cloud services from different Cloud providers (CP). We propose a new auction policy that considers the relationship among CPs (mutual business relationship) in bidding mechanism. In our new auction-based market model, we allow the group of service providers to publish their bids collaboratively as a single bid to the auctioneer. It gives service providers a chance to autonomously find partners and make groups. Then they can use group strategy to increase their competitive power and compete for winning the bid (s). This will reduce conflicts, as well as collaboration cost and negotiation time, among participants as compare to existing CA-based market model. We implement our proposed market model of trading service in a simulated environment and study its economic efficiency with existing model. An innovative resource allocation scheme is proposed to improve the performance of device-to-device (D2D) communications as an underlay in the downlink (DL) cellular networks. To optimize the system sum rate over the resource sharing of both D2D and cellular modes, we introduce a sequential second price auction as the allocation mechanism. In the auction, all the spectrum resources are considered as a set of resource units, which are auctioned off by groups of D2D pairs in sequence. We first formulate the value of each resource unit for each D2D pair, as a basis of the proposed auction. And then a detailed auction algorithm is explained using a N-ary tree. The equilibrium path of a sequential second price auction is obtained in the auction process, and the state value of the leaf node in the end of the path represents the final allocation. The simulation results show that the proposed auction algorithm leads to a good performance on the system sum rate, efficiency and fairness. Naor, Pinkas, and Sumner introduced and implemented a sealed-bid, two-server auction system that is perhaps the most efficient and practical to date. Based on a cryptographic primitive known as oblivious transfer, their system aims to ensure privacy and correctness provided that at least one auction server behaves honestly. As observed in [19], however, the NPS system suffers from a security flaw in which one of the two servers can cheat so as to modify bids almost arbitrarily and without detection. We propose a means of repairing this flaw while preserving the attractive practical elements of the NPS protocol, including minimal round complexity for servers and minimal computation by players providing private inputs. Our proposal requires a slightly greater amount of computation and communication on the part of the two auction servers, but actually involves much less computation on the part of bidders. This latter feature makes our proposal particularly attractive for use with low-power devices. While the original proposal of NPS involved several dozen exponentiations for a typical auction, ours by contrast involves only several dozen modular multiplications. The key idea in our proposal is a form of oblivious transfer that we refer to as verifiable proxy oblimous transfer (VPOT).