Distributed Double Auctions for Large-Scale Device-to-Device Resource Trading
Shuqin Gao, Costas Courcoubetis, Lingjie Duan

TL;DR
This paper introduces a distributed double auction mechanism for large-scale device-to-device resource trading in wireless networks, addressing scalability and truthful reporting issues with a novel market model and algorithms.
Contribution
It proposes a scalable, distributed D2D trading market model with a new pricing mechanism that incentivizes truthful reporting and achieves near-optimal resource allocation.
Findings
Achieves near-optimal allocative efficiency using a greedy matching algorithm.
Ensures truthful reporting through a distributed pricing mechanism.
Analyzes optimal trading frequency over multiple rounds.
Abstract
Mobile users in future wireless networks face limited wireless resources such as data plan, computation capacity and energy storage. Given that some of these users may not be utilizing fully their wireless resources, device-to-device (D2D) resource sharing is a promising approach to exploit users' diversity in resource use and for pooling their resources locally. In this paper, we propose a novel two-sided D2D trading market model that enables a large number of locally connected users to trade resources. Traditional resource allocation solutions are mostly centralized without considering users' local D2D connectivity constraints, becoming unscalable for large-scale trading. In addition, there may be market failure since selfish users will not truthfully report their actual valuations and quantities for buying or selling resources. To address these two key challenges, we first…
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Taxonomy
TopicsAuction Theory and Applications · Optimization and Search Problems · Advanced Bandit Algorithms Research
