Emergent Mind

Auction-based Incentive Mechanisms for Dynamic Mobile Ad-Hoc Crowd Service

(1503.06819)
Published Mar 23, 2015 in cs.NI and cs.GT

Abstract

We investigate a type of emerging user-assisted mobile applications or services, referred to as Dynamic Mobile Ad-hoc Crowd Service (DMACS), such as collaborative streaming via smartphones or location privacy protection through a crowd of smartphone users. Such services are provided and consumed by users carrying smart mobile devices (e.g., smartphones) who are in close proximity of each other (e.g., within Bluetooth range). Users in a DMACS system dynamically arrive and depart over time, and are divided into multiple possibly overlapping groups according to radio range constraints. Crucial to the success of such systems is a mechanism that incentivizes users' participation and ensures fair trading. In this paper, we design a multi-market, dynamic double auction mechanism, referred to as M-CHAIN, and show that it is truthful, feasible, individual-rational, no-deficit, and computationally efficient. The novelty and significance of M-CHAIN is that it addresses and solves the fair trading problem in a multi-group or multi-market dynamic double auction problem which naturally occurs in a mobile wireless environment. We demonstrate its efficiency via simulations based on generated user patterns (stochastic arrivals, random market clustering of users) and real-world traces.

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