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Xi Fang

Researcher at Arizona State University

Publications -  39
Citations -  7542

Xi Fang is an academic researcher from Arizona State University. The author has contributed to research in topics: Wireless network & Approximation algorithm. The author has an hindex of 23, co-authored 39 publications receiving 6875 citations.

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Journal ArticleDOI

Smart Grid — The New and Improved Power Grid: A Survey

TL;DR: In this paper, the authors survey the literature till 2011 on the enabling technologies for the Smart Grid and explore three major systems, namely the smart infrastructure system, the smart management system, and the smart protection system.

Smart Grid - The New and Improved Power Grid:

TL;DR: This article surveys the literature till 2011 on the enabling technologies for the Smart Grid, and explores three major systems, namely the smart infrastructure system, the smart management system, and the smart protection system.
Proceedings ArticleDOI

Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing

TL;DR: This work designs an auction-based incentive mechanism for mobile phone sensing that is computationally efficient, individually rational, profitable, and truthful, and shows how to compute the unique Stackelberg Equilibrium, at which the utility of the platform is maximized.
Journal ArticleDOI

Incentive mechanisms for crowdsensing: crowdsourcing with smartphones

TL;DR: This work designs an auction-based incentive mechanism for crowdsensing, which is computationally efficient, individually rational, profitable, and truthful, and shows how to compute the unique Stackelberg Equilibrium, at which the utility of the crowdsourcer is maximized.
Journal ArticleDOI

Coping with a Smart Jammer in Wireless Networks: A Stackelberg Game Approach

TL;DR: This paper proves the existence and uniqueness of the Stackelberg Equilibrium (SE) by giving closed-form expressions for the SE strategies of both the user and the player and designs algorithms for computing the jammer's best response strategy and approximating the user's optimal strategy.