Paper Info
Title
Towards Redundancy-Aware Data Utility Maximization in Crowdsourced Sensing with Smartphones
Abstract
This paper studies the critical problem of maximizing the aggregate data utility under budget constraint in mobile crowd sourced sensing. This problem is particularly challenging given the redundancy in sensing data, self-interested and strategic user behaviors, and private cost information of smartphones. Most of existing approaches do not consider the important performance objective - maximizing the redundancy-aware data utility of sensing data collected from smartphones. Furthermore, they do not consider the practical constraint on budget. In this paper, we propose a combinatorial auction mechanism based on a reverse auction framework. It consists of an approximation algorithm for winning bids determination and a critical payment scheme. The approximation algorithm guarantees a constant approximation ratio at polynomial-time complexity. The critical payment scheme guarantees truthful bidding. The rigid theoretical analysis demonstrates that our mechanism achieves truthfulness, individual rationality, computational efficiency, and budget feasibility. Extensive simulations show that the proposed mechanism produces high redundancy-aware data utility.
Year
DOI
Venue
2015
10.1109/ICPP.2015.99
2015 44th International Conference on Parallel Processing
Keywords
Field
DocType
Mobile crowdsourcing,Redundancy-aware,Auction,Truthful,Budget Feasibility
Data modeling,Approximation algorithm,Budget constraint,Combinatorial auction,Computer science,Redundancy (engineering),Aggregate data,Reverse auction,Bidding,Distributed computing
Conference
ISSN
Citations 
PageRank 
0190-3918
3
0.37
References 
Authors
15
5
Name
Order
Citations
PageRank
Juan Li1274.32
Yanmin Zhu21767142.50
Jiadi Yu337157.86
Qian Zhang45483343.05
Lionel M. Ni59462802.67