Z. Javed, Z. Khan, J. J. Lehtomäki, H. Ahmadi and E. Hossain, "Eliciting Truthful Data From Crowdsourced Wireless Monitoring Modules in Cloud Managed Networks," in IEEE Access, vol. 8, pp. 173641-173653, 2020, doi: 10.1109/ACCESS.2020.3022569
Eliciting truthful data from crowdsourced wireless monitoring modules in cloud managed networks
|Author:||Javed, Zunera1; Khan, Zaheer1; Lehtomäki, Janne J.1;|
1Centre for Wireless Communications, University of Oulu, 90014 Oulu, Finland
2Department of Electronic Engineering, University of York, York YO10 5DD, U.K.
3Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
|Online Access:||PDF Full Text (PDF, 2.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020110389122
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-11-03
To facilitate efficient cloud managed resource allocation solutions, collection of key wireless metrics from multiple access points (APs) at different locations within a given area is required. In unlicensed shared spectrum bands collection of metric data can be a challenging task for a cloud manager as independent self-interested APs can operate in these bands in the same area. We propose to design an intelligent crowdsourcing solution that incentivizes independent APs to truthfully measure/report data relating to their wireless channel utilization (CU). Our work focuses on challenging scenarios where independent APs can take advantage of recurring patterns in CU data by utilizing distribution aware strategies to obtain higher reward payments. We design truthful reporting methods that utilize logarithmic and quadratic scoring rules for reward payments to the APs. We show that when measurement computation costs are considered then under certain scenarios these scoring rules no longer ensure incentive compatibility. To address this, we present a novel reward function which incorporates a distribution aware penalty cost that charges APs for distorting reports based on recurring patterns. Along with synthetic data, we also use real CU data values crowdsourced using multiple independent measuring/reporting devices deployed by us in the University of Oulu.
|Pages:||173641 - 173653|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported in part by the Infotech Oulu through the framework of the Digital Solutions in Sensing and Interactions, and in part by the Academy of Finland 6Genesis Flagship under Grant 318927.
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
© The Authors 2020. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.