Data quality guarantee for credible caching device selection in mobile crowdsensing systems
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
Crowdsensing
Systems
(MCSs)
present a flexible and economical alternative to traditional
infrastructure based large-scale sensing through the
recruitment of personal mobile devices as data sources.
As this becomes a popular sensing approach it will impact
the capacity of typical centralized cellular communication
infrastructures widely adopted by MCS applications
and any costs accrued. Following the trend towards
edge processing, Mobile Edge Caching offloads data and
services from the system core to reduce service latency and
bandwidth occupation. However, in the MCS case the edge
device is owned by the general public and are therefore
more vulnerable to data or calculation manipulation by
the user. We now better understand sensor data and
user trustworthiness but have no way to determine which
of devices could also be trusted, i.e. act as a credible
caching device. In this article, we treat the quality of
sensing data reported by each user as an indication of
their possibility of providing credible caching services.
Specifically, we conduct a comprehensive study of the data
quality problem with regards to cache-enabled MCSs, and
develop an incentivization method to encourage users to
actively provide high quality data. That is, quality-aware
behavior evaluation is core to the credible caching device
selection process. Results of extensive simulations based
on real-world data verify the effectiveness of our design.
We also highlight several promising research directions
that remain open for further elaborations.
Systems
(MCSs)
present a flexible and economical alternative to traditional
infrastructure based large-scale sensing through the
recruitment of personal mobile devices as data sources.
As this becomes a popular sensing approach it will impact
the capacity of typical centralized cellular communication
infrastructures widely adopted by MCS applications
and any costs accrued. Following the trend towards
edge processing, Mobile Edge Caching offloads data and
services from the system core to reduce service latency and
bandwidth occupation. However, in the MCS case the edge
device is owned by the general public and are therefore
more vulnerable to data or calculation manipulation by
the user. We now better understand sensor data and
user trustworthiness but have no way to determine which
of devices could also be trusted, i.e. act as a credible
caching device. In this article, we treat the quality of
sensing data reported by each user as an indication of
their possibility of providing credible caching services.
Specifically, we conduct a comprehensive study of the data
quality problem with regards to cache-enabled MCSs, and
develop an incentivization method to encourage users to
actively provide high quality data. That is, quality-aware
behavior evaluation is core to the credible caching device
selection process. Results of extensive simulations based
on real-world data verify the effectiveness of our design.
We also highlight several promising research directions
that remain open for further elaborations.
Date Issued
2018-07-04
Date Acceptance
2018-01-23
Citation
IEEE Wireless Communications, 2018, 25 (3), pp.58-64
ISSN
1536-1284
Publisher
Institute of Electrical and Electronics Engineers
Start Page
58
End Page
64
Journal / Book Title
IEEE Wireless Communications
Volume
25
Issue
3
Copyright Statement
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
The Alan Turing Institute
Identifier
https://ieeexplore.ieee.org/document/8403952
Grant Number
ATIGA001
Subjects
Science & Technology
Technology
Computer Science, Hardware & Architecture
Computer Science, Information Systems
Engineering, Electrical & Electronic
Telecommunications
Computer Science
Engineering
0906 Electrical and Electronic Engineering
0805 Distributed Computing
1005 Communications Technologies
Networking & Telecommunications
Publication Status
Published
Date Publish Online
2018-07-04