Document Type
Article
Publication Date
4-13-2020
Journal / Book Title
Sensors
Abstract
In mobile crowdsensing, some users jointly finish a sensing task through the sensors equipped in their intelligent terminals. In particular, the photo crowdsensing based on Mobile Edge Computing (MEC) collects pictures for some specific targets or events and uploads them to nearby edge servers, which leads to richer data content and more efficient data storage compared with the common mobile crowdsensing; hence, it has attracted an important amount of attention recently. However, the mobile users prefer uploading the photos through Wifi APs (PoIs) rather than cellular networks. Therefore, photos stored in mobile phones are exchanged among users, in order to quickly upload them to the PoIs, which are actually the edge services. In this paper, we propose a utility-based Storage Management strategy in mobile phones for Photo Crowdsensing (SMPC), which makes a sending/deleting decision on a user’s device for either maximizing photo delivery ratio (SMPC-R) or minimizing average delay (SMPC-D). The decision is made according to the photo’s utility, which is calculated by measuring the impact of reproducing or deleting a photo on the above performance goals. We have done simulations based on the random-waypoint model and three real traces: roma/taxi, epfl, and geolife. The results show that, compared with other storage management strategies, SMPC-R gets the highest delivery ratio and SMPC-D achieves the lowest average delay.
DOI
10.3390/s20082199
Journal ISSN / Book ISBN
EISSN 1424-8220
Montclair State University Digital Commons Citation
Wang, En; Qu, Zhengdao; Liang, Xinyao; Meng, Xiangyu; Yang, Yongjian; Li, Dawei; and Meng, Weibin, "Storage Management Strategy in Mobile Phones for Photo Crowdsensing" (2020). Department of Computer Science Faculty Scholarship and Creative Works. 642.
https://digitalcommons.montclair.edu/compusci-facpubs/642
Published Citation
Wang, E., Qu, Z., Liang, X., Meng, X., Yang, Y., Li, D., & Meng, W. (2020). Storage Management Strategy in Mobile Phones for Photo Crowdsensing. Sensors, 20(8), 2199. https://doi.org/10.3390/s20082199
Included in
Artificial Intelligence and Robotics Commons, Databases and Information Systems Commons, Data Science Commons, Graphics and Human Computer Interfaces Commons, Information Security Commons, Mathematics Commons, Numerical Analysis and Scientific Computing Commons, OS and Networks Commons, Other Applied Mathematics Commons, Other Computer Sciences Commons, Programming Languages and Compilers Commons, Software Engineering Commons, Systems Architecture Commons, Theory and Algorithms Commons
Comments
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).