Paper Info
Title
Budgeted video replacement policy in mobile crowdsensing.
Abstract
Mobile crowdsensing offers a new platform that recruits a suitable set of users to collectively complete an information collection/sensing task through users’ equipped devices. As a special case, video crowdsensing is to collect different video segments of the same event that are taken separately by the built-in cameras of mobile devices, and then combine them into a complete video. Mobile crowdsensing has attracted considerable attention recently due to the rich information that can be provided by videos. However, because of the limited caching space, a suitable video replacement policy is necessary. In this paper, we propose a Budgeted Video replaCement policy in mobile Video crowdsensing (BVCV), which first determines a video segment’s value according to its caching situation and natural attributes. Then, we formulate the video caching problem as a budgeted maximum coverage problem, which is a well-known NP-hard problem. Finally, we propose a practical greedy solution and also infer the approximate ratio, which could be regarded as the lower bound of BVCV to the optimal solution. Our experiments with the real mobility datasets (StudentLife dataset, Buffalo/phonelab-wifi dataset) show that, the proposed budgeted video replacement policy achieves a longer successfully delivered video length, compared with other general replacement policies.
Year
DOI
Venue
2020
10.1016/j.jpdc.2019.10.003
Journal of Parallel and Distributed Computing
Keywords
Field
DocType
Mobile video crowdsensing,Replacement policy,Budgeted,NP-hard
Maximum coverage problem,Upper and lower bounds,Computer science,Crowdsensing,Mobile device,Distributed computing,Special case
Journal
Volume
ISSN
Citations 
136
0743-7315
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
En Wang15715.09
Yongjian Yang23914.05
Jie Wu32311.49
Kaihao Lou452.41
Wenbin Liu53111.66
Yuanbo Xu611.38