UM
Traffic At-a-Glance: Time-Bounded Analytics on Large Visual Traffic Data
Li, Gang; Li, Xinfeng; Yang, Fan; Teng, Jin; Ding, Sihao; Zheng, Yuan F.; Xuan, Dong; Chen, Biao; Zhao, Wei
2017-09
Source PublicationIEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
ISSN1045-9219
Volume28Issue:9Pages:2703-2717
AbstractMassive visual traffic data have become available recently. Though it opens the realm of intelligent traffic analysis, processing the data in a timely manner is difficult yet critical to time sensitive decisions, which are typical to traffic related management. In this paper, we study time-bounded aggregation analytics on large visual traffic data including traffic images and videos. We first find that current MapReduce framework can not work well due to two challenges: first, significant dual diversities exist on data distributions and processing time; second, apriori knowledge on these distributions and time costs are not always available. However, we also observe spatial and temporal locality on data values and processing time. Based on the examination, we design Traffic At-a-Glance (TaG), an augmented MapReduce framework for time-bounded traffic analytics jobs. Particularly, we propose a novel sampling algorithm that exploits traffic data localities and stratifies samples based on data distributions and processing time. It runs in an iterative, adaptive manner without apriori knowledge. Moreover, we propose a heuristic scheduling algorithm with considerations of batch processing overhead. Further, we refine the load balancing mechanism based on data processing time locality to respect job time bounds. In addition, we extend TaG to well handle traffic videos by sampling video data based on motion information encoded in the videos. We implement TaG on Hadoop and conduct extensive experiments on a large visual traffic dataset. The evaluations on different data sizes show TaG is able to achieve high accuracy within time bounds.
KeywordTraffic analysis visual data big data MapReduce load balance
DOI10.1109/TPDS.2017.2684158
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000407484300022
PublisherIEEE COMPUTER SOC
The Source to ArticleWOS
Fulltext Access
Citation statistics
Cited Times [WOS]:3   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Recommended Citation
GB/T 7714
Li, Gang,Li, Xinfeng,Yang, Fan,et al. Traffic At-a-Glance: Time-Bounded Analytics on Large Visual Traffic Data[J]. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,2017,28(9):2703-2717.
APA Li, Gang.,Li, Xinfeng.,Yang, Fan.,Teng, Jin.,Ding, Sihao.,...&Zhao, Wei.(2017).Traffic At-a-Glance: Time-Bounded Analytics on Large Visual Traffic Data.IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,28(9),2703-2717.
MLA Li, Gang,et al."Traffic At-a-Glance: Time-Bounded Analytics on Large Visual Traffic Data".IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 28.9(2017):2703-2717.
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