Title
Cost-Effective Sensor Data Collection from Internet-of-Things Zones Using Existing Transportation Fleets
Abstract
Modern IoT devices are equipped with media-rich sensors that generate a heavy burden to local access networks. To improve the efficiency of data collection, we introduce the concept of "IoT zones" as geographically-correlated clusters of local IoT devices with well connected wireless networks that may have limited access to the Internet. We develop techniques to create a cost-effective data collection network using existing transportation fleets with predefined schedules to collect sensor data from IoT zones and upload them at locations with better network connectivity. Specifically, we provide solutions to the upload point placement and upload path planning problems given tradeoffs between collection quality, timing needs (QoS), and installation cost. We evaluate our approaches using a real-world bus network in Orange County, CA and study the applicability and efficiency of the proposed method as compared to several other approaches. The trace-driven simulations reveal that our best-performing algorithm: upload point selection (UPS) algorithm significantly outperforms others, e.g., in one of the scenarios with 160 total cost, it achieves sub-21 sec data transfer time (15+ times improvement), sub 3.2% late delivery ratio (about 12 times improvement), and above 96% data delivery ratio (about 50% improvement). In addition, it achieves the above performance without excessive installation cost: even when a cost limit of 640 is given, UPS algorithm opts for a solution with about 160 total cost (versus 640 from others).
Year
DOI
Venue
2019
10.1109/SMARTCOMP.2019.00071
2019 IEEE International Conference on Smart Computing (SMARTCOMP)
Keywords
Field
DocType
IoT zones,data collection,transportation fleet,upload point placement,upload path planning
Data collection,Wireless network,Bus network,Computer science,Upload,Quality of service,Computer network,Total cost,Access network,The Internet
Conference
ISBN
Citations 
PageRank 
978-1-7281-1690-7
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Fangqi Liu100.34
Qiuxi Zhu2182.80
Md. Yusuf Sarwar Uddin300.68
Cheng-Hsin Hsu499181.56
Nalini Venkatasubramanian51426137.46