Scalable Activity-Travel Pattern Monitoring Framework for Large-scale City Environment
In this paper, we introduce Activity Travel Pattern (ATP) monitoring in a large-scale city environment. ATP represents where city residents and vehicles stay and how they travel around in a complex megacity. Monitoring ATP will incubate new types of value-added services such as predictive mobile advertisement, demand forecasting for urban stores, and adaptive transportation scheduling. To enable ATP monitoring, we develop ActraMon, a high-performance ATP monitoring framework. As a first step, ActraMon provides a simple but effective computational model of ATP and a declarative query language facilitating effective specification of various ATP monitoring queries. More important, ActraMon employs the shared staging architecture and highly efficient processing techniques, which address the scalability challenges caused by massive location updates, a number of ATP monitoring queries and processing complexity of ATP monitoring. Finally, we demonstrate the extensive performance study of ActraMon using realistic city-wide ATP workloads.
Activity-travel pattern (ATP), monitoring, location data processing, scalable architecture, large-scale, city
Software and Cyber-Physical Systems
IEEE Transactions on Mobile Computing
LEE, Youngki; LEE, SangJeong; KIM, Byoungjip; KIM, Jungwoo; Rhee, Yunseok; and SONG, Junehwa.
Scalable Activity-Travel Pattern Monitoring Framework for Large-scale City Environment. (2012). IEEE Transactions on Mobile Computing. 11, (4), 644-662. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/2080