Issue No. 04 - April (2012 vol. 11)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TMC.2011.113
Youngki Lee , KAIST, Daejeon
SangJeong Lee , KAIST, Daejeon
Byoungjip Kim , KAIST, Daejeon
Jungwoo Kim , KAIST, Daejeon
Yunseok Rhee , Hankuk University of Foreign Studies, Yongin
Junehwa Song , KAIST, Daejeon
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-performanceATP 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.
Y. Lee, J. Kim, J. Song, S. Lee, B. Kim and Y. Rhee, "Scalable Activity-Travel Pattern Monitoring Framework for Large-Scale City Environment," in IEEE Transactions on Mobile Computing, vol. 11, no. , pp. 644-662, 2011.