TY - GEN
T1 - Context activity selection and scheduling in context-driven simulation
AU - Lee, Jae Woong
AU - Helal, Abdelsalam
AU - Sung, Yunsick
AU - Cho, Kyungeun
PY - 2014
Y1 - 2014
N2 - Human activities in smart spaces are traced by sensors and logged, as sensor events, in the form of sensory values, when the sensors detect elements of the activities. The event-driven approach that models the combination of the sensor events is one of the most common human activity simulation approaches. However, this approach is scalewise challenged as activities and spaces get more complex. A large volume of sensor events demands more human efforts in modeling, and requires higher processing overhead. We observe that rather than simulating by combining sensor events, semantical abstraction could offer a scalable alternative in managing such complexity. In our previous work, we proposed a context-driven such an approach, which scales well in complex simulation. The approach evaluates current state space and advances the simulation loop by units of context, not by sensor events. By changing the domain of simulation from event to context, we could measure a remarkable performance advantage. Through the experiment, we noticed that activity design was critical to end performance. In this paper, therefore, we focus on modeling activities for a better fit to the contextdriven approach. We introduce a new activity model along with associated algorithms to select and schedule the activities. We also provide an evaluation of the performance and computational complexity of the algorithms.
AB - Human activities in smart spaces are traced by sensors and logged, as sensor events, in the form of sensory values, when the sensors detect elements of the activities. The event-driven approach that models the combination of the sensor events is one of the most common human activity simulation approaches. However, this approach is scalewise challenged as activities and spaces get more complex. A large volume of sensor events demands more human efforts in modeling, and requires higher processing overhead. We observe that rather than simulating by combining sensor events, semantical abstraction could offer a scalable alternative in managing such complexity. In our previous work, we proposed a context-driven such an approach, which scales well in complex simulation. The approach evaluates current state space and advances the simulation loop by units of context, not by sensor events. By changing the domain of simulation from event to context, we could measure a remarkable performance advantage. Through the experiment, we noticed that activity design was critical to end performance. In this paper, therefore, we focus on modeling activities for a better fit to the contextdriven approach. We introduce a new activity model along with associated algorithms to select and schedule the activities. We also provide an evaluation of the performance and computational complexity of the algorithms.
KW - Context
KW - Context-driven simulation
KW - Event-driven simulation
KW - Human activity simulation
UR - http://www.scopus.com/inward/record.url?scp=84901984245&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84901984245
SN - 9781632662156
T3 - Simulation Series
SP - 60
EP - 67
BT - Symposium on Theory of Modeling and Simulation - DEVS Integrative M and S Symposium, DEVS 2014; 2014 Spring Simulation Multi-Conference, SpringSim 2014
PB - The Society for Modeling and Simulation International
T2 - 2014 Symposium on Theory of Modeling and Simulation - DEVS Integrative M and S Symposium, DEVS 2014; 2014 Spring Simulation Multi-Conference, SpringSim 2014
Y2 - 13 April 2014 through 16 April 2014
ER -