Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications (PerCom)
Department of Computer Science
Context-aware pervasive-computing applications require continuous monitoring of their physical and computational environment to make appropriate adaptation decisions in time. The data streams produced by sensors, however, may overflow the queues on the dissemination path. Traditional flow-control and congestion-control policies either drop data or force the sender to pause. When the data sender is sensing the physical environment, however, a pause is equivalent to dropping data. Instead of arbitrarily dropping data that may contain important events, we present a policy-driven data dissemination service named PACK, based on an overlay-based infrastructure for efficient multicast delivery. PACK enforces application-specified policies that define how to discard or summarize data flows wherever queues overflow on the data path, notably at the mobile hosts where applications often reside. A key contribution of our approach is to uniformly apply the data-stream “packing” abstraction to queue overflow caused by network congestion, slow receivers, and temporary disconnection. We present experimental results and a detailed application study of the PACK service.
Guanling Chen and David Kotz. Policy-Driven Data Dissemination for Context-Aware Applications. In Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications (PerCom), March 2005. DOI 10.1109/PERCOM.2005.32.
Dartmouth Digital Commons Citation
Chen, Guanling and Kotz, David, "Policy-Driven Data Dissemination for Context-Aware Applications" (2005). Dartmouth Scholarship. 3069.