Introduction to process-oriented simulation and CSIM (tutorial session)
WSC' 90 Proceedings of the 22nd conference on Winter simulation
Data mining: concepts and techniques
Data mining: concepts and techniques
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
CSIM19: CSIM19: a powerful tool for building system models
Proceedings of the 33nd conference on Winter simulation
Infrastructure tradeoffs for sensor networks
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Directed diffusion for wireless sensor networking
IEEE/ACM Transactions on Networking (TON)
RAP: A Real-Time Communication Architecture for Large-Scale Wireless Sensor Networks
RTAS '02 Proceedings of the Eighth IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'02)
Understanding packet delivery performance in dense wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
CODA: congestion detection and avoidance in sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
The Cougar Project: a work-in-progress report
ACM SIGMOD Record
Balancing energy efficiency and quality of aggregate data in sensor networks
The VLDB Journal — The International Journal on Very Large Data Bases
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
CAPS: Energy-Efficient Processing of Continuous Aggregate Queries in Sensor Networks
PERCOM '06 Proceedings of the Fourth Annual IEEE International Conference on Pervasive Computing and Communications
Scalable data delivery for networked servers and wireless sensor networks
Scalable data delivery for networked servers and wireless sensor networks
The Tenet architecture for tiered sensor networks
Proceedings of the 4th international conference on Embedded networked sensor systems
Modeling spatially correlated data in sensor networks
ACM Transactions on Sensor Networks (TOSN)
The regiment macroprogramming system
Proceedings of the 6th international conference on Information processing in sensor networks
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
The design and implementation of a declarative sensor network system
Proceedings of the 5th international conference on Embedded networked sensor systems
Data Quality and Query Cost in Pervasive Sensing Systems
PERCOM '08 Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications
IrisNet: An Architecture for a Worldwide Sensor Web
IEEE Pervasive Computing
Macro-programming wireless sensor networks using Kairos
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Modeling and assessing quality of information in multisensor multimedia monitoring systems
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Using fuzzy AHP for evaluating the dimensions of data quality
International Journal of Business Information Systems
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This research is motivated by large-scale pervasive sensing applications. We examine the benefits and costs of caching data for such applications. We propose and evaluate several approaches to querying for, and then caching data in a sensor field data server. We show that for some application requirements (i.e., when delay drives data quality), policies that emulate cache hits by computing and returning approximate values for sensor data yield a simultaneous quality improvement and cost saving. This win-win is because when system delay is sufficiently important, the benefit to both query cost and data quality achieved by using approximate values outweighs the negative impact on quality due to the approximation. In contrast, when data accuracy drives quality, a linear trade-off between query cost and data quality emerges. We also identify caching and lookup policies for which the sensor field query rate is bounded when servicing an arbitrary workload of user queries. This upper bound is achieved by having multiple user queries share the cost of a single sensor field query. Finally, we demonstrate that our results are robust to the manner in which the environment being monitored changes using models for two different sensing systems.