Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Directed diffusion for wireless sensor networking
IEEE/ACM Transactions on Networking (TON)
Supporting Aggregate Queries Over Ad-Hoc Wireless Sensor Networks
WMCSA '02 Proceedings of the Fourth IEEE Workshop on Mobile Computing Systems and Applications
Balancing energy efficiency and quality of aggregate data in sensor networks
The VLDB Journal — The International Journal on Very Large Data Bases
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
DAG Based In-Network Aggregation for Sensor Network Monitoring
SAINT '06 Proceedings of the International Symposium on Applications on Internet
The emergence of networking abstractions and techniques in TinyOS
NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
In-network aggregation trade-offs for data collection in wireless sensor networks
International Journal of Sensor Networks
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In wireless sensor networks, the timeout scheduling of data aggregation controls the time each sensor node has to wait to receive data from its child nodes. This paper proposes a new timeout scheduling scheme for data aggregation, the ATS-DA, which adaptively configures its length of timeout according to changing data patterns. The ATS-DA decreases the timeout when the variance of the received data (data variation) from children is lower than a pre-defined threshold because there are not any noticeable events, which reduces the consumed power and improves transmission latency. The ATS-DA, however, increases the timeout when data variation is more than the pre-defined threshold in order to fulfill more accurate data aggregation. Extensive simulation work under various workloads has revealed that ATS-DA not only enhances data accuracy by 33%, but also it improves power consumption and transmission latency by 5% and 58% respectively, as compared with the previous cascading timeout scheduling scheme.