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Most of the existing query processing algorithms for Wireless Sensor Networks (WSNs) only can deal with discrete values. However, since the monitored environment always changes continuously with time, discrete values cannot describe the environment accurately and hence may not satisfy a variety of query requirements, such as the queries of the maximal,(More)
To observe the complicate physical world by a WSN, the sensors in the WSN senses and samples the data from the physical world. Currently, most of the existing work use equi-frequency sampling methods (EFS) or EFS based sampling methods for data acquisition in sensor networks. However, the accuracies of EFS and EFS based sampling methods cannot be guaranteed(More)
A Wireless Sensor Network consists of a number of sensors. The energy of each sensor is limited which limits network lifetime. There are many existing energy efficiency algorithms to prolong network lifetime. Basically, there are two kinds of methods. One is energy-efficiency management, such as duty-cycling using virtual-backbones. The other one is energy(More)
The amount of sensory data manifests an explosive growth due to the increasing popularity of Wireless Sensor Networks. The scale of the sensory data in many applications has already exceeds several petabytes annually, which is beyond the computation and transmission capabilities of the conventional WSNs. On the other hand, the information carried by big(More)
To observe the complicated physical world, the sensors in a network sense and sample the data from the physical world. Currently, most existing works use the Equi-Frequency Sampling (EFS) methods or EFS based methods for data acquisition. However, the accuracy of EFS and EFS based methods cannot be guaranteed in practice since the physical world keeps(More)
Proof. As presented in Section IV.A, the querying process for r(x) in T is a traversal process over T . Assuming for each interval Int of T , there exists a parameter μ that satisfies |I| − μ ≤ |A| ≤ |I|. Thus, the total error introduced by the traversal process from the sink to the leaf node is O(hμ) where h is the height of T . Thus, the total error of(More)
Aggregation operations are important for users to get summarization information in WSN applications. As large numbers of applications only require approximate aggregation results rather than the exact ones, some approximate aggregation algorithms are proposed to save energy. However, the error bounds of these algorithms are fixed and it is impossible to(More)