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—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(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)
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)
1 Proof of Theorem 1 Theorem 1. To satisfy that any r(x) (x ∈ S(t)) can be extracted with error O(M j), where M j ⊆ S(t) ⊆ M j+1 and 1 ≤ j ≤ log n, the condition |I| − µ ≤ |A| ≤ |I| should be ensured, where µ = 1 − 1 β · h · |M j |. Proof. As presented in Section IV.A, the querying process for r(x) in T is a traversal process over T. Assuming for each(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)