Practical Summation via Sampling in Large-Scale Sensor Networks

S. Peng, S. Li, F. Liu, Y. Peng, and X. Liao (PRC)


Summation, Sampling, Sensor Network


In this article we design a novel measurement technique, FLAKE based on sparse sampling that are generic, in that it are applicable to arbitrary wireless sensor networks (WSN). It can be used to ef´Čüciently evaluate system size, scale of event, and other global aggregating or summation information of individual nodes over the whole network in low communication cost. This functionality is useful in many applications, but hard to achieve when each node has only a limited, local knowledge of the network. Therefore, we propose a measurement technique, FLAKE composed of two main components to solve this problem. One is the Injected Random Data Dissemination (Sampling) method, the other is sparse sampling algorithm based on Inverse Sampling, upon which it improves by achieving a target variance with small error and low communication cost. FLAKE uses approximately uniform random data dissem ination and sparse sampling in sensor networks, which is an unstructured and localized method.At last we provide experimental results demonstrating the effectiveness of our algorithm on both small-scale and large-scale WSN. Our measurement technique appears to be the practical and ap propriate choice.

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