An efficient entropy estimation approach
Marko Paavola · 2011
Advances in miniaturisation have led to the development of new wireless measurement technologies such as wireless sensor networks (WSNs). A WSN consists of low cost nodes, which are battery-operated devices, capable of sensing the environment, transmitting and receiving, and computing. While a WSN has several advantages, including cost-effectiveness and easy installation, the nodes suffer from small memory, low computing power, small bandwidth and limited energy supply. In order to cope with restrictions on resources, data processing methods should be as efficient as possible. As a result, high quality approximates are preferred instead of accurate answers. The aim of this thesis was to propose an efficient entropy approximation method for resourceconstrained environments. Specifically, the algorithm should use a small, constant amount of memory, and have certain accuracy and low computational demand. The performance of the proposed algorithm was evaluated experimentally with three case studies. The first study focused on the online monitoring of WSN communications performance in an industrial environment. The monitoring approach was based on the observation that entropy could be applied to assess the impact of interferences on time-delay variation of periodic tasks. The main purpose of the additional two cases, depth of anaesthesia (DOA) –monitoring and benchmarking with simulated data sets was to provide additional evidence on the general applicability of the proposed method. Moreover, in case of DOA-monitoring, an efficient entropy approximation could assist in the development of handheld devices or processing large amount of online data from different channels simultaneously. The initial results from the communication and DOA monitoring applications as well as from simulations were encouraging. Therefore, based on the case studies, the proposed method was able to meet the stated requirements. Since entropy is a widely used quantity, the method is also expected to have a variety of applications in measurement systems with similar requirements.