Laurence T. Yang

Embedded and Ubiquitous Computing – EUC 2005 Workshops

We evaluated several multivariate stream data reduction techniques that can be used in sensor network applications. The evaluated techniques include Wavelet-based methods, sampling, hierarchical clustering, and singular value decomposition (SVD). We tested the reduction methods over the range of different parameters including data reduction rate, data types, number of dimensions and data window size of the input stream. Both real and synthetic time series data were used for the evaluation. The results of experiments suggested that the reduction techniques should be evaluated in the context of applications, as different applications generate different types of data and that has a substantial impact on the performance of different reduction methods. The findings reported in this paper can serve as a useful guideline for sensor network design and construction.

A walkthrough from smart spaces to smart hyperspaces towards a smart world with ubiquitous intelligence

In the ubicomp/percomp era, more ubiquitous computation/information/service would be the main driving force, and the corresponding essential element would be the various smart/intelligent ubiquitous things or u-things with attached/embedded/blended computers. Based on the soon available ubiquitous networking infrastructures and services, such ordinary u-things surrounding us are capable of computing, communicating, connecting or being connected, and behaving smartly with some intelligence. Our world would evolve towards a smart world mainly characterized by ubiquitous intelligence and filled with these smart u-things falling into three categories; smart object, smart space and smart system. The next research phase to emerge, we believe, is to coordinate these diverse smart objects and integrate these isolated smart spaces together into a higher level of spaces known as smart hyperspace or hyper-environments, and eventually create the smart world. In this paper, we discuss the potential trends and related challenges from smart things, smart spaces to smart hyperspaces toward the smart world with ubiquitous intelligence.