Data Alignment for Data Fusion in Wireless Multimedia Sensor Networks Based on M2M
José Roberto Pérez Cruz · KSII Transactions on Internet and Information Systems · 2012
Advances in MEMS and CMOS technologies have motivated the development of low cost/power sensors and wireless multimedia sensor networks (WMSN).The WMSNs were created to ubiquitously harvest multimedia content.Such networks have allowed researchers and engineers to glimpse at new Machine-to-Machine (M2M) Systems, such as remote monitoring of biosignals for telemedicine networks.These systems require the acquisition of a large number of data streams that are simultaneously generated by multiple distributed devices.This paradigm of data generation and transmission is known as event-streaming.In order to be useful to the application, the collected data requires a preprocessing called data fusion, which entails the temporal alignment task of multimedia data.A practical way to perform this task is in a centralized manner, assuming that the network nodes only function as collector entities.However, by following this scheme, a considerable amount of redundant information is transmitted to the central entity.To decrease such redundancy, data fusion must be performed in a collaborative way.In this paper, we propose a collaborative data alignment approach for event-streaming.Our approach identifies temporal relationships by translating temporal dependencies based on a timeline to causal dependencies of the media involved.