Integration of Reliable Sensor Data Stream Management into Digital Libraries

Abstract

Data Stream Management (DSM) addresses the continuous processing of sensor data. DSM requires the combination of stream operators, which may run on different distributed devices, into stream processes. Due to the recent advantages in sensor technologies and wireless communication, the amount of information generated by DSM will increase significantly. In order to efficiently deal with this streaming information, Digital Library (DL) systems have to merge with DSM systems. Especially in healthcare, the continuous monitoring of patients at home (telemonitoring) will generate a significant amount of information stored in an e-health digital library (electronic patient record). In order to stream-enable DL systems, we present an integrated data stream management and Digital Library infrastructure in this work. A vital requirement for healthcare applications is however that this infrastructure provides a high degree of reliability. In this paper, we present novel approaches to reliable DSM within a DL infrastructure. In particular, we propose information filtering operators, a declarative query engine called MXQuery, and efficient operator checkpointing to maintain high result quality of DSM. Furthermore, we present a demonstrator implementation of the integrated DSM and DL infrastructure, called OSIRIS-SE. OSIRIS-SE supports flexible and efficient failure handling to ensures complete and consistent continuous data stream processing and execution of DL processes even in the case of multiple failures.