In this paper, we identify issues and present solutions developed – both theoretical and experimental – during the course of developing a data stream management system (DSMS) for applications in a sensor environment. Specifically, we summarize our solutions for CQ processing, trigger mechanisms, and Quality of Service (QoS) management in a stream data processing system. Specifically, we first present our query processing model and then discuss our scheduling strategies to support different requirements of stream applications. We further discuss our QoS framework in such a DSMS and present our load shedding techniques, queueing model, and analysis techniques in order to effectively deliver QoS requirements for those applications. Finally, we...
The ubiquitous use of mobile devices, sensors, and the linkage between them open up opportunities fo...
Recently, several policies have been proposed for scheduling multiple Continuous Queries (CQs) in a ...
This paper describes our ongoing work developing the Stanford Stream Data Manager (STREAM), a system...
Data stream processing in the industrial as well as in the academic field has gained more and more i...
Data streams processing is an emerging research area that is driven by the growing need for monitori...
The massive usage of Data Streams dates back to the artificial satellites information processing sys...
In many application fields, such as production lines or stock analysis, it is substantial to create ...
Quality-aware management of data streams is gaining more and more importance with the amount of data...
In recent years, data streams have become ubiquitous as technology is improving and the prices of se...
Data Stream Management (DSM) addresses the continuous processing of sensor data. DSM requires the co...
Processing data streams with Quality-of-Service (QoS) guarantees is an emerging area in existing str...
The emergence of Data Stream Management Systems (DSMS) facilitates implementing many types of monito...
Data stream systems have to deal with massive data volumes. To perform several queries in parallel o...
This demonstration shows an integrated query processing environment where users can seamlessly query...
This paper provides an overview of these problems, examines why traditional relational systems are i...
The ubiquitous use of mobile devices, sensors, and the linkage between them open up opportunities fo...
Recently, several policies have been proposed for scheduling multiple Continuous Queries (CQs) in a ...
This paper describes our ongoing work developing the Stanford Stream Data Manager (STREAM), a system...
Data stream processing in the industrial as well as in the academic field has gained more and more i...
Data streams processing is an emerging research area that is driven by the growing need for monitori...
The massive usage of Data Streams dates back to the artificial satellites information processing sys...
In many application fields, such as production lines or stock analysis, it is substantial to create ...
Quality-aware management of data streams is gaining more and more importance with the amount of data...
In recent years, data streams have become ubiquitous as technology is improving and the prices of se...
Data Stream Management (DSM) addresses the continuous processing of sensor data. DSM requires the co...
Processing data streams with Quality-of-Service (QoS) guarantees is an emerging area in existing str...
The emergence of Data Stream Management Systems (DSMS) facilitates implementing many types of monito...
Data stream systems have to deal with massive data volumes. To perform several queries in parallel o...
This demonstration shows an integrated query processing environment where users can seamlessly query...
This paper provides an overview of these problems, examines why traditional relational systems are i...
The ubiquitous use of mobile devices, sensors, and the linkage between them open up opportunities fo...
Recently, several policies have been proposed for scheduling multiple Continuous Queries (CQs) in a ...
This paper describes our ongoing work developing the Stanford Stream Data Manager (STREAM), a system...