Abstract. Many emerging on-line data analysis applications require applying continuous query operations such as correlation, aggregation, and filtering to data streams in real-time. Distributed stream processing systems allow in-network stream processing to achieve better scalability and quality-of-service (QoS) provision. In this paper we present Synergy, a distributed stream processing middleware that provides sharing-aware component composition. Synergy enables efficient reuse of both data streams and processing components, while composing distributed stream processing applications with QoS demands. Synergy provides a set of fully distributed algorithms to discover and evaluate the reusability of available data streams and processing com...
Data streaming applications are becoming more and more common due to the rapid development in emergi...
It is challenging for large-scale stream management systems to return always perfect results when pr...
The wide diffusion of cheap, small, and portable sensors integrated in an unprecedented large variet...
Abstract—Stream processing has become increasingly important as many emerging applications call for ...
In today's world, stream processing systems have become important, as applications like media broadc...
Abstract. Data streaming applications are becoming more and more common due to the rapid development...
This paper addresses the shared resource contention problem associated with the auto-parallelization...
Many emerging distributed applications require the processing of massive amounts of data in real-tim...
Abstract. Data streaming applications are becoming more and more common due to the rapid development...
Resource management in Distributed Stream Processing Systems (DSPS) defines the way queries are depl...
Applications characterized by the continuous processing of large data streams have recently attracte...
Deploying an infrastructure to execute queries on distributed data streams sources requires to ident...
Abstract. In the recent years we have witnessed a proliferation of dis-tributed stream processing sy...
Distributed Stream Processing systems have become an essential part of big data processing platforms...
There is an increasing amount of information being made available as data streams, e.g. stock ticker...
Data streaming applications are becoming more and more common due to the rapid development in emergi...
It is challenging for large-scale stream management systems to return always perfect results when pr...
The wide diffusion of cheap, small, and portable sensors integrated in an unprecedented large variet...
Abstract—Stream processing has become increasingly important as many emerging applications call for ...
In today's world, stream processing systems have become important, as applications like media broadc...
Abstract. Data streaming applications are becoming more and more common due to the rapid development...
This paper addresses the shared resource contention problem associated with the auto-parallelization...
Many emerging distributed applications require the processing of massive amounts of data in real-tim...
Abstract. Data streaming applications are becoming more and more common due to the rapid development...
Resource management in Distributed Stream Processing Systems (DSPS) defines the way queries are depl...
Applications characterized by the continuous processing of large data streams have recently attracte...
Deploying an infrastructure to execute queries on distributed data streams sources requires to ident...
Abstract. In the recent years we have witnessed a proliferation of dis-tributed stream processing sy...
Distributed Stream Processing systems have become an essential part of big data processing platforms...
There is an increasing amount of information being made available as data streams, e.g. stock ticker...
Data streaming applications are becoming more and more common due to the rapid development in emergi...
It is challenging for large-scale stream management systems to return always perfect results when pr...
The wide diffusion of cheap, small, and portable sensors integrated in an unprecedented large variet...