Quality-aware management of data streams is gaining more and more importance with the amount of data produced by streams growing continuously. The resources required for data stream processing depend on different factors and are limited by the environment of the data stream management system (DSMS). Thus, with a potentially unbounded amount of stream data and limited processing resources, some of the data stream processing tasks (originating from different users) may not be satisfyingly answered, and therefore, users should be enabled to negotiate a certain quality for the execution of their stream processing tasks. After the negotiation process, it is the responsibility of the Data Stream Management System to meet the quality constraints b...
Distributed Stream Processing Systems (DSPS) are ``Fast Data'' platforms that allow streaming applic...
[[abstract]]In real-time environments, information is disseminated to clients under timing constrain...
In the era of big data, with streaming applications such as social media, surveillance monitoring an...
Quality-aware management of data streams is gaining more and more importance with the amount of data...
Data stream processing in the industrial as well as in the academic field has gained more and more i...
In this paper, we identify issues and present solutions developed – both theoretical and experimenta...
Continuous queries in a Data Stream Management System (DSMS) rely on time as a basis for win-dows on...
Recently, several policies have been proposed for scheduling multiple Continuous Queries (CQs) in a ...
The emergence of Data Stream Management Systems (DSMS) facilitates implementing many types of monito...
In many application fields, such as production lines or stock analysis, it is substantial to create ...
Data Stream Management Systems (DSMS) typically host multiple Continuous Queries (CQ) that process s...
In many applications involving continuous data streams, data arrival is bursty and data rate fluctua...
Traditional databases store sets of relatively static records with no pre-defined notion of time, un...
Quality of Service (QoS) and Quality of Data (QoD) are the two major dimensions for evaluating any q...
Processing data streams with Quality-of-Service (QoS) guarantees is an emerging area in existing str...
Distributed Stream Processing Systems (DSPS) are ``Fast Data'' platforms that allow streaming applic...
[[abstract]]In real-time environments, information is disseminated to clients under timing constrain...
In the era of big data, with streaming applications such as social media, surveillance monitoring an...
Quality-aware management of data streams is gaining more and more importance with the amount of data...
Data stream processing in the industrial as well as in the academic field has gained more and more i...
In this paper, we identify issues and present solutions developed – both theoretical and experimenta...
Continuous queries in a Data Stream Management System (DSMS) rely on time as a basis for win-dows on...
Recently, several policies have been proposed for scheduling multiple Continuous Queries (CQs) in a ...
The emergence of Data Stream Management Systems (DSMS) facilitates implementing many types of monito...
In many application fields, such as production lines or stock analysis, it is substantial to create ...
Data Stream Management Systems (DSMS) typically host multiple Continuous Queries (CQ) that process s...
In many applications involving continuous data streams, data arrival is bursty and data rate fluctua...
Traditional databases store sets of relatively static records with no pre-defined notion of time, un...
Quality of Service (QoS) and Quality of Data (QoD) are the two major dimensions for evaluating any q...
Processing data streams with Quality-of-Service (QoS) guarantees is an emerging area in existing str...
Distributed Stream Processing Systems (DSPS) are ``Fast Data'' platforms that allow streaming applic...
[[abstract]]In real-time environments, information is disseminated to clients under timing constrain...
In the era of big data, with streaming applications such as social media, surveillance monitoring an...