Event-based applications and enabling technologies
Proceedings of the Third ACM International Conference on Distributed Event-Based Systems
Event processing: past, present and future
Proceedings of the VLDB Endowment
Secure shared continuous query processing
Proceedings of the 2011 ACM Symposium on Applied Computing
Seamless event and data stream processing: reconciling windows and consumption modes
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications - Volume Part I
Multilevel secure data stream processing
DBSec'11 Proceedings of the 25th annual IFIP WG 11.3 conference on Data and applications security and privacy
Load shedding in data stream management systems using application semantics
BNCOD'10 Proceedings of the 27th British national conference on Data Security and Security Data
Knowledge-based processing of complex stock market events
Proceedings of the 15th International Conference on Extending Database Technology
Fusion of background knowledge and streams of events
Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
From calls to events: architecting future BPM systems
BPM'12 Proceedings of the 10th international conference on Business Process Management
Streaming data management for the online processing of simulation data
Proceedings of the Winter Simulation Conference
Revenue-Based resource management on shared clouds for heterogenous bursty data streams
GECON'12 Proceedings of the 9th international conference on Economics of Grids, Clouds, Systems, and Services
Information flow control for stream processing in clouds
Proceedings of the 18th ACM symposium on Access control models and technologies
Multilevel secure data stream processing: Architecture and implementation
Journal of Computer Security - DBSec 2011
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Traditional database management systems, widely used today, are not well-suited for a class of emerging applications, such as computer network management, homeland security, sensor computing, and environmental monitoring. These applicationsneed to continuously process large amounts of data coming in the form of a stream, and meet stringent response time requirements. Support for handling QoS metrics, such as response time, memory usage, and throughput, is central to any system proposed for the above applications. Stream Data Processing: A Quality of Service Perspective (Modeling, Scheduling, Load Shedding, and Complex Event Processing), presents a new paradigm suitable for stream and complex event processing. This book covers a broad range of topics in stream data processing and includes detailed technical discussions of a number of proposed techniques. This volume is intended as a textbook for graduate courses and as a reference book for researchers, advanced-level students in CS, and IT practitioners.