Modularization techniques for active rules design
ACM Transactions on Database Systems (TODS)
Achieving scalability and expressiveness in an Internet-scale event notification service
Proceedings of the nineteenth annual ACM symposium on Principles of distributed computing
The Ode Active Database: Trigger Semantics and Implementation
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Managing Intra-operator Parallelism in Parallel Database Systems
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
ROCK & ROLL: A Deductive Object-Oriented Database with Active and Spatial Extensions
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
ACM Transactions on Computer Systems (TOCS)
The VLDB Journal — The International Journal on Very Large Data Bases
Dynamic Load Distribution in the Borealis Stream Processor
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
High-performance complex event processing over streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Providing resiliency to load variations in distributed stream processing
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
SnoopIB: interval-based event specification and detection for active databases
Data & Knowledge Engineering
MavEStream: Synergistic Integration of Stream and Event Processing
ICDT '07 Proceedings of the Second International Conference on Digital Telecommunications
Querying the internet with PIER
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
EventScript: an event-processing language based on regular expressions with actions
Proceedings of the 2008 ACM SIGPLAN-SIGBED conference on Languages, compilers, and tools for embedded systems
Events and streams: harnessing and unleashing their synergy!
Proceedings of the second international conference on Distributed event-based systems
Real-time, load-adaptive processing of continuous queries over data streams
Proceedings of the second international conference on Distributed event-based systems
Optimizing State-Intensive Non-Blocking Queries Using Run-time Adaptation
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
Event-processing network model and implementation
IBM Systems Journal
Efficient dynamic operator placement in a locally distributed continuous query system
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part I
Control considerations for scalable event processing
DSOM'05 Proceedings of the 16th IFIP/IEEE Ambient Networks international conference on Distributed Systems: operations and Management
Traffic models in broadband networks
IEEE Communications Magazine
Placement of replicated tasks for distributed stream processing systems
Proceedings of the Fourth ACM International Conference on Distributed Event-Based Systems
Industry experience with the IBM Active Middleware Technology (AMiT) Complex Event Processing engine
Proceedings of the Fourth ACM International Conference on Distributed Event-Based Systems
GPGPU for cheaper 3D MMO servers
TELE-INFO'10 Proceedings of the 9th WSEAS international conference on Telecommunications and informatics
Event processing: past, present and future
Proceedings of the VLDB Endowment
Pattern rewriting framework for event processing optimization
Proceedings of the 5th ACM international conference on Distributed event-based system
Non functional properties of event porcessing
Proceedings of the 5th ACM international conference on Distributed event-based system
A scalable complex event processing system and evaluations of its performance
Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
Pub/Sub on stream: a multi-core based message broker with QoS support
Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
Deriving a unified fault taxonomy for event-based systems
Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
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
Input data organization for batch processing in time window based computations
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Adaptive online scheduling in storm
Proceedings of the 7th ACM international conference on Distributed event-based systems
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The quantity of events that a single application needs to process is constantly increasing. RFID related events have doubled within the past year and reached 4 trillion events per day, financial applications in large banks are processing 400 million events per day, and Massively Multiplayer Online (MMO) games are monitoring millions of events per second during peak periods. It is evident that scalability in event throughput is a major requirement for such applications. While the first generation of event processing systems is centralized, we see various solutions that attempt to use both scale-up and scale-out techniques. Alas, partitioning of the processing manually is difficult due to the semantic dependencies among event processing agents. It is also difficult to manually tune up the partition dynamically. This paper proposes a horizontal partition that is automatically created by analyzing the semantic dependencies among agents using a stratification principle. Each stratum contains a collection of independent agents, and events are routed to subsequent strata. We also implement a profiling-based technique for assigning agents to nodes in each stratum with the goal of maximizing throughput. A complementary step is to distribute load among different execution nodes dynamically based on their performance characteristics and the event traffic model. Experimental results show significant improvement in the ability to process high throughput of events relative to both centralized solutions as well as vertical partitions. We find this to be a promising approach to achieve high scalability particularly when the traffic model and network topology change frequently.