Analysis of a local search heuristic for facility location problems
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Managing Intra-operator Parallelism in Parallel Database Systems
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Relational subscription middleware for Internet-scale publish-subscribe
Proceedings of the 2nd international workshop on Distributed event-based systems
Facility location with Service Installation Costs
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Dynamic Load Distribution in the Borealis Stream Processor
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Operator placement for in-network stream query processing
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Optimal Component Composition for Scalable Stream Processing
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
Improved approximation for universal facility location
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Distributed Stream Management using Utility-Driven Self-Adaptive Middleware
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
Facility location with hierarchical facility costs
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Network-Aware Operator Placement for Stream-Processing Systems
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Contract-based load management in federated distributed systems
NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
Network-aware query processing for stream-based applications
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Placement of replicated message mediation components
Proceedings of the 2007 ACM/IFIP/USENIX international conference on Middleware companion
Replica placement for high availability in distributed stream processing systems
Proceedings of the second international conference on Distributed event-based systems
Placement Strategies for Internet-Scale Data Stream Systems
IEEE Internet Computing
Biologically-inspired distributed middleware management for stream processing systems
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
SODA: an optimizing scheduler for large-scale stream-based distributed computer systems
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
A stratified approach for supporting high throughput event processing applications
Proceedings of the Third ACM International Conference on Distributed Event-Based Systems
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
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We propose an algorithm for placing tasks of data flows for streaming systems onto servers within a message-oriented middleware where certain tasks can be replicated. Our work is centered on the idea that certain transformations are stateless and can therefore be replicated. Replication in this case can cause workloads to be partitioned among multiple machines, thus enabling message processing to be parallelized and lead to improvements in performance. We propose a guided replication approach for this purpose that iteratively computes the optimal placement of replicas where each subsequent iteration of the algorithm takes as input optimal solutions computed in the previous run. As a result, the system performance is consistently improved, which eventually converges as shown in simulation results. We demonstrate, through simulation experiments with both simple and complex task flow graphs and network topologies that introducing our replication mechanism can lead to improvements in runtime performance. When system resources are scarce, the benefits of applying our replication mechanism are even greater.