Actors: a model of concurrent computation in distributed systems
Actors: a model of concurrent computation in distributed systems
A Partial Order Event Model for Concurrent Objects
CONCUR '99 Proceedings of the 10th International Conference on Concurrency Theory
Aurora: a data stream management system
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Foundations of Actor Semantics
Foundations of Actor Semantics
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
SPADE: the system s declarative stream processing engine
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
ORGs for Scalable, Robust, Privacy-Friendly Client Cloud Computing
IEEE Internet Computing
Validity of the single processor approach to achieving large scale computing capabilities
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Performance evaluation of message-oriented middleware using the SPECjms2007 benchmark
Performance Evaluation
Benchmarking of message-oriented middleware
Proceedings of the Third ACM International Conference on Distributed Event-Based Systems
A universal modular ACTOR formalism for artificial intelligence
IJCAI'73 Proceedings of the 3rd international joint conference on Artificial intelligence
Stochastic performance analysis and capacity planning of publish/subscribe systems
Proceedings of the Fourth ACM International Conference on Distributed Event-Based Systems
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
Performance modeling in mapreduce environments: challenges and opportunities
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
Incoop: MapReduce for incremental computations
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An industrial case study of performance and cost design space exploration
ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
Understanding performance modeling for modular mobile-cloud applications
ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
M3: Stream Processing on Main-Memory MapReduce
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
Stormy: an elastic and highly available streaming service in the cloud
Proceedings of the 2012 Joint EDBT/ICDT Workshops
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While data are growing at a speed never seen before, parallel computing is becoming more and more essential to process this massive volume of data in a timely manner. Therefore, recently, concurrent computations have been receiving increasing attention due to the widespread adoption of multi-core processors and the emerging advancements of cloud computing technology. The ubiquity of mobile devices, location services, and sensor pervasiveness are examples of new scenarios that have created the crucial need for building scalable computing platforms and parallel architectures to process vast amounts of generated streaming data. In practice, efficiently operating these systems is hard due to the intrinsic complexity of these architectures and the lack of a formal and in-depth knowledge of the performance models and the consequent system costs. The Actor Model theory has been presented as a mathematical model of con- current computation that had enormous success in practice and inspired a number of contemporary work in this area. Recently, the Storm system has been presented as a realization of the principles of the Actor Model theory in the context of the large scale processing of streaming data. In this paper, we present, to the best of our knowledge, the first set of models that formalize the performance characteristics of a practical distributed, parallel and fault-tolerant stream processing system that follows the Actor Model theory. In particular, we model the characteristics of the data flow, the data processing and the system management costs at a fine granularity within the different steps of executing a distributed stream processing job. Finally, we present an experimental validation of the described performance models using the Storm system.