A Performance Study of Event Processing Systems

Mendes, Marcelo R.N.; Bizarro, Pedro; Marques, Paulo

doi:10.1007/978-3-642-10424-4_16

Cited by 48 publications

(16 citation statements)

References 16 publications

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“…For performance evaluation, standard benchmarks would be a great service to the streaming optimization community. Existing benchmarking work includes the Stanford stream query repository [Arasu et al 2006], the BiCEP benchmarks [Mendes et al 2009], and the StreamIt benchmarks [Thies and Amarasinghe 2010], but more work is needed. Another direction for future research is multimetric optimizers.…”

Section: Metrics For Streaming Optimization Profitabilitymentioning

confidence: 99%

A catalog of stream processing optimizations

et al. 2014

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Various research communities have independently arrived at stream processing as a programming model for high-performance and parallel computation, including digital signal processing, databases, operating systems, and complex event processing. Each of these communities has developed some of the same optimizations, but often with conflicting terminology and unstated assumptions. This paper presents a survey of optimizations for stream processing. It is aimed both at users who need to understand and guide the system's optimizer, and at implementers who need to make engineering trade-offs. To consolidate terminology, this paper is organized as a catalog, in a style similar to catalogs of design patterns or refactorings. To make assumptions explicit and help with trade-offs, each optimization is presented with its safety constraints (when does it preserve correctness?) and a profitability experiment (when does it improve performance?). We hope that this survey will help future optimization inventors to stand on the shoulders of giants from not just their own community.

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Section: Metrics For Streaming Optimization Profitabilitymentioning

confidence: 99%

A catalog of stream processing optimizations

et al. 2014

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“…Again, MavEStream system enforces QoS by complex scheduling heuristics that may not always perform suitably under bursty conditions. Additionally, this lack of QoS support in CEP has also been recently considered in the literature: in [16] several microbenchmarks were proposed to compare different CEP engines and assess their scalability with respect to a number of queries. Various ways of evaluating their ability to changes in load conditions were also discussed.…”

Section: Related Work Research In Data Stream Management Systems (mentioning

confidence: 99%

A Distributed In-Transit Processing Infrastructure for Forecasting Electric Vehicle Charging Demand

Tolosana-Calasanz

Bañares

Cipcigan

et al. 2013

2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing

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Abstract-With an increasing interest in Electric Vehicles (EVs), it is essential to understand how EV charging could impact demand on the Electricity Grid. Existing approaches used to achieve this make use of a centralised data collection mechanism -which often is agnostic of demand variation in a given geographical area. We present an in-transit data processing architecture that is more efficient and can aggregate a variety of different types of data. A model using Reference nets has been developed and evaluated. Our focus in this paper is primarily to introduce requirements for such an architecture.

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“…[12]. One promising approach would seem to be use of reconfigurable hardware, such as Field-Programmable Gate Arrays (FPGAs), in order to accelerate event processing.…”

Section: Introductionmentioning

confidence: 99%

20Gbps C-Based Complex Event Processing

Inoue

Takenaka

Motomura

2011

2011 21st International Conference on Field Programmable Logic and Applications

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This paper presents the world's fastest complex event processing system, designed to process a large number of events on FPGAs. Unlike conventional SQL-based approaches, our approach features logic automation constructed with a new C-based event language that supports regular expressions on the basis of C functions, so that a wide variety of eventprocessing applications can be efficiently mapped to FPGAs. Evaluations on an FPGA-based NIC show that we have achieved 20Gbps event processing performance in a financial trading application with only a small logic increase, 2.7%.

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A Performance Study of Event Processing Systems

Cited by 48 publications

References 16 publications

A catalog of stream processing optimizations

A catalog of stream processing optimizations

A Distributed In-Transit Processing Infrastructure for Forecasting Electric Vehicle Charging Demand

20Gbps C-Based Complex Event Processing

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