2017•Unpublished venueRequires access

Performance Modeling of Stream Joins

Vincenzo Massimiliano Gulisano, Alessandro V. Papadopoulos, Yiannis Nikolakopoulos, Marina Papatriantafilou, Philippas Tsigas

Open publisher page 20 citations

Abstract

Streaming analysis is widely used in a variety of environments, from cloud computing infrastructures up to the network's edge. In these contexts, accurate modeling of streaming operators' performance enables fine-grained prediction of applications' behavior without the need of costly monitoring. This is of utmost importance for computationally-expensive operators like stream joins, that observe throughput and latency very sensitive to rate-varying data streams, especially when deterministic processing is required.

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What this paper is about

Streaming analysis is widely used in a variety of environments, from cloud computing infrastructures up to the network's edge. In these contexts, accurate modeling of streaming operators' performance enables fine-grained prediction of applications' behavior without the need of costly monitoring. This is of utmost importance for computationally-expensive operators like stream joins, that observe throughput and latency very sensitive to rate-varying data streams, especially when deterministic processing is required.

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OpenAlex reports 20 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Streaming analysis is widely used in a variety of environments, from cloud computing infrastructures up to the network's edge. In these contexts, accurate modeling of streaming operators' performance enables fine-grained prediction of applications' behavior without the need of costly monitoring. This is of utmost importance for computationally-expensive operators like stream joins, that observe throughput and latency very sensitive to rate-varying data streams, especially when deterministic processing is required.

Key concepts: Joins, Computer science, Stream processing, Cloud computing, Latency (audio), Distributed computing, Throughput, Enhanced Data Rates for GSM Evolution

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