Performance Modeling of Stream Joins
Vincenzo Massimiliano Gulisano, Alessandro V. Papadopoulos, Yiannis Nikolakopoulos, Marina Papatriantafilou, Philippas Tsigas
Abstract
Vincenzo Massimiliano Gulisano, Alessandro V. Papadopoulos, Yiannis Nikolakopoulos, Marina Papatriantafilou, Philippas Tsigas
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.
OpenAlex reports 20 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
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