1 research outputs found
A Comprehensive Survey on Parallelization and Elasticity in Stream Processing
Stream Processing (SP) has evolved as the leading paradigm to process and
gain value from the high volume of streaming data produced e.g. in the domain
of the Internet of Things. An SP system is a middleware that deploys a network
of operators between data sources, such as sensors, and the consuming
applications. SP systems typically face intense and highly dynamic data
streams. Parallelization and elasticity enables SP systems to process these
streams with continuously high quality of service. The current research
landscape provides a broad spectrum of methods for parallelization and
elasticity in SP. Each method makes specific assumptions and focuses on
particular aspects of the problem. However, the literature lacks a
comprehensive overview and categorization of the state of the art in SP
parallelization and elasticity, which is necessary to consolidate the state of
the research and to plan future research directions on this basis. Therefore,
in this survey, we study the literature and develop a classification of current
methods for both parallelization and elasticity in SP systems.Comment: 37 Pages, to be published in ACM Computing Survey