Publication | Closed Access
Optimal operator placement for distributed stream processing applications
147
Citations
25
References
2016
Year
Unknown Venue
Cluster ComputingEngineeringRecent TrendsData Streaming ArchitectureStreaming DataOperations ResearchOptimal Operator PlacementData ScienceSystems EngineeringInternet Of ThingsParallel ComputingCombinatorial OptimizationData ManagementData Stream ProcessingStream ProcessingStreaming EngineComputer ScienceMobile ComputingData Stream ManagementFog NetworksEdge ComputingApplications PlacementCloud ComputingParallel ProgrammingBig Data
Data Stream Processing (DSP) applications are widely used to timely extract information from distributed data sources, such as sensing devices, monitoring stations, and social networks. To successfully handle this ever increasing amount of data, recent trends investigate the possibility of exploiting decentralized computational resources (e.g., Fog computing) to define the applications placement. Several placement policies have been proposed in the literature, but they are based on different assumptions and optimization goals and, as such, they are not completely comparable to each other.
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