StreamCloud: An Elastic Parallel-Distributed Stream Processing Engine
type: Distribution
access URL: https://theses.hal.science/tel-00768281
format: HTML
issued: 2026-05-29T17:12:17.528317
modified: 2026-05-29T17:12:17.423586

StreamCloud: An Elastic Parallel-Distributed Stream Processing Engine
type: Dataset
contact point: Organization
  fn: CCSD
keyword: elasticidad
keyword: infoeu-reposemanticsdoctoralthesis
keyword: fault-tolerance
keyword: data-streaming
keyword: sistemas-de-procesamiento-de-flujos-de-datos
keyword: tolerancia-a-fallos
keyword: elasticite
keyword: scalability
keyword: equilibrado-de-carga
keyword: load-balancing
keyword: escalabilidad
keyword: infoinfo-dccomputer-science-csdistributed-parallel-and-cluster-computing-csdc
keyword: stream-processing-engine
keyword: elasticity
keyword: theses
landing page: https://theses.hal.science/tel-00768281
description: In recent years, applications in domains such as telecommunications, network security or large scale sensor networks showed the limits of the traditional store-then-process paradigm. In this context, Stream Processing Engines emerged as a candidate solution for all these applications demanding for high processing capacity with low processing latency guarantees. With Stream Processing Engines, data streams are not persisted but rather processed on the fly, producing results continuously. Current Stream Processing Engines, either centralized or distributed, do not scale with the input load due to single-node bottlenecks. Moreover, they are based on static configurations that lead to either under or over-provisioning. This Ph.D. thesis discusses StreamCloud, an elastic paralleldistributed stream processing engine that enables for processing of large data stream volumes. Stream- Cloud minimizes the distribution and parallelization overhead introducing novel techniques that split queries into parallel subqueries and allocate them to independent sets of nodes. Moreover, Stream- Cloud elastic and dynamic load balancing protocols enable for effective adjustment of resources depending on the incoming load. Together with the parallelization and elasticity techniques, Stream- Cloud defines a novel fault tolerance protocol that introduces minimal overhead while providing fast recovery. StreamCloud has been fully implemented and evaluated using several real word applications such as fraud detection applications or network analysis applications. The evaluation, conducted using a cluster with more than 300 cores, demonstrates the large scalability, the elasticity and fault tolerance effectiveness of StreamCloud.
issued: 2026-05-29T17:12:17.470969
language: en
modified: 2026-05-29T17:12:17.470976

test_moissonnage_selune
type: Agent