[HAL] BigDataFr recommends: Distributed Data Stream Processing and Edge Computing: A Survey on Resource Elasticity and Future Directions


BigDataFr recommends: Smarter Round Robin Scheduling Algorithm for Cloud Computing and Big Data


[…] Under several emerging application scenarios, such as in smart cities, operational monitoring of large infrastructure, wearable assistance, and Internet of Things, continuous data streams must be processed under very short delays. Several solutions, including multiple software engines, have been developed for processing unbounded data streams in a scalable and efficient manner. More recently, architecture has been proposed to use edge computing for data stream processing. This paper surveys state of the art on stream processing engines and mechanisms for exploiting resource elasticity features of cloud computing in stream processing. Resource elasticity allows for an application or service to scale out/in according to fluctuating demands. […]

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By Marcos Dias de Assuncao 1,2, Alexandre Da Silva Veith 1,2, Rajkumar Buyya 3,4
Source: hal-archives-ouvertes.fr

1 – AVALON – Algorithms and Software Architectures for Distributed and HPC Platforms
Inria Grenoble – Rhône-Alpes, LIP – Laboratoire de l’Informatique du Parallélisme
2 – ENS Lyon – École normale supérieure – Lyon
3 – University of Melbourne
4 – CIS – School of Computing and Information Systems

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