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Evaluating Streaming Strategies for Event Processing Across Infrastructure Clouds

Radu Tudoran, Kate Keahey, Pierre Riteau, Sergey Panitkin, Gabriel Antoniu
2014 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing  
In this paper, we propose two strategies for efficiently implementing such streaming in the cloud and evaluate them in the context of an ATLAS application processing experimental data.  ...  data is processed as a series of time events.  ...  THE COST OF STREAMING Another interesting aspect to evaluate is the cost of streaming to the cloud for the two streaming strategies.  ... 
doi:10.1109/ccgrid.2014.89 dblp:conf/ccgrid/TudoranKRPA14 fatcat:33ich2cub5adlo3yoa44jnkbqq


Radu Tudoran, Olivier Nano, Ivo Santos, Alexandru Costan, Hakan Soncu, Luc Bougé, Gabriel Antoniu
2014 Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems - DEBS '14  
In their quest for finding the Value in the 3 Vs of Big Data, applications process larger data sets, within and across clouds.  ...  stream processing.  ...  ACKNOWLEDGMENT The authors would like to thank Costin Grigoras (CERN) for his valuable support and insights on the MonALISA monitoring traces of the ALICE experiment.  ... 
doi:10.1145/2611286.2611298 dblp:conf/debs/TudoranNSCSBA14 fatcat:gvprtr4ot5avba3u6skwhk64ky

JetStream: Enabling high throughput live event streaming on multi-site clouds

Radu Tudoran, Alexandru Costan, Olivier Nano, Ivo Santos, Hakan Soncu, Gabriel Antoniu
2016 Future generations computer systems  
data mining queries based on inter-site event stream processing.  ...  This is namely the challenge we address in this paper, by proposing JetStream, a high performance batch-based streaming middleware for efficient transfers of events between cloud datacenters.  ...  Acknowledgments The authors would like to thank Andreea Pintilie for her valuable input related to the ant-based algorithm for the intermediate node selection.  ... 
doi:10.1016/j.future.2015.01.016 fatcat:sjw2hxrbvvfqvpknnj6r6dtbea

SMART: An Application Framework for Real Time Big Data Analysis on Heterogeneous Cloud Environments

Julio C.S. dos Anjos, Marcos D. Assuncao, Jean Bez, Claudio Geyer, Edison Pignaton de Freitas, Alexandre Carissimi, Joao Paulo C. L. Costa, Gilles Fedak, Felix Freitag, Volker Markl, Paul Fergus, Rubem Pereira
2015 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing  
Big data processing techniques are evolving to address this challenge, with analysis increasingly being performed using cloud-based systems.  ...  service solutions for SMEs.  ...  In streaming systems, the performance is workload sensitive which indicates a need for more detailed evaluation.  ... 
doi:10.1109/cit/iucc/dasc/picom.2015.29 dblp:conf/IEEEcit/AnjosABGFCCFFMF15 fatcat:pp3t6xrdzzb6df5fwalnyglwoe

Distributed Operator Placement for IoT Data Analytics Across Edge and Cloud Resources

Eduard Gibert Renart, Alexandre Da Silva Veith, Daniel Balouek-Thomert, Marcos Dias De Assuncao, Laurent Lefevre, Manish Parashar
2019 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)  
The heterogeneity among the edge devices and cloud servers introduces an important challenge for deciding how to split and orchestrate the IoT applications across the edge and the cloud.  ...  Cloud-based architectures often centralize storage and processing, generating high data movement overheads that penalize real-time applications.  ...  Other frameworks involve Apache Storm [26] , which supports event-based stream processing, and Apache Flink [27] , which enables batch and stream processing with its unified APIs.  ... 
doi:10.1109/ccgrid.2019.00060 dblp:conf/ccgrid/RenartVBALP19 fatcat:gtrbl7ruizc63ig6xn6xgth2am

Latency-Aware Placement of Data Stream Analytics on Edge Computing [chapter]

Alexandre da Silva Veith, Marcos Dias de Assunção, Laurent Lefèvre
2018 Lecture Notes in Computer Science  
The interest in processing data events under stringent time constraints as they arrive has led to the emergence of architecture and engines for data stream processing.  ...  In this work, we introduce strategies to create placement configurations for data stream processing applications whose operator topologies follow series parallel graphs.  ...  The contributions of this work are: (i) it presents a model for Distributed Stream Processing (DSP) applications in heterogeneous infrastructure ( §2); (ii) it introduces placement strategies for dynamically  ... 
doi:10.1007/978-3-030-03596-9_14 fatcat:cnxakippsnhxhiwguanykmohbq

Boosting Big Data Streaming Applications in Clouds with BurstFlow

Paulo R. R. De Souza, Kassiano J. Matteussi, Alexandre da S. Veith, Breno F. Zanchetta, Valderi R. Q. Leithardt, M. Alvaro Lozano, Edison P. De Freitas, Julio C. S. Dos Anjos, Claudio F. R. Geyer
2020 IEEE Access  
TABLE 1 . 1 Techniques for Adaptative Stream Processing Infrastructures Strategies Proc Author Geo-Distributed Cloud Infrastructure Cluster Multi-Cloud Hybrid Infrastructure Window Size Time  ...  BURSTFLOW: A MECHANISM TO BOOST THE THROUGHPUT OF SP APPLICATIONS IN MULTI CLOUD This section details BurstFlow and its strategies proposed for placing creating micro-batches onto MC infrastructure while  ... 
doi:10.1109/access.2020.3042739 fatcat:zjyqz7yop5eyfncg4paa5fmbf4

Streaming vs. Functions: A Cost Perspective on Cloud Event Processing [article]

Tobias Pfandzelter and Sören Henning and Trever Schirmer and Wilhelm Hasselbring and David Bermbach
2022 arXiv   pre-print
In cloud event processing, data generated at the edge is processed in real-time by cloud resources.  ...  Both distributed stream processing (DSP) and Function-as-a-Service (FaaS) have been proposed to implement such event processing applications.  ...  This material is based upon works supported by the Google Cloud Research Credits program with the awards GCP209186206 and GCP203304083.  ... 
arXiv:2204.11509v2 fatcat:paipsfgxf5dchpxeflmmafv5ai

Performance Characterization and Modeling of Serverless and HPC Streaming Applications [article]

Andre Luckow, Shantenu Jha
2019 arXiv   pre-print
Experiment-in-the-Loop Computing (EILC) requires support for numerous types of processing and the management of heterogeneous infrastructure over a dynamic range of scales: from the edge to the cloud and  ...  Pilot-Streaming provides a unified abstraction for resource management for HPC, cloud, and serverless, and allocates resource containers independent of the application workload removing the need to write  ...  EILC and stream processing can be used for detecting events of interests, pre-processing data, and steering of simulations and instruments.  ... 
arXiv:1909.06055v1 fatcat:srn4aojierffzlzlp2hmwm6io4

Leveraging Fog Computing for Scalable IoT Datacenter Using Spine-Leaf Network Topology

K. C. Okafor, Ifeyinwa E. Achumba, Gloria A. Chukwudebe, Gordon C. Ononiwu
2017 Journal of Electrical and Computer Engineering  
Besides, the scalability requirements found in the current IoT data processing (in the cloud) can hardly be used for applications such as assisted living systems, Big Data analytic solutions, and smart  ...  This paper proposes an extended cloud IoT model that optimizes bandwidth while allowing edge devices (Internet-connected objects/devices) to smartly process data without relying on a cloud network.  ...  Acknowledgments This research was carried out as an extended work on Distributed Cloud Computing Network for SGEMS/EETACP project commissioned by the Department of Electronic Engineering, University of  ... 
doi:10.1155/2017/2363240 fatcat:7x7xvrmuf5dm7ixlu4m33ryxta

Managing parallelism for stream processing in the cloud

Nathan Backman, Rodrigo Fonseca, Uǧur Çetintemel
2012 Proceedings of the 1st International Workshop on Hot Topics in Cloud Data Processing - HotCDP '12  
Stream processing applications run continuously and have varying load. Cloud infrastructures present an attractive option to meet these fluctuating computational demands.  ...  It supports data-and task-parallel processing of all workflow operators, by all computing nodes, while maintaining the ordering properties of sorted data streams.  ...  In our tests, we evaluate and disseminate partition strategies for windowbased operators after a variable number of windows have been evaluated (e.g., every 10 windows) while we use timebased evaluation  ... 
doi:10.1145/2169090.2169091 fatcat:tbpoehinxffjjbcjz7ccrksvqm

Vertical Workflows: Service Orchestration across Cloud & Edge Resources

Omer Rana, Manjerhussain Shaikh, Muhammad Ali, Ashiq Anjum, Luiz Bittencourt
2018 2018 IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud)  
efficient allocation of processing across such edge devices and data centers.  ...  Many Internet of Things (IoT) applications today involve data capture from sensors that are close to the phenomenon being measured, with such data subsequently being transmitted to Cloud data centers for  ...  LFB would like to thank CNPq and CAPES for the financial support.  ... 
doi:10.1109/ficloud.2018.00058 dblp:conf/ficloud/RanaSAAB18 fatcat:gsqm3peunvhktl3dkus65dxvbe

Strategies for Big Data Analytics through Lambda Architectures in Volatile Environments [article]

Alexandre Da Silva Veith, Edison Pignaton de Freitas AVALON
2017 arXiv   pre-print
The proposed strategies make use of services such as migration, replication, MapReduce simulation, and combined processing methods (batch- and streaming-based).  ...  %An application of batch and stream-based methods are proposed to reduce the latency.  ...  RELATED WORK Heterogeneous Infrastructures JetStream is a set of strategies for efficient transfers of events between cloud data centers (Tudoran et al., 2014) .  ... 
arXiv:1708.04796v1 fatcat:ieeqnouvifg5fgecl2ac7yuooa

Strategies for Big Data Analytics through Lambda Architectures in Volatile Environments

Veith Alexandre da Silva, Anjos Julio C.S. dos, de Freitas Edison Pignaton, Lampoltshammer Thomas J., Geyer Claudio F.
2016 IFAC-PapersOnLine  
The proposed strategies make use of services such as migration, replication, MapReduce simulation, and combined processing methods (batch-and streaming-based).  ...  Via these services, a distribution of tasks for the best balance of computational resources is achieved, while monitoring and management can be performed asynchronously in the background.  ...  RELATED WORK Heterogeneous Infrastructures JetStream is a set of strategies for efficient transfers of events between cloud data centers (Tudoran et al., 2014) .  ... 
doi:10.1016/j.ifacol.2016.11.138 fatcat:zy45z7ztc5f6zbmx4pskr7w5a4

Scaling Archived Social Media Data Analysis Using a Hadoop Cloud

Javier Conejero, Peter Burnap, Omer Rana, Jeffrey Morgan
2013 2013 IEEE Sixth International Conference on Cloud Computing  
We demonstrate the approach using a data set consisting of several million Twitter messages, analysed over two types of Cloud infrastructure.  ...  Over recent years, there has been an emerging interest in supporting social media analysis for marketing, opinion analysis and understanding community cohesion.  ...  We would like to thank JISC for their support.  ... 
doi:10.1109/cloud.2013.120 dblp:conf/IEEEcloud/ConejeroBRM13 fatcat:awgnn6wg2jcjzd6ityoqv2qyzi
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