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portfolio
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publications
BSPonP2P: Model for Collaborative Computing at BSP Applications in P2P Desktop Grid
Published in ERAD 2014, 2014
Recommended citation: da Silva Veith, Alexandre; Righi, Rodrigo. R.
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Collaborative Computing of BSP Applications in P2P Grids (Original title: BSPonP2P: Computação Colaborativa de Aplicações BSP em Grades P2)
Published in INPI 2015, 2015
Progamming Language:
C
Recommended citation: da Silva Veith, Alexandre; da Costa, Cristiano André; da Rosa Righi, Rodrigo
Collaborative computing of parallel applications in P2P environments
Published in NEA 2015, 2015
Abstract
This book addresses the issue of “How to explore collaborative computing in P2P Grids to run BSP applications efficiently?”. To answer this question came the BSPonP2P model, which creates an environment with approaches based on the structured and unstructured models from the P2P networks. The combination of these models aims to streamline the management of communication and data on the network. Another difference of the proposed model is the use of the parallel programming model Bulk Synchronous Parallel (BSP), which creates an environment for executing processes, validating dependencies and improving communication between them. We use metrics required for the processes as memory, computing, communication, and also information from the infrastructure to establish a unique performance metric called PM. This metric is evaluated periodically to define migrations according to the launched superstep barriers. The results show that BSPonP2P uses the computational idleness, and brings performance gains to the executions.
Recommended citation: da Silva Veith, Alexandre; Righi, Rodrigo. R
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BSPonP2P: Towards Running Bulk-Synchronous Parallel Applications on P2P Desktop Grids
Published in PDPTA 2015, 2015
Recommended citation: da Rosa Righi, Rodrigo; da Silva Veith, Alexandre; Rodrigues, Vinicius Facco; Rostirolla, Gustavo
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Rescheduling and checkpointing as strategies to run synchronous parallel programs on P2P desktop grids
Published in SAC 2015, 2015
Recommended citation: da Rosa Righi, Rodrigo; da Silva Veith, Alexandre; Rodrigues, Vinicius Facco; Rostirolla, Gustavo; da Costa, Cristiano André; Farias, Kleinner; Alberti, Antonio Marcos
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Strategies for Big Data Analytics through Lambda Architectures in Volatile Environments
Published in IFAC 2016, 2016
Recommended citation: da Silva Veith, Alexandre; dos Anjos, J. C.; de Freitas Pignaton, Edison; Lampoltshammer, Thomas J.; Geyer, Claudio
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Assessing the Impact of Network Bandwidth and Operator Placement on Data Stream Processing for Edge Computing Environments
Published in COMPAS 2017, 2017
Recommended citation: da Silva Veith, Alexandre; Dias de Assunção, Marcos; Lefèvre, Laurent
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Distributed data stream processing and edge computing: A survey on resource elasticity and future directions
Published in JNCA 2017, 2017
Recommended citation: de Assunção, Marcos Dias; da Silva Veith, Alexandre; Buyya, Rajkumar
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Apache Spark
Published in EBDT 2018, 2018
Recommended citation: da Silva Veith, Alexandre; Dias de Assunção, Marcos
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Latency-Aware Strategies for Placing Data Stream Analytics onto Edge Computing
Published in HotEdge 2018, 2018
Recommended citation: da Silva Veith, Alexandre; Dias de Assuncao, Marcos; Lefevre, Laurent
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Aten: A Dispatcher for Big Data Applications in Heterogeneous Systems
Published in HPCS 2018, 2018
Recommended citation: R. R. De Souza Jr, Paulo; Matteussi, Kassiano; C. S. Anjos, Julio; D. D. dos Santos, Jobe and R. Geyer, Claudio; da Silva Veith, Alexandre
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Enabling Strategies for Big Data Analytics in Hybrid Infrastructures
Published in HPCS 2018, 2018
Recommended citation: C. S. Anjos, Julio; Matteussi, Kassiano; R. R. De Souza Jr, Paulo; da Silva Veith, Alexandre; Fedak, Gilles; Luis Victoria Barbosa, Jorge and R. Geyer, Claudio
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Latency-Aware Placement of Data Stream Analytics on Edge Computing
Published in ICSOC 2018, 2018
Recommended citation: da Silva Veith, Alexandre; de Assunção, Marcos Dias; Lefèvre, Laurent
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Distributed Operator Placement for IoT Data Analytics Across Edge and Cloud Resources
Published in CCGrid 2019, 2019
Recommended citation: Gibert Renart, Eduard*; da Silva Veith, Alexandre*; Balouek-Thomert, Daniel; de Assunção, Marcos Dias; Lefèvre, Laurent; Parashar, Manish
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Multi-Objective Reinforcement Learning for Reconfiguring Data Stream Analytics on Edge Computing
Published in ICPP 2019, 2019
Recommended citation: da Silva Veith, Alexandre; de Souza, Felipe Rodrigo; Dias de Assunção, Marcos; Lefèvre, Laurent; Santos dos Anjos, Julio Cesar
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Monte-Carlo Tree Search and Reinforcement Learning for Reconfiguring Data Stream Processing on Edge Computing
Published in SBAC-PAD 2019, 2019
Recommended citation: da Silva Veith, Alexandre; Dias de Assunção, Marcos; Lefèvre, Laurent
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Scalable Joint Optimization of Placement and Parallelism of Data Stream Processing Applications on Cloud-Edge Infrastructure
Published in ICSOC 2020, 2020
Recommended citation: de Souza, Felipe Rodrigo; da Silva Veith, Alexandre; de Assunção, Marcos Dias; Caron, Eddy
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An Optimal Model for Optimizing the Placement and Parallelism of Data Stream Processing Applications on Cloud-Edge Computing
Published in SBAC-PAD 2020, 2020
Recommended citation: de Souza, Felipe Rodrigo; Dias de Assunção, Marcos; Caron, Eddy; da Silva Veith, Alexandre
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Boosting Big Data Streaming Applications in Clouds with BurstFlow
Published in IEEE Access 2020, 2020
Recommended citation: De Souza Junior, Paulo R. R.; Matteussi, Kassiano J.; da Silva Veith, Alexandre; Zanchetta, Breno F.; R. Q. Leithardt, Valderi; Lozano M., Álvaro; P. de Freitas, Edison; dos Anjos, Julio C. S.; R. Geyer, Claudio F.
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Sustainable Computing on the Edge: A System Dynamics Perspective
Published in HotMobile '21, 2021
Recommended citation: Ramprasad, Brian; da Silva Veith, Alexandre; Gable, Moshe; de Lara, Eyal
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Pain-o-vision, effortless pain management
Published in MobiSys '21: Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services, 2021
Recommended citation: Ramprasad, Brian; Chen, Hongkai; da Silva Veith, Alexandre; Truong, Khai; de Lara, Eyal.
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Latency-Aware Strategies for Deploying Data Stream Processing Applications on Large Cloud-Edge Infrastructure
Published in IEEE TCC 2021, 2021
Recommended citation: da Silva Veith, Alexandre; Dias de Assunção, Marcos; Lefèvre, Laurent.
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Combining DNN partitioning and early exit
Published in EdgeSys '22: Proceedings of the 5th International Workshop on Edge Systems, Analytics and Networking, 2022
Recommended citation: Ebrahimi, Maryam; da Silva Veith, Alexandre; Gabel, Moshe; de Lara, Eyal.
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Shepherd: Seamless Stream Processing on the Edge
Published in The Seventh ACM/IEEE Symposium on Edge Computing, 2022
Recommended citation: Ramprasad, Brian; Mishra, Pritish; Thiessen, Myles; Chen, Hongkai; da Silva Veith, Alexandre; Gable, Moshe; Balmau, Oana; Chow, Abelard; de Lara, Eyal
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PORTEND: A Joint Performance Model for Partitioned Early-Exiting DNNs
Published in The 29th IEEE International Conference on Parallel and Distributed Systems (ICPADS 2023), 2023
Recommended citation: Ebrahimi, Maryam; da Silva Veith, Alexandre; Gabel, Moshe; de Lara, Eyal.
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PathFS: A File System for the Hierarchical Edge
Published in EdgeSys '24: Proceedings of the 7th International Workshop on Edge Systems, Analytics and Networking, 2024
Recommended citation: Dantas de Lima Melo, Vinicius; Thiessen , Myles; Panas, Aleksey; da Silva Veith, Alexandre; Yano, Keijiro; Balmau, Oana; de Lara, Eyal.
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Falcon: Live Reconfiguration for Stateful Stream Processing on the Edge (Best Paper Award)
Published in The Nineth ACM/IEEE Symposium on Edge Computing, 2024
Recommended citation: Mishra, Pritish; Bore, Nelson; Ramprasad, Brian; Thiessen, Myles; Gabel, Moshe; da Silva Veith, Alexandre; Balmau, Oana; de Lara, Eyal
talks
PDPTA 2015 - BSPonP2P: Towards Running Bulk-Synchronous Parallel Applications on P2P Desktop Grids
Published:
ERAD 2016 - Stream Processing Overview - Original Title: Trabalhando com Big Data em Tempo Real
Published:
IFAC 2016 - Strategies for Big Data Analytics through Lambda Architectures in Volatile Environments
Published:
CCGRID 2019 - Distributed Operator Placement for IoT Data Analytics Across Edge and Cloud Resources
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teaching
CR05: Advanced Topics in Scalable Data Management
Graduate course, ENS-Lyon, Computer Science, 2018
General Presentation
Big data is becoming a bigger deal every day. Every day 2.5 Quintillion bytes of data are created. In 2016, big data will affect everyone. These lectures focus on a large point of view of the current data management. In charged of Lecture 8 (Data Stream Processing) and lecture 9 (Practical Session of Data Stream Processing).
CSC2228: Advanced Topics in Mobile and Pervasive Computing: Edge Computing
Graduate course, University of Toronto, Computer Science, 2021
General Presentation
Next generation mobile and IoT applications, such as intelligent personal assistants, medical patient monitoring, and intelligent transportation systems, are not compatible with the existing cloud computing model where applications are deployed on a small number of extremely large datacenters accessible over the wide area network. These applications require either low latencies that are not achievable over the wide area, or produce large volumes of data that can overwhelm the network. Edge computing is a new paradigm that addresses these issues by expanding the traditional cloud architecture with additional datacenter layers that provide computation and storage closer to the end user. For example, a wide-area cloud datacenter which serves a large country can be augmented by a hierarchy of datacenters that provides coverage at the city, neighborhood, and building level. This course provides an overview of some of the current research directions in edge computing..