Data Orchestration for Urban Computing through Fog Computing

• Grant number: 18/23126-3
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: September 01, 2019
• End date: October 31, 2020
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Leandro Aparecido Villas
• Grantee: Maycon Leone Maciel Peixoto
• Host Institution: Instituto de Computação (IC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 15/24494-8 - Communications and processing of big data in cloud and fog computing, AP.TEM
• Associated scholarship(s): 19/24938-4 - Reduction of traffic flow data through fog computing, BE.EP.PD

Abstract

In an Urban Computing, there are several sensors producing a huge amount of data from an Intelligent Transportation System. These data can be difficult to process, analyze and store even for Cloud Computing. Thus, Fog Computing, as an extension of Cloud Computing, is used to perform perform services directly at the edge of the network, providing low latency and real-time computing. In this case, Fog can provide infrastructure to store and process data for decision making, even if autonomously, regardless of the state of the Cloud infrastructure. In this way, this project aims to foment research in Cloud Computing, under the angle of Fog Computing, through the study, proposition and evaluation of techniques that seek to contribute state-of-the-art in the fundamental issue of data produced from a Intelligent Transportation System. The overall goal of this project is to reduce the volume of data and increase the relevance before to sent them to the Cloud. For this, a mechanism will be developed to deal with data orchestration, identifying which part of the data load will be handled by edge computing resources and which part will be handled by the Cloud. Finally, it should be noted that this proposal is linked to the thematic project financed by FAPESP (process: 2015/24494-8).

Scientific publications

(6)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

PEIXOTO, MAYCON L. M.; CRUZ, EDSON M.; MAIA, ADRIANO H. O.; SANTOS, MARIESE C. A.; LOBATO JUNIOR, WELLINGTON, V; VILLAS, LEANDRO A.; IEEE. Exploiting Fog Computing with an Adapted DBSCAN for Traffic Congestion Detection System. 2020 IEEE 92ND VEHICULAR TECHNOLOGY CONFERENCE (VTC2020-FALL), v. N/A, p. 5-pg., 2020-01-01. (18/23126-3, 15/24494-8)

MACIEL PEIXOTO, MAYCON LEONE; GENEZ, THIAGO A. L.; BITTENCOURT, LUIZ F.. Hierarchical Scheduling Mechanisms in Multi-Level Fog Computing. IEEE TRANSACTIONS ON SERVICES COMPUTING, v. 15, n. 5, p. 14-pg., 2022-09-01. (18/23126-3, 15/24494-8)

LOBATO JUNIOR, WELLINGTON; DE SOUZA, ALLAN M.; PEIXOTO, MAYCON L. M.; ROSARIO, DENIS; VILLAS, LEANDRO; IEEE. A Cache Strategy for Intelligent Transportation System to Connected Autonomous Vehicles. 2020 IEEE 92ND VEHICULAR TECHNOLOGY CONFERENCE (VTC2020-FALL), v. N/A, p. 5-pg., 2020-01-01. (18/23126-3, 15/24494-8)

PEIXOTO, M. L. M.; MAIA, A. H. O.; MOTA, E.; RANGEL, E.; COSTA, D. G.; TURGUT, D.; VILLAS, L. A.. A traffic data clustering framework based on fog computing for VANETs. VEHICULAR COMMUNICATIONS, v. 31, OCT 2021. (18/23126-3, 15/24494-8)

RODRIGUES, DIEGO O.; MAIA, GUILHERME; BRAUN, TORSTEN; LOUREIRO, ANTONIO A. F.; PEIXOTO, MAYCON L. M.; VILLAS, LEANDRO A.. Exploring Hybrid-Multimodal Routing to Improve User Experience in Urban Trips. APPLIED SCIENCES-BASEL, v. 11, n. 10, MAY 2021. (18/23126-3, 18/19639-5, 18/12447-3, 15/24494-8, 20/11259-9)

PEIXOTO, M. L. M.; MOTA, E.; MAIA, A. H. O.; LOBATO, W.; SALAHUDDIN, M. A.; BOUTABA, R.; VILLAS, L. A.. FogJam: A Fog Service for Detecting Traffic Congestion in a Continuous Data Stream VANET. Ad Hoc Networks, v. 140, p. 15-pg., 2023-03-01. (18/23126-3, 19/19105-3, 15/24494-8)