Data and Resource Management on the Internet of Things

• Grant number: 20/12891-0
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: December 01, 2020
• End date: September 30, 2021
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Agreement: MCTI/MC
• Principal Investigator: Paulo de Figueiredo Pires
• Grantee: Tiago Cariolano de Souza Xavier
• Host Institution: Instituto de Computação. Universidade Federal Fluminense (UFF). Ministério da Educação (Brasil). Niterói , SP, Brazil
• Associated research grant: 15/24144-7 - Technologies and solutions for enabling the cloud of things paradigm, AP.TEM

Abstract

As society becomes more interconnected, organizations and individuals scattered across the globe produce vast amounts of data as a result of their interactions with the physical world and with each other. The Internet of Things (IoT) is the paradigm that allows the instrumentation of the physical world through devices, the integration of these devices with each other and with other resources available via the Internet, and the exploration of the data generated by the devices to feed users' systems and applications, producing value-added services and information. In order to fully realize the vision advocated by the IoT paradigm, there are several practical and research challenges to be overcome. In particular, it is necessary to investigate and propose solutions for the effective and efficient management of the enormous amount of data produced and the resources necessary for its manipulation. In this scenario, the solutions range from software frameworks and architectures, practices, methodologies, algorithms, and procedures to properly manage data and resources considering the entire life cycle of IoT systems and the huge amount of data generated by the devices. Such architectures, practices and procedures require resource management systems that include flexible mechanisms for the management and processing of data flows and events generated by the dynamic objects that are part of IoT. Software solutions and new architectures will be proposed to manage data flow processing using the restricted capabilities of IoT devices and other devices located at the edge of the network. Among the main challenges to be dealt with in this project are dealing with the communication and real-time processing of data in an environment of heterogeneous resources and applications, transaction management operations adapted to streams, the allocation of resources to serve applications heterogeneous and with strict latency requirements, and the energy savings of the devices that make up the physical infrastructure of the IoT.

Scientific publications

(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)

XAVIER, TIAGO C. S.; DELICATO, FLAVIA C.; PIRES, PAULO F.; AMORIM, CLAUDIO L.; LI, WEI; ZOMAYA, ALBERT. Managing Heterogeneous and Time-Sensitive IoT Applications through Collaborative and Energy-Aware Resource Allocation. ACM TRANSACTIONS ON INTERNET OF THINGS, v. 3, n. 2, p. 28-pg., 2022-05-01. (20/12891-0)