Offloading Data Fusion to Programmable Data Planes

Big data refers to a class of applications that operate on large amounts of data. One paradigm that fits the big data applications category is the Internet of Things (IoT). Millions of IoT devices continuously produce data and exchange information to support critical applications in different scenarios, such as smart cities and smart homes. As IoT devices become more popular, new techniques are necessary to accurately analyze data collected from devices and communicate efficiently with minimal delays. Data fusion is one widely used technique for performing accurate decisions. Data fusions process data from multiple sensors by integrating them at a single information source. This project aims to devise methods to offload the data fusion computation into the programmable data plane at the network edge to integrate strategies that improve communication and analysis of data collected from IoT environments. The systems we envision using our methods can, for example, improve the processing of big data collected from IoT devices using computation on switches.

Faculty Supervisor:

Israat Haque

Student:

Partner:

Universidade Federal do Rio Grande do Sul

Discipline:

Computer science

Sector:

Artificial Intelligence; Technology

University:

Dalhousie University

Program: