My Master Thesis: Data Analytics Platform for IoT Environments

My thesis for the master of Telecommunication Technologies, Systems and Networks at Universitat Politècnica de València was creating a data analytics platform for IoT environments with the supervesion of Prof. Carlos Enrique Palau.

Abstract:

With the appearance of the term of Big Data that is conjugated with the evolution of IoT devices and platforms, the need to have networks for IoT platforms more intelligent, more powerful, more efficient, more secure, more reliable, and more scalable has arised. The technologies of Software Defined Networking (SDN) and Network function virtualization (NFV) play an important role to facilitate the challenges and make IoT platform network components more effective with using less network resources. We tried to build a tool to analyze network data, measure the efficiency, and show statistical information of those IoT platform network components with different network technologies. 

Methodology:

Create a virtual platform with Ubuntu 16.04 using Docker 17.06.0-ce with its containers: Logstash, Elasticsearch and Kibana. A use case is considered by using two IoT network devices as data sources: Openvswitch log as internal source (installed on the same virtual machine) and TCP connection as external source. 

Results

This platform can offer analytic information for different IoT network devices for different technologies (SDN, NFV) that are connected with. Kibana interface facilitates for user having statistical information on the received data, searching for a specific information in a customized timeline

The full master thesis can be found on: http://hdl.handle.net/10251/91766