MSc project: IoT Monitoring and Analysis System

This page describes an example Master student project previously offered in the DNA lab.

Background

The Internet of Things (IoT) is expected to be more and more present in our everyday lives. Objects are progressively becoming smart objects: smartTVs, smartphones, smartwatches, etc. These heterogeneous objects have more computing power, and have the ability to collect data, to communicate with each other, and to access the Internet.

Mobile cloud computing [1] leverages the unique advantages of heterogeneous devices in the IoT, sharing their computing power and collected data to locally collaborate in processing tasks they could not achieve individually, and create an ambient intelligence. Examples of applications found in the literature include
distributed image processing, crowd sourcing and computing, sensor data sharing, social networking, or context recognition.

Sensors embedded in smart objects can generate a large amount of data, this Big Data has to be stored, potentially remotely in a cloud. To communicate with each other, the basic model is envisioned to be client-server, i.e., each IoT device acts as a data server, and transmits the data to another device acting as a client, which can in its turn act as a server of that data [2].

Computational offloading, also known as cyber foraging, has greatly evolved over the last few years. Recent examples of research works include making devices offload code to remote cloud resources [3] and to other devices [4].

Objectives

This master thesis can also be done as an internship if requested. It includes:
• Compiling a survey on available tools and approaches to share data and computational tasks.
• Setting up a simple experimental network of smart objects, and implement an efficient data collection and monitoring architecture.
• Explore context recognition and collaborative mechanisms.

Supervisors

Dr Fehmi Ben Abdesslem (SICS Swedish ICT) and Dr Anders Lindgren (SICS Swedish ICT & Luleå University of Technology).

Dates

The length, start date and precise technical content of the internship are negotiable. Apply before May 29th 2014.

References

[1] Fernando, Niroshinie, Seng W. Loke, and Wenny Rahayu. 2013 "Mobile cloud computing: A survey." Future Generation Computer Systems 29.1:84-106.

[2] Olov Schelén, Robert Brännström, and Christer Åhlund. 2013. A sensor-data acquisition grid architecture. Networking, Sensing and Control (ICNSC), 2013 10th IEEE International Conference on. IEEE.

[3] Eduardo Cuervo, Aruna Balasubramanian, Dae-ki Cho, Alec Wolman, Stefan Saroiu, Ranveer Chandra, and Paramvir Bahl. 2010. MAUI: making smartphones last longer with code offload. In Proceedings of the 8th international conference on Mobile systems, applications, and services (MobiSys'10). ACM, New York, NY, USA.

[4] Cong Shi, Vasileios Lakafosis, Mostafa H. Ammar, and Ellen W. Zegura. 2012. Serendipity: enabling remote computing among intermittently connected mobile devices. In Proceedings of the thirteenth ACM internation

Interested?

Please contact Fehmi Ben Abdesslem, fehmi [at] sics.se or Anders Lindgren, andersl [at] sics.se