Introduction

Moving away from battery-based Wireless Sensor Networks (WSNs) is a recent trend. Instead harvesting energy from the node's environment, through solar panels or temperature differences is favored. Our study [1] has shown that harvesting energy from temperature differences between soil and air is feasible. However, no scheduling algorithm was used. Instead, energy was used immedeately when it was harvested/available, until the energy store was emptied. This leads to the behavior shown below: During the day, enough energy can be harvested. However, less energy is available during night, or in general during days with less energy. It is easy to see, that days vary very much. Therefore an optimized scheduling strategy is required to use energy more efficient.

Task

Your task is to analyze the data set from [1] and develop scheduling strategies for intermittent systems, such as energy harvested nodes. You should consider more than one node, because scheduling involves sending packets to other nodes, with slightly different energy. You should use different sequences of the study's data as an input for the different nodes, to have a varying energy pattern. Additionally, you can use temperature from different depths to simulate different energy production throughout the simulation. Finally, our existing simulation should be extended, to integrate multiple nodes with different energy patterns.

Literature

1. [Pullwitt:2018:FSE:3277883.3277886]

Skills

The following skills are helpful for the execution of this thesis (not all of them are required!):

• Python
• Energy Harvesting
• Scheduling
• Simulation

Links

• Hinweise zur Durchführung von studentischen Arbeiten am IBR