Wireless Sensor Node Analysis Employing Energy Harvesting

Wireless Sensor Node Analysis Employing Energy Harvesting

Internship Description

The project consist of a theoretical and a system research thrusts in energy-harvesting wireless sensor networks. Looking at the energy harvesting module in sensor node from the system’s prospective, we observe that adopting an interruption/harvesting policy enhances the energy consumption, but it also increases average packet end-to-end delay and packet dropping! There are various tradeoffs exist in wireless sensor network (WSN) design. Of particular interest to the project are 1) End-to-end delay vs. energy harvesting & network size, and 2) Increasing network size allows for a smaller number of data sink nodes and reduces dropping but it also increases average end-to-end delay. In order to quantify the tradeoffs, we raise a question. How delay, network size, and harvesting policy (service vacation) interact with each other? In other words, how large the network dimensions can go to considering certain packet latency threshold and dropping? Energy harvesting module can arbitrary be triggered, upon empty buffers, and thus, imposes random interruption periods on the sensor node, these random cycles (vacations) increases latency due to residual vacation time that is consumed for harvesting. In order to solve the above challenge, the student will study this system and think of a theoretical and a system approaches (with the assistance of the instructor) to improve the end-to-end delay. For instance, a possible solution would be, instead of arbitrary harvesting time, we aim at optimizing this value to minimize the delay and dropping. We also aim at adding a constraint that forces the sensor node to trigger the harvesting phase once its battery is low! Currently, the networking lab has a set of 20 sensor motes that are programmable using TinyOS and also has all the necessary mathematical packages to evaluate the student proposed models. 

Deliverables/Expectations

The student is expected to achieve:

1.       (theatrical component): An optimization of the energy harvesting value that minimizes the system end-to-end delay validated using matlab.

2.       (systems component): Translate the results from (1) into a working code, which can be tested over our TelosB sensor motes using TinyOS (C/C++).

 

The above results, if completed, are considered novel and can result into a publication with the agreement with the instructor.​

Faculty Name

Basem Shihada

Field of Study

Computer science and electrical engineering