Adaptive energy management for solar energy harvesting wireless sensor nodes

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Author
Aydin, Abdul Kerim
Advisor
Akar, Nail
Date
2018-09Publisher
Bilkent University
Language
en_US
Type
Thesis
Metadata
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http://hdl.handle.net/11693/48073Abstract
Wireless Sensor Networks (WSN) will have a key role in the upcoming era of the
Internet of Things (IoT) as they will be forming the basis of communication infrastructure.
Energy harvesting has been a widely used instrument for prolonging
the battery life and enhancing the quality of service (QoS) of sensor nodes (SN).
In this study, we investigate adaptive transmission policies for a solar-powered
wireless sensor node which is tasked with sending status updates to a gateway as
frequently as possible with energy-neutral operation constraints. On the basis of
empirical data, we model the daily variations of the solar energy harvesting process
with a Discrete Time Markov Chain (DTMC). When the number of states
of the DTMC is increased, the harvesting process is modeled more accurately.
Using the DTMC model, we formulate the energy management problem of the
WSN node as a Markov Decision Process (MDP); and based on this model, we
use the policy iteration algorithm to obtain optimal energy management policies
so as to minimize the average Age of Information (AoI) of the corresponding status
update system. We validate the effectiveness of the proposed approach using
datasets belonging to two different locations with 20 years of solar radiance data.