Electrical and Computer Engineering ETDs
Publication Date
Fall 10-18-2021
Abstract
In this thesis, we address the problem of prolonging the battery life of Internet of Things (IoT) nodes by introducing a smart energy harvesting framework for IoT networks supported by femtocell access points (FAPs) based on the principles of Contract Theory and Reinforcement Learning. Initially, the IoT nodes’ social and physical characteristics are identified and captured through the concept of IoT node types. Then, Contract Theory is adopted to capture the interactions among the FAPs, who provide personalized rewards, i.e., charging power, to the IoT nodes to incentivize them to invest their effort, i.e., transmission power, to report their data to the FAPs. The IoT nodes’ and FAPs’ contract-theoretic utility functions are formulated, following the network economic concept of the involved entities’ personalized profit. A contract-theoretic optimization problem is introduced to determine the optimal personalized contracts among each IoT node connected to a FAP, i.e., a pair of transmission and charging power, aiming to jointly guarantee the optimal satisfaction of all the involved entities in the examined IoT system. An artificial intelligent framework based on reinforcement learning is introduced to support the IoT nodes’ autonomous association to the most beneficial FAP in terms of long-term gained rewards. Finally, a detailed simulation and comparative results are presented to show the pure operation performance of the proposed framework, as well as its drawbacks and benefits, compared to other approaches. Our findings show that the personalized contracts offered to the IoT nodes outperform by a factor of four compared to an agnostic type approach in terms of the achieved IoT system’s social welfare.
Keywords
Smart, Energy Harvesting, IoT, Networks
Document Type
Thesis
Language
English
Degree Name
Computer Engineering
Level of Degree
Masters
Department Name
Electrical and Computer Engineering
First Committee Member (Chair)
Eirini Eleni Tsiropoulou
Second Committee Member
Jim Plusquellic
Third Committee Member
Payman Zarkesh-Ha
Recommended Citation
Sangoleye, Fisayo. "Smart Energy Harvesting for Internet of Things Networks." (2021). https://digitalrepository.unm.edu/ece_etds/508