Optimizing Energy States in Mobile Embedded Systems: A SIPN-Based Approach

This paper delves into the analysis, modeling, and power optimization of energy states in mobile embedded devices using Signal Interpreted Petri Nets (SIPNs). Utilizing a multi-factor authentication device as a case study, we first introduce its essential functions and possible energy states. We propose a taxonomy for classifying these energy states into elementary types based on energy inflow and storage conditions. A primary classification into Optimal, Suboptimal, and Critical energy states is proposed. Furthermore, we explore complex energy states where elementary types overlap, discussing their analysis and optimization using Petri Net hierarchies. These energy states are then modeled and analyzed via SIPN, focusing on properties like reachability and liveness for enhanced power optimization. Ultimately, this research offers a framework for better understanding and optimizing the energy efficiency of mobile embedded systems.