Smart energy management and low-power design of sensor and actuator nodes on algorithmic level for self-powered sensorial materials and robotics

Abstract

We propose and demonstrate a design methodology for embedded systems satisfying low power requirements suitable for self-powered sensor and actuator nodes. This design methodology focuses on 1. smart energy management at runtime and 2. application-specific System-On- Chip (SoC) design at design time, contributing to low-power systems on both algorithmic and technology level. Smart energy management is performed spatially at runtime by a behaviour-based or state-action-driven selection from a set of different (implemented) algorithms classified by their demand of computation power, and temporally by varying data processing rates. It can be shown that power/energy consumption of an application-specific SoC design depends strongly on computation complexity. Signal and control processing is modelled on abstract level using signal flow diagrams. These signal flow graphs are mapped to Petri Nets to enable direct high-level synthesis of digital SoC circuits using a multi-process architecture with the Communicating-Sequential-Process model on execution level. Power analysis using simulation techniques on gatelevel provides input for the algorithmic selection during runtime of the system, leading to a closed-loop design flow. Additionally, the signal-flow approach enables power management by varying the signal flow and data processing rates depending on actual energy consumption, estimated energy deposit, and required Quality-of-Service.