Dynamic profiling and fuzzy-logic-based optimization of sensor network platforms

Abstract

The commercialization of sensor-based platforms is facilitating the realization of numerous sensor network applications with diverse application requirements. However, sensor network platforms are becoming increasingly complex to design and optimize due to the multitude of interdependent parameters that must be considered. To further complicate matters, application experts oftentimes are not trained engineers, but rather biologists, teachers, or agriculturists who wish to utilize the sensor-based platforms for various domain-specific tasks. To assist both platform developers and application experts, we present a centralized dynamic profiling and optimization platform for sensor-based systems that enables application experts to rapidly optimize a sensor network for a particular application without requiring extensive knowledge of, and experience with, the underlying physical hardware platform. In this article, we present an optimization framework that allows developers to characterize application requirements through high-level design metrics and fuzzy-logic-based optimization. We further analyze the benefits of utilizing dynamic profiling information to eliminate the guesswork of creating a “good” benchmark, present several reoptimization evaluation algorithms used to detect if re-optimization is necessary, and highlight the benefits of the proposed dynamic optimization framework compared to static optimization alternatives.