Value of Information Aware Opportunistic Duty Cycling in Solar Harvesting Sensor Networks

TL;DR

This paper introduces an energy-efficient opportunistic duty cycling scheme for solar-powered sensor networks that dynamically balances energy harvesting and data importance to enable perpetual operation.

Contribution

It models the duty cycling problem as a budget-dynamic Multi-Arm Bandit problem and proposes a distributed scheme that adapts based on local energy and data value estimates.

Findings

The scheme effectively balances energy use and data importance.

Theoretical analysis confirms low regret compared to optimal strategies.

Experimental results demonstrate promising performance in real scenarios.

Abstract

The energy-harvested Wireless Sensor Networks (WSNs) may operate perpetually with the extra energy supply from ambient natural energy, such as solar energy. Nevertheless, the harvested energy is still limited so it's not able to support the perpetual network operation with full duty cycle. To achieve the perpetual network operation and process the data with high importance, measured by Value of Information (VoI), the network has to operate under partial duty cycle and to improve the efficiency to consume the harvested energy. The challenging problem is how to deal with the stochastic feature of the natural energy and the variable data VoI. We consider the energy consumption during storing and the diversity of the data process including sampling, transmitting and receiving, which consume different power levels. The problem is then mapped as the budget-dynamic Multi-Arm Bandit (MAB) problem by treating the energy as the budget and the data process as arm pulling. This paper proposes an Opportunistic Duty Cycling (ODC) scheme to improve the energy efficiency while satisfying the perpetual network operation. ODC chooses the proper opportunities to store the harvested energy or to spend it on the data process based on the historical information of the energy harvesting and the VoI of the processed data. With this scheme, each sensor node need only estimate the ambient natural energy in short term so as to reduce the computation and the storage for the historical information. It also can distributively adjust its own duty cycle according to its local historical information. This paper also conducts the extensive analysis on the performance of our scheme ODC, and the theoretical results validate the regret, which is the difference between the optimal scheme and ours. Our experimental results also manifest the promising performance of ODC.