An empirical study of harvesting-aware duty cycling in environmentally-powered wireless sensor networks

Abstract

In an environmentally-powered wireless sensor network, where nodes are powered solely by harvesting energy from ambient sources, node operation highly depends on the energy availability and harvesting rate. For duty-cycling schemes to support existing wireless sensor network applications, they need to adapt the nodes' sleep-wake schedules according to energy harvesting and consumption rates. In this paper, we propose a harvesting-aware duty-cycling scheme, perform an empirical study of this scheme over a solar harvesting powered wireless sensor network in a source-relay-sink configuration, and provide some experimental results to illustrate its throughput performance under various light conditions.

Relay node selection scheme and deep sleep period for power management in energy‐harvesting wireless sensor networks

“…The network may not be capable to render its own function due to the death of many of its nodes. Thus, network age is closely related to node lifetime and also represents an important and leading feature of sensor network [3]. At the same time, replacing/replenishing the batteries of each node periodically is an exorbitant cost.…”

“…In fact, several existing research works aim to save the energy consumption of sensors through the use of innovative conservation schemes like load balancing and clustering [4][5][6], especially the increase of its lifetime. The technique of "duty cycling" [7] is one those schemes, which seems very interesting to us, where all nodes within WSN can switch individually from waking to sleep or vice versa, and this switch is based on the use of MAC protocols, which can be assorted into two types: synchronous and asynchronous MAC protocols [3,8,9]. In the first type of these protocols like S-MAC [10], the nodes share the timetable information that appoints their cycle of sleep and activity period by the control packets.…”

Ambient Source and Energy Prediction for Energy-Aware Task Scheduling in IoT

“…However, this work lacks the ambient prediction and the novelty in the task scheduling algorithm. In [22], the authors demonstrated an energy balancing method, via a duty cycle process to minimize the energy consumption of sensor nodes equipped with solar harvesters.…”