Leakage-aware energy synchronization for wireless sensor networks

Abstract

To ensure sustainable operations of wireless sensor systems, environmental energy harvesting has been regarded as the right solution for long-term applications. In energy-dynamic environments, energy conservation is no longer considered necessarily beneficial, because energy storage units (e.g., batteries or capacitors) are limited in capacity and leakageprone. In contrast to legacy energy conservation approaches, we aim at energy synchronization for wireless sensor devices. The starting point of this work is TwinStar, which uses ultra-capacitor as the only energy storage unit. To efficiently use the harvested energy, we design and implement leakage-aware feedback control techniques to match local and network-wide activity of sensor nodes with the dynamic energy supply from environments. We conduct system evaluation under three typical real-world settingsindoor, outdoor, and mobile backpack under a wide range of system settings. Results indicate our leakage-aware control can effectively utilize energy that could otherwise leak away. Nodes running leakage-aware control can enjoy 70% more energy than the ones running non-leakage-aware control and application performance (e.g., event detection) can be improved significantly.

RF-MAC: A Medium Access Control Protocol for Re-Chargeable Sensor Networks Powered by Wireless Energy Harvesting

“…MAC protocols that aim for energy conservation have been extensively explored in the recent past, with a comprehensive classification and survey on this topic presented in [4], [14], [16], [19]. In this section, we review the related MAC protocols for energy harvesting sensor networks.…”

LB-MAC: A Lifetime-Balanced MAC Protocol for Sensor Networks

“…With the input mapping between battery readings and residual energy levels, a sensor node can estimate its residual nodal lifetime based on its voltage reading and consumption rate. To reduce the overhead for storing the mapping information, the whole voltage range can be divided into multiple segments such that the mapping relation for each segment can be captured with a simple function; this way, only the functions and segment information need to be stored [21]. Though our current implementation requires extra measurement work to find out the mapping between battery readings and residual energy levels, we believe that more precise and pervasive hardware support will be available in near future due to the increasing demand of lifetime-aware services [1].…”

Energy management in sensor networks

“…By using the photovoltaic effect, which converts light to electrical power, solarcell-based energy harvesting techniques provide orders of magnitude higher power density than other technologies. Because of this, most existing energy harvesting systems used in sensor networks are based on solar cells, such as Heliomote [2], Prometheus [6], Trio [1], AmbiMax [7], PicoNodes [13], PUMA [14] and TwinStar [15]. To design a highly efficient solar-based harvesting system, these solar-based designs need to employ a maximum power point tracker (MPPT).…”

“…Although ultracapacitor-based designs have many advantages, they impose a major challenge: the energy leakage of ultracapacitors is high when they reach their full capacity. Recently, two capacitor-based energy harvesting and storage systems-TwinStar [15] and eShare [20]-have been proposed. The TwinStar system provides local leakage-aware energy control, and the eShare system supports global leakage-aware energy sharing.…”