System architecture directions for networked sensors
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Contiki - A Lightweight and Flexible Operating System for Tiny Networked Sensors
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
Nano-RK: An Energy-Aware Resource-Centric RTOS for Sensor Networks
RTSS '05 Proceedings of the 26th IEEE International Real-Time Systems Symposium
Mementos: system support for long-running computation on RFID-scale devices
Proceedings of the sixteenth international conference on Architectural support for programming languages and operating systems
Dewdrop: an energy-aware runtime for computational RFID
Proceedings of the 8th USENIX conference on Networked systems design and implementation
Programming micro-aerial vehicle swarms with karma
Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
DoubleDip: leveraging thermoelectric harvesting for low power monitoring of sporadic water use
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
Enabling bit-by-bit backscatter communication in severe energy harvesting environments
NSDI'14 Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation
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As sensors penetrate into deeply embedded settings such as implantables, wearables, and textiles, they present new challenges due to their tiny energy buffers and extremely low harvesting conditions under which they need to operate. However, existing low-power operating systems are not designed with the goal of scaling down to such severely constrained environments. We address these challenges with QuarkOS, an OS that scales down by carefully dividing every communication, sensing, and computation task into tiny fragments (e.g. half-bit, one pixel) and introduces sleeps between such fragments to re-charge. In addition QuarkOS is designed to have minimal run-time overhead, while still adapting performance to harvesting conditions. Our results are promising and show continuous communication from an RF-powered CRFID can occur at a third of the harvesting levels of prior approaches, and continuous image sensing to be performed with a tiny solar panel under natural indoor light.