vNV-Heap: An Ownership-Based Virtually Non-volatile Heap for Embedded Systems
The Internet of Batteryless Things might revolutionize our understanding of connected devices by harvesting required operational energy from the environment. These systems come with the system-software challenge that the intermittently powered IoT devices have to checkpoint their state in non-volatile memory to later resume with this state when sufficient energy is available. The scarce energy resources demand that only modified data is persisted before a power failure, which requires precise modification tracking.
We present vNV-Heap, the first ownership-based virtually Non-Volatile Heap for intermittently powered systems with guaranteed power-failure resilience. The heap exploits ownership systems, a zero-cost (i.e., compile-time) abstraction for example implemented by Rust, to track modifications and virtualize object persistence. To achieve power-failure resilience, our heap is designed and implemented to guarantee bounded operations by static program code analysis: For example, the heap allows for determining a worst-case energy consumption for the operation of persisting modified and currently volatile objects. The evaluation of our open-source implementation on an embedded hardware platform (i.e., ESP32-C3) shows that using our heap abstraction is more energy efficient than existing approaches while also providing runtime guarantees by static worst-case bounds.
Tue 17 JunDisplayed time zone: Seoul change
10:30 - 11:50 | |||
10:30 20mTalk | rtesbench: A Multi-core Benchmark Framework for Real-Time Embedded Systems LCTES DOI | ||
10:50 20mTalk | ASC-Hook: Efficient System Call Interception for ARM LCTES Yang Shen National University of Defense Technology, Min Xie National University of Defense Technology, Tao Wu Changsha University of Science and Technology, Wenzhe Zhang National University of Defense Technology, China, Ruibo Wang National University of Defense Technology, Gen Zhang National University of Defense Technology DOI | ||
11:10 20mTalk | SSFFT: Energy-Efficient Selective Scaling for Fast Fourier Transform in Embedded GPUs LCTES Dongwon Yang Korea University, Jaebeom Jeon Korea University, Minseong Gil Korea University, Junsu Kim Korea University, Seondeok Kim Korea University, Gunjae Koo Korea University, Myung Kuk Yoon Ewha Womans University, Yunho Oh Korea University DOI | ||
11:30 20mTalk | vNV-Heap: An Ownership-Based Virtually Non-volatile Heap for Embedded Systems LCTES Markus Elias Gerber Friedrich-Alexander-Universität Erlangen-Nürnberg, Luis Gerhorst Friedrich-Alexander-Universität Erlangen-Nürnberg, Ishwar Mudraje Saarland University, Kai Vogelgesang Saarland University, Thorsten Herfet Saarland University, Peter Wägemann Friedrich-Alexander University Erlangen-Nürnberg (FAU) DOI |