Ambient energy harvesting nonvolatile processors

Liu, Yongpan; Li, Zewei; Li, Hehe; Wang, Yudong; Li, Xueqing; Ma, Kaisheng; Li, Shuangchen; Chang, Meng-Fan; Sampson, John J.; Xie, Yuan; Shu, Jiwu; Yang, Huazhong

doi:10.1145/2744769.2747910

Cited by 124 publications

(44 citation statements)

References 39 publications

(63 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To smooth out large temporal variations in harvested energy, the IoT device has on-board energy storage 1 .…”

Section: A System Modelmentioning

confidence: 99%

“…The amount of energy harvested is highly time varying and the energy supply is intermittent. For this reason, processors with off-chip nonvolatile main memory (and potentially even on-chip caches and register files) have been proposed [1], [6] to guarantee forward progress of program execution. In these approaches, the processor saves its intermediate results in non-volatile memory when the energy supply is too low for the processor to operate.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal checkpointing for secure intermittently-powered IoT devices

Ghodsi

Garg

Karri

2017

2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)

View full text Add to dashboard Cite

Abstract-Energy harvesting is a promising solution to power Internet of Things (IoT) devices. Due to the intermittent nature of these energy sources, one cannot guarantee forward progress of program execution. Prior work has advocated for checkpointing the intermediate state to off-chip non-volatile memory (NVM). Encrypting checkpoints addresses the security concern, but significantly increases the checkpointing overheads. In this paper, we propose a new online checkpointing policy that judiciously determines when to checkpoint so as to minimize application time to completion while guaranteeing security. Compared to state-of-the-art checkpointing schemes that do not account for the overheads of encrypted checkpoints we improve execution time up to 1.4×.

show abstract

“…To smooth out large temporal variations in harvested energy, the IoT device has on-board energy storage 1 .…”

Section: A System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal checkpointing for secure intermittently-powered IoT devices

Ghodsi

Garg

Karri

2017

2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)

View full text Add to dashboard Cite

show abstract

“…Fig. 1 shows a storage-less energy harvesting platform [10,11] powered by ambient energy sources. Due to variations of energy sources and lacking of energy buffers, the collected energy is justin-time for usage and the node oscillates between ON and OFF states.…”

Section: Motivationmentioning

confidence: 99%

Performance-aware task scheduling for energy harvesting nonvolatile processors considering power switching overhead

Liu

et al. 2016

Proceedings of the 53rd Annual Design Automation Conference

Self Cite

View full text Add to dashboard Cite

Nonvolatile processors have manifested strong vitality in batteryless energy harvesting sensor nodes due to their characteristics of zero standby power, resilience to power failures and fast read/write operations. However, I/O and sensing operations cannot store their system states after power off, hence they are sensitive to power failures and high power switching overhead is induced during power oscillation, which significantly degrades the system performance.In this paper, we propose a novel performance-aware task scheduling technique considering power switching overhead for energy harvesting nonvolatile processors. We first give the analysis of the power switching overhead on energy harvesting sensor nodes. Then, the scheduling problem is formulated by MILP (Mixed Integer Linear Programming). Furthermore, a task splitting strategy is adopted to improve the performance and an heuristic scheduling algorithm is proposed to reduce the problem complexity. Experimental results show that the proposed scheduling approach can improve the performance by 14% on average compared to the state-of-theart scheduling strategy. With the employment of the task splitting approach, the execution time can be further reduced by 10.6%.

show abstract

“…Thus, after a supply interruption, the system state is restored and the program continues from the point where it was interrupted, instead of restarting from the beginning. Recent hardware approaches overcome the need to save and restore the system’s state by using non-volatile processors [8]. These approaches are only effective in retaining the state of on-chip peripherals that are controlled by the special function registers of the microcontroller unit (MCU), e.g., internal ADCs.…”

Section: Introductionmentioning

confidence: 99%

RESTOP: Retaining External Peripheral State in Intermittently-Powered Sensor Systems

Arreola

Balsamo

Merrett

et al. 2018

Sensors

View full text Add to dashboard Cite

Energy harvesting sensor systems typically incorporate energy buffers (e.g., rechargeable batteries and supercapacitors) to accommodate fluctuations in supply. However, the presence of these elements limits the miniaturization of devices. In recent years, researchers have proposed a new paradigm, transient computing, where systems operate directly from the energy harvesting source and allow computation to span across power cycles, without adding energy buffers. Various transient computing approaches have addressed the challenge of power intermittency by retaining the processor’s state using non-volatile memory. However, no generic approach has yet been proposed to retain the state of peripherals external to the processing element. This paper proposes RESTOP, flexible middleware which retains the state of multiple external peripherals that are connected to a computing element (i.e., a microcontroller) through protocols such as SPI or I2C. RESTOP acts as an interface between the main application and the peripheral, which keeps a record, at run-time, of the transmitted data in order to restore peripheral configuration after a power interruption. RESTOP is practically implemented and validated using three digitally interfaced peripherals, successfully restoring their configuration after power interruptions, imposing a maximum time overhead of 15% when configuring a peripheral. However, this represents an overhead of only 0.82% during complete execution of our typical sensing application, which is substantially lower than existing approaches.

show abstract

Ambient energy harvesting nonvolatile processors

Cited by 124 publications

References 39 publications

Optimal checkpointing for secure intermittently-powered IoT devices

Optimal checkpointing for secure intermittently-powered IoT devices

Performance-aware task scheduling for energy harvesting nonvolatile processors considering power switching overhead

RESTOP: Retaining External Peripheral State in Intermittently-Powered Sensor Systems

Contact Info

Product

Resources

About