<i>NC-Load</i> : On-Demand Program Loading and Running for Computing Sharing Among IoT Devices

The number of Internet of Things (IoT) devices has increased rapidly in recent years, but lack effective methods to integrate their computational power. In this article, we propose NC-Load, which couples IoT devices into a multiprocessor system, allowing process scheduling across different devices to share their computing power and improve overall throughput. Specifically, NC-Load consists of three key designs, i.e., remote page fault (RPF), lightweight program cropping, and identical memory layout migration, contributing to three merits compared to existing systems: 1) high storage efficiency: the target device launches the program with a locally stored lightweight icon and leverages RPFs to retrieve the required code/data from the source device; 2) on-demand memory loading: only the required memory portions are transmitted when scheduling programs across different devices, which ensures quick recovery of the program; and 3) consistent memory layout: to ensure consistency of addresses after program offloading, the virtual memory area layout of the source device is migrated to the target device. We implement NC-Load on Linux 6.1 and conduct performance evaluation using unmodified programs and the N-Queens cases. The results demonstrate that NC-Load can achieve superior performance in terms of storage efficiency, program performance, memory usage, and throughput.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-12-19
DOI
https://doi.org/10.1109/jiot.2024.3520584
Citations
2
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.70

Funders

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article

NC-Load : On-Demand Program Loading and Running for Computing Sharing Among IoT Devices

Peng Zhao, Ju Ren, Sijing Duan, Feng Lyu et al.
2 citations
IEEE Internet of Things Journal
IoT and Edge/Fog Computing
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article

NC-Load : On-Demand Program Loading and Running for Computing Sharing Among IoT Devices

Peng Zhao, Ju Ren, Sijing Duan, Feng Lyu, Yaoxue Zhang, Yanhao Dong, Yongmin Zhang
article en
2 citations

Abstract

The number of Internet of Things (IoT) devices has increased rapidly in recent years, but lack effective methods to integrate their computational power. In this article, we propose NC-Load, which couples IoT devices into a multiprocessor system, allowing process scheduling across different devices to share their computing power and improve overall throughput. Specifically, NC-Load consists of three key designs, i.e., remote page fault (RPF), lightweight program cropping, and identical memory layout migration, contributing to three merits compared to existing systems: 1) high storage efficiency: the target device launches the program with a locally stored lightweight icon and leverages RPFs to retrieve the required code/data from the source device; 2) on-demand memory loading: only the required memory portions are transmitted when scheduling programs across different devices, which ensures quick recovery of the program; and 3) consistent memory layout: to ensure consistency of addresses after program offloading, the virtual memory area layout of the source device is migrated to the target device. We implement NC-Load on Linux 6.1 and conduct performance evaluation using unmodified programs and the N-Queens cases. The results demonstrate that NC-Load can achieve superior performance in terms of storage efficiency, program performance, memory usage, and throughput.

IEEE Internet of Things JournalVol. 12(9)
Central South University (CN), Tsinghua University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 26%
IoT and Edge/Fog Computing
0.70
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