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Reliability Versus Latency in IIoT Visual Applications: A Scalable Task Offloading Framework

delete2022-09-01
delete8
PRE
AI
J
Junchao Ma *
B
Bodong Shang
H
Hao Song
黄
黄永明 (Yongming Huang)
P
Pingzhi Fan
DOI:10.1109/JIOT.2022.3148115delete
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摘要

摘要

En 中文
In Industrial Internet of Things (IIoT), reliability and latency are two important performance indicators. However, these two performance indicators are contradictory with each other, which are difficult to be enhanced simultaneously. In reality, many IIoT applications are in video or image format with critical requirements of both reliability and latency. In this article, we propose a scalable task offloading scheme for IIoT visual applications considering the unique scalable feature compared with general content. The proposed scheme demonstrates that partial content can be adaptively offloaded to a specific computing node to meet the reliability and latency requirements, meanwhile obtaining an excellent tradeoff between them. For optimization, a utility function is defined to characterize the tradeoff between reliability and latency. Then, a greedy algorithm is introduced to solve the problem of maximizing the utility function, where a near-optimal scheduling policy is adopted to achieve offloading association and properly offload data volume. Simulation results reveal that the proposed scalable task offloading scheme performs better than other benchmark schemes in balancing reliability and latency in IIoT visual applications, especially when the network traffic is moderate and channel conditions are undesirable.
Keyword:
Task analysis
Industrial Internet of Things
Reliability
Visualization
Computational modeling
Streaming media
Wireless communication
Industrial Internet of Things (IIoT) visual application
latency
reliability
scalable task offloading
utility function

期刊

IEEE Internet of Things Journal 封面图
IEEE Internet of Things Journal
IF:
8.9
论文数:
1.4W
被引数:
7.8W

机构

S
Southwest Jiaotong University
学者数:
2.9W
论文数: 2.1W
被引数: 2.3W
I
Intel Corporation
学者数:
2.7K
论文数: 2.0K
被引数: 6
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