IEICE TRANSACTIONS on Communications
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Traffic Reduction Technologies and Data Aggregation Control to Minimize Latency in IoT Systems
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The spread of the Internet of Things (IoT) has led to the generation of large amounts of data, requiring massive communication, computing, and storage resources. Cloud computing plays an important role in realizing most IoT applications classified as massive machine type communication and cyber-physical control applications in vertical domains. To handle the increasing amount of IoT data, it is important to reduce the traffic concentrated in the cloud by distributing the computing and storage resources to the network edge side and to suppress the latency of the IoT applications. In this paper, we first present a recent literature review on fog/edge computing and data aggregation as representative traffic reduction technologies for efficiently utilizing communication, computing, and storage resources in IoT systems, and then focus on data aggregation control minimizing the latency in an IoT gateway. We then present a unified modeling for statistical and nonstatistical data aggregation and analyze its latency. We analytically derive the Laplace-Stieltjes transform and average of the stationary distribution of the latency and approximate the average latency; we subsequently apply it to an adaptive aggregation number control for the time-variant data arrival. The transient traffic characteristics, that is, the absorption of traffic fluctuations realizing a stable optimal latency, were clarified through a simulation with a time-variant Poisson input and non-Poisson inputs, such as a Beta input, which is a typical IoT traffic model.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E104-B No.7 pp.706-715
- Publication Date
- 2021/07/01
- Publicized
- 2021/02/04
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2020CQI0002
- Type of Manuscript
- Special Section INVITED PAPER (Special Section on Future Directions of Research and Development on Communication Quality)
- Category
Authors
Hideaki YOSHINO
Nippon Institute of Technology
Kenko OTA
Nippon Institute of Technology
Takefumi HIRAGURI
Nippon Institute of Technology
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Hideaki YOSHINO, Kenko OTA, Takefumi HIRAGURI, "Traffic Reduction Technologies and Data Aggregation Control to Minimize Latency in IoT Systems" in IEICE TRANSACTIONS on Communications,
vol. E104-B, no. 7, pp. 706-715, July 2021, doi: 10.1587/transcom.2020CQI0002.
Abstract: The spread of the Internet of Things (IoT) has led to the generation of large amounts of data, requiring massive communication, computing, and storage resources. Cloud computing plays an important role in realizing most IoT applications classified as massive machine type communication and cyber-physical control applications in vertical domains. To handle the increasing amount of IoT data, it is important to reduce the traffic concentrated in the cloud by distributing the computing and storage resources to the network edge side and to suppress the latency of the IoT applications. In this paper, we first present a recent literature review on fog/edge computing and data aggregation as representative traffic reduction technologies for efficiently utilizing communication, computing, and storage resources in IoT systems, and then focus on data aggregation control minimizing the latency in an IoT gateway. We then present a unified modeling for statistical and nonstatistical data aggregation and analyze its latency. We analytically derive the Laplace-Stieltjes transform and average of the stationary distribution of the latency and approximate the average latency; we subsequently apply it to an adaptive aggregation number control for the time-variant data arrival. The transient traffic characteristics, that is, the absorption of traffic fluctuations realizing a stable optimal latency, were clarified through a simulation with a time-variant Poisson input and non-Poisson inputs, such as a Beta input, which is a typical IoT traffic model.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2020CQI0002/_p
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@ARTICLE{e104-b_7_706,
author={Hideaki YOSHINO, Kenko OTA, Takefumi HIRAGURI, },
journal={IEICE TRANSACTIONS on Communications},
title={Traffic Reduction Technologies and Data Aggregation Control to Minimize Latency in IoT Systems},
year={2021},
volume={E104-B},
number={7},
pages={706-715},
abstract={The spread of the Internet of Things (IoT) has led to the generation of large amounts of data, requiring massive communication, computing, and storage resources. Cloud computing plays an important role in realizing most IoT applications classified as massive machine type communication and cyber-physical control applications in vertical domains. To handle the increasing amount of IoT data, it is important to reduce the traffic concentrated in the cloud by distributing the computing and storage resources to the network edge side and to suppress the latency of the IoT applications. In this paper, we first present a recent literature review on fog/edge computing and data aggregation as representative traffic reduction technologies for efficiently utilizing communication, computing, and storage resources in IoT systems, and then focus on data aggregation control minimizing the latency in an IoT gateway. We then present a unified modeling for statistical and nonstatistical data aggregation and analyze its latency. We analytically derive the Laplace-Stieltjes transform and average of the stationary distribution of the latency and approximate the average latency; we subsequently apply it to an adaptive aggregation number control for the time-variant data arrival. The transient traffic characteristics, that is, the absorption of traffic fluctuations realizing a stable optimal latency, were clarified through a simulation with a time-variant Poisson input and non-Poisson inputs, such as a Beta input, which is a typical IoT traffic model.},
keywords={},
doi={10.1587/transcom.2020CQI0002},
ISSN={1745-1345},
month={July},}
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TY - JOUR
TI - Traffic Reduction Technologies and Data Aggregation Control to Minimize Latency in IoT Systems
T2 - IEICE TRANSACTIONS on Communications
SP - 706
EP - 715
AU - Hideaki YOSHINO
AU - Kenko OTA
AU - Takefumi HIRAGURI
PY - 2021
DO - 10.1587/transcom.2020CQI0002
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E104-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 2021
AB - The spread of the Internet of Things (IoT) has led to the generation of large amounts of data, requiring massive communication, computing, and storage resources. Cloud computing plays an important role in realizing most IoT applications classified as massive machine type communication and cyber-physical control applications in vertical domains. To handle the increasing amount of IoT data, it is important to reduce the traffic concentrated in the cloud by distributing the computing and storage resources to the network edge side and to suppress the latency of the IoT applications. In this paper, we first present a recent literature review on fog/edge computing and data aggregation as representative traffic reduction technologies for efficiently utilizing communication, computing, and storage resources in IoT systems, and then focus on data aggregation control minimizing the latency in an IoT gateway. We then present a unified modeling for statistical and nonstatistical data aggregation and analyze its latency. We analytically derive the Laplace-Stieltjes transform and average of the stationary distribution of the latency and approximate the average latency; we subsequently apply it to an adaptive aggregation number control for the time-variant data arrival. The transient traffic characteristics, that is, the absorption of traffic fluctuations realizing a stable optimal latency, were clarified through a simulation with a time-variant Poisson input and non-Poisson inputs, such as a Beta input, which is a typical IoT traffic model.
ER -
English
