Paper Info
Title
Adaptive Control of Statistical Data Aggregation to Minimize Latency in IoT Gateway.
Abstract
Latency-critical Internet of Things (IoT) applications, such as factory automation and smart grids, have received great attention recently. To satisfy the stringent latency requirements for such applications, it is important to suppress the latency in an IoT gateway that aggregates a large amount of small-sized data from massive IoT devices. In a previous study, we have analyzed two fundamental statistical data aggregation schemes for the IoT gateway: constant interval and constant number, and derived simple and accurate estimation formulas for the optimal aggregation parameters under steady-state conditions with a Poisson arrival. In this paper, we propose an adaptive control scheme of statistical data aggregation that minimizes the latency when time variation exists in the arrival rate. Applying the estimation formula of the optimal aggregation number to the proposed scheme, we realized adaptive control of the aggregation number according to the offered traffic. The transient and average characteristics of the proposed scheme with time-variant inputs were clarified by simulation. The results indicate that the proposed scheme achieved stable and nearly theoretically optimal latency, even during an overloaded traffic condition.
Year
DOI
Venue
2018
10.1109/GIIS.2018.8635712
GIIS
Keywords
Field
DocType
Internet of Things,Data aggregation,Logic gates,Adaptive control,Transient analysis,Adaptation models,Estimation
Logic gate,Smart grid,Latency (engineering),Computer science,Automation,Real-time computing,Default gateway,Adaptive control,Poisson distribution,Data aggregator
Conference
ISSN
ISBN
Citations 
2150-329X
978-1-5386-7272-3
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Hideaki Yoshino112.08
Kenko Ota211.40
Takefumi Hiraguri34915.58