scholarly journals THE ASSIGNMENT OF TASKS TO THE NODES OF THE IOT DISTRIBUTED SYSTEM BASED ON REINFORCEMENT MACHINE LEARNING

2021 ◽  
Vol 63 (1) ◽  
pp. 27-33
Author(s):  
Maria V. Stepanova ◽  
◽  
Oleg I. Eremin ◽  
Keyword(s):  
Machine Learning ◽  
Reinforcement Learning ◽  
Internet Of Things ◽  
Distributed System ◽  
Task Assignment ◽  
Parallel Systems ◽  
Learning Method ◽  
Adaptive Approach ◽  
Iot Platform

The article describes issues of applying an adaptive approach based on reinforcement learning for assignment of the computing tasks to nodes of distributed Internet of Things (IoT) platform. The IoT platform consists of heterogeneous elements that are computing nodes. Classical approaches, methods, and algorithms for distributed and parallel systems are not suitable for task assignment in IoT systems due to its characteristics. The reinforcement learning method allows you to solve the problem of building a distributed system due to the adaptive formation of a sequence of computational nodes and the corresponding computational tasks. Thus, the article represents a method that makes IoT nodes capable of execution computing tasks, especially, which were previously designed for classical distributed and parallel systems.

scholarly journals System Log Detection Model Based on Conformal Prediction

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 232 ◽  
Author(s):  
Yitong Ren ◽  
Zhaojun Gu ◽  
Zhi Wang ◽  
Zhihong Tian ◽  
Chunbo Liu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Anomaly Detection ◽  
Statistical Learning ◽  
The Internet ◽  
Learning Method ◽  
Log Data ◽  
Detection Model ◽  
Statistical Learning Method ◽  
The Internet Of Things

With the rapid development of the Internet of Things, the combination of the Internet of Things with machine learning, Hadoop and other fields are current development trends. Hadoop Distributed File System (HDFS) is one of the core components of Hadoop, which is used to process files that are divided into data blocks distributed in the cluster. Once the distributed log data are abnormal, it will cause serious losses. When using machine learning algorithms for system log anomaly detection, the output of threshold-based classification models are only normal or abnormal simple predictions. This paper used the statistical learning method of conformity measure to calculate the similarity between test data and past experience. Compared with detection methods based on static threshold, the statistical learning method of the conformity measure can dynamically adapt to the changing log data. By adjusting the maximum fault tolerance, a system administrator can better manage and monitor the system logs. In addition, the computational efficiency of the statistical learning method for conformity measurement was improved. This paper implemented an intranet anomaly detection model based on log analysis, and conducted trial detection on HDFS data sets quickly and efficiently.

Dynamical Resource Allocation in Edge for Trustable Internet-of-Things Systems: A Reinforcement Learning Method

2020 ◽  
Vol 16 (9) ◽  
pp. 6103-6113 ◽  
Author(s):  
Shuiguang Deng ◽  
Zhengzhe Xiang ◽  
Peng Zhao ◽  
Javid Taheri ◽  
Honghao Gao ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Reinforcement Learning ◽  
Internet Of Things ◽  
Learning Method

A Plant Control Technology Using Reinforcement Learning Method with Automatic Reward Adjustment

2009 ◽  
Vol 129 (7) ◽  
pp. 1253-1263
Author(s):  
Toru Eguchi ◽  
Takaaki Sekiai ◽  
Akihiro Yamada ◽  
Satoru Shimizu ◽  
Masayuki Fukai
Keyword(s):  
Reinforcement Learning ◽  
Control Technology ◽  
Learning Method ◽  
Plant Control

An Approach to Optimal Task Assignment in a Distributed System

2004 ◽  
Vol 36 (10) ◽  
pp. 51-55 ◽  
Author(s):  
Rasim Magamed ogly Alguliev ◽  
Ramiz Magamed ogly Aliguliev ◽  
Rashid Kurbanali ogly Alekperov
Keyword(s):  
Distributed System ◽  
Task Assignment

Detecting Abnormal Behavior of an IoT Device in the Network Based on a Traffic Model

Telecom IT ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 50-55
Author(s):  
D. Saharov ◽  
D. Kozlov
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Mobile Networks ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Abnormal Behavior ◽  
Traffic Model ◽  
The Internet ◽  
Wide Spread ◽  
The Internet Of Things

The article deals with the СoAP Protocol that regulates the transmission and reception of information traf-fic by terminal devices in IoT networks. The article describes a model for detecting abnormal traffic in 5G/IoT networks using machine learning algorithms, as well as the main methods for solving this prob-lem. The relevance of the article is due to the wide spread of the Internet of things and the upcoming update of mobile networks to the 5g generation.

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