Performance Analysis of Clustering Schemes in MANETs

Vijayalakshmi, J.; Prabu, K.

doi:10.1007/978-3-030-03146-6_92

Cited by 2 publications

(2 citation statements)

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“…The function of the genome of the classification rule is calculated according to ( 6), (7). Introduced mechanisms of "switches" to exclude genes from the rules, which are not essential for classification (8), (9). The classification rule is depicted as follows (10).…”

Section: Discussion Of the Research Results Of The Application Of Genetic Algorithms In The Forecasting Subsystemmentioning

confidence: 99%

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Development of a model of a subsystem for forecasting changes in data transmission routes in special purpose mobile radio networks

Divitskyi

Salnyk

Hol

et al. 2021

EEJET

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This research addressed the issue of improving the quality of service for the control system of mobile radio networks. The analysis of the forecasting sphere concerning the methods of service quality of mobile radio networks for special purposes, in particular, forecasting the time of congestion of data transmission routes is carried out. It is found that these methods are used in wired and computer networks operating at the network and data link levels. The basic parameters of the protocols of the channel and network layers of mobile radio networks are highlighted. Forecasting methods are analyzed: temporal extrapolation, causality, expert, and the main disadvantages are indicated. A model of a control system for mobile radio networks with a forecasting subsystem is shown. The features of mobile radio networks, which form the requirements for routing methods, are described. A lot of requirements have been put forward for the model of a control system for mobile radio networks. The structure of a model of a control system for mobile radio networks with an improved forecasting subsystem is proposed. On the basis of genetic algorithms, the tasks that arise in the process of identification, training and forecasting in the forecasting subsystem are solved. The operation of the processes consists in building a base of rules aimed at identifying significant dependencies in a time series based on the use of a genetic algorithm. It is based on the use of evolutionary principles to find the optimal solution. Application of the proposed model will allow real-time identification and will significantly improve the quality of service for mobile radio networks. It will increase the speed and volume of data processed during training, improve the quality and reliability of predicting changes in data transmission routes

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Section: Discussion Of the Research Results Of The Application Of Genetic Algorithms In The Forecasting Subsystemmentioning

confidence: 99%

“…It is important to ensure the quality of service requirements for users on rough terrain and in the context of military operations. It is also necessary to minimize the influence of the human factor in planning, organizing and maintaining communications [9].…”

Section: Materials and Methods Of Researchmentioning

confidence: 99%