Optimal Control by the Queue with Rate and Quality of Service Depending on the Amount of Harvested Energy as a Model of the Node of Wireless Sensor Network

A queueing model with energy harvesting and multi-threshold control by service regimes is analysed. The available service regimes are characterized by the different service rate, requirements to the number of energy units for a request service and the probability of error occurrence during service. Error accounting is vital for adequate modelling wireless networks due to existence of an interference in a transmission thread. The increase of the number of energy units for service of a request implies an opportunity to send a stronger signal what implies the higher transmission rate and a lower probability of error occurrence during transmission. Error occurrence causes the repeated transmission and, therefore, consumption of more energy. Under the fixed parameters of the control strategy, the system dynamics is described by a continuous-time six-dimensional Markov chain. This allows to compute the steady-state distribution of the system states and, then, formulate and solve optimization problems. Numerical results are presented. © Springer Nature Switzerland AG 2019.

Authors
Dudin A. 1, 2 , Kim C.3 , Dudin S. 1, 2
Language
English
Pages
165-178
Status
Published
Volume
11965 LNCS
Year
2019
Organizations
  • 1 Department of Applied Mathematics and Computer Science, Belarusian State University, Minsk, 220030, Belarus
  • 2 Peoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation
  • 3 Sangji University, Wonju, Kangwon 26339, South Korea
Keywords
Energy harvesting; Optimization; Queueing system; Reliability; Service rate control
Date of creation
10.02.2020
Date of change
25.05.2021
Short link
https://repository.rudn.ru/en/records/article/record/56422/
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Pham V.D., Hoang T., Kirichek R., Makolkina M., Koucheryavy A.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 11965 LNCS. 2019. P. 495-507