Optimization Methods for Energy Consumption Estimation in Wireless Sensor Networks
The main problems in wireless sensor technologies are the constrained energy resources (e. g., battery capacity, processing consumption), and their long-lasting operational capacity in the environment while collecting and sending data to the central station. So, in the design and development of wire...
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doaj-0986cef890ff4eda81ffff16ac8334032020-11-25T00:13:53ZengSDEWES CentreJournal of Sustainable Development of Energy, Water and Environment Systems1848-92572019-06-017226127410.13044/j.sdewes.d6.024400244Optimization Methods for Energy Consumption Estimation in Wireless Sensor NetworksMare Srbinovska0Marija Cundeva-Blajer1 Department of Electrical Measurement and Materials, Faculty of Electrical Engineering and Information Technologies, Ss Cyril and Methodius University, Rugjer Boskovik 18, PO Box 574, 1000 Skopje, R. Macedonia Department of Electrical Measurement and Materials, Faculty of Electrical Engineering and Information Technologies, Ss Cyril and Methodius University, Rugjer Boskovik 18, PO Box 574, 1000 Skopje, R. Macedonia The main problems in wireless sensor technologies are the constrained energy resources (e. g., battery capacity, processing consumption), and their long-lasting operational capacity in the environment while collecting and sending data to the central station. So, in the design and development of wireless sensor networks, one of the main challenges is to achieve maximal battery life. Real time monitoring by implementation of wireless sensor networks contributes to minimization of potential production risks, emerging mainly from environmental influences and human actions. The main goal in this paper is to obtain minimal energy consumption of wireless sensor nodes while collecting distributed data in environmental parameters monitoring. The communication module and the controller should be in idle state as long as possible when they are not active. Energy consumption changes with the frequency of the transmitted measurement data by the sensors and send/receive configuration of the radio frequency modules. Therefore, all of these parameters should be chosen carefully in order to create an optimal environmental monitoring system. In this contribution the stochastic optimization method-genetic algorithm is used to minimize the energy consumption of the wireless sensor nodes depending on the frequency of the transmitted data and the period of the transmission process. The optimization method is implemented for different scenarios while the frequency of the transmitted data is increasing and the period of transmission of all the active components in a sensor node is increasing. http://www.sdewes.org/jsdewes/pid6.0244 Wireless sensor networksSmart sensor energy consumptionEnergy optimizationGenetic algorithmBattery lifeEnvironmental monitoring. |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mare Srbinovska Marija Cundeva-Blajer |
spellingShingle |
Mare Srbinovska Marija Cundeva-Blajer Optimization Methods for Energy Consumption Estimation in Wireless Sensor Networks Journal of Sustainable Development of Energy, Water and Environment Systems Wireless sensor networks Smart sensor energy consumption Energy optimization Genetic algorithm Battery life Environmental monitoring. |
author_facet |
Mare Srbinovska Marija Cundeva-Blajer |
author_sort |
Mare Srbinovska |
title |
Optimization Methods for Energy Consumption Estimation in Wireless Sensor Networks |
title_short |
Optimization Methods for Energy Consumption Estimation in Wireless Sensor Networks |
title_full |
Optimization Methods for Energy Consumption Estimation in Wireless Sensor Networks |
title_fullStr |
Optimization Methods for Energy Consumption Estimation in Wireless Sensor Networks |
title_full_unstemmed |
Optimization Methods for Energy Consumption Estimation in Wireless Sensor Networks |
title_sort |
optimization methods for energy consumption estimation in wireless sensor networks |
publisher |
SDEWES Centre |
series |
Journal of Sustainable Development of Energy, Water and Environment Systems |
issn |
1848-9257 |
publishDate |
2019-06-01 |
description |
The main problems in wireless sensor technologies are the constrained energy resources (e. g., battery capacity, processing consumption), and their long-lasting operational capacity in the environment while collecting and sending data to the central station. So, in the design and development of wireless sensor networks, one of the main challenges is to achieve maximal battery life. Real time monitoring by implementation of wireless sensor networks contributes to minimization of potential production risks, emerging mainly from environmental influences and human actions. The main goal in this paper is to obtain minimal energy consumption of wireless sensor nodes while collecting distributed data in environmental parameters monitoring. The communication module and the controller should be in idle state as long as possible when they are not active. Energy consumption changes with the frequency of the transmitted measurement data by the sensors and send/receive configuration of the radio frequency modules. Therefore, all of these parameters should be chosen carefully in order to create an optimal environmental monitoring system. In this contribution the stochastic optimization method-genetic algorithm is used to minimize the energy consumption of the wireless sensor nodes depending on the frequency of the transmitted data and the period of the transmission process. The optimization method is implemented for different scenarios while the frequency of the transmitted data is increasing and the period of transmission of all the active components in a sensor node is increasing. |
topic |
Wireless sensor networks Smart sensor energy consumption Energy optimization Genetic algorithm Battery life Environmental monitoring. |
url |
http://www.sdewes.org/jsdewes/pid6.0244
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work_keys_str_mv |
AT maresrbinovska optimizationmethodsforenergyconsumptionestimationinwirelesssensornetworks AT marijacundevablajer optimizationmethodsforenergyconsumptionestimationinwirelesssensornetworks |
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1725392600797544448 |