SEMU: A Framework of Simulation Environment for Wireless Sensor Networks with Co-simulation Model

Author(s):  
Shih-Hsiang Lo ◽  
Jiun-Hung Ding ◽  
Sheng-Je Hung ◽  
Jin-Wei Tang ◽  
Wei-Lun Tsai ◽  
...  
2021 ◽  
Vol 6 (1) ◽  
pp. 1229-1240
Author(s):  
Naeem Ahmed Haq Nawaz ◽  
Musab Bassam Al-Zghoul ◽  
Hamid Raza Malik ◽  
Omar Radhi Aqeel Al-Zabi ◽  
Bilal Radi Ageel Al-Zabi

2017 ◽  
Vol 32 (1) ◽  
pp. 29-40 ◽  
Author(s):  
Ruan Delgado Gomes ◽  
Diego Veras Queiroz ◽  
Iguatemi Eduardo Fonseca ◽  
Marcelo Sampaio Alencar

2010 ◽  
Vol 6 (1) ◽  
pp. 679205 ◽  
Author(s):  
Levente Buttyán ◽  
Péter Schaffer

We introduce PANEL a position-based aggregator node election protocol for wireless sensor networks. The novelty of PANEL with respect to other aggregator node election protocols is that it supports asynchronous sensor network applications where the sensor readings are fetched by the base stations after some delay. In particular, the motivation for the design of PANEL was to support reliable and persistent data storage applications, such as TinyPEDS; see the study by Girao et al. (2007). PANEL ensures load balancing, and it supports intra and intercluster routing allowing sensor-to-aggregator, aggregator-to-aggregator, base station-to-aggregator, and aggregator to-base station communications. We also compare PANEL with HEED; see the study by Younis and Fahmy (2004) in the simulation environment provided by TOSSIM, and show that, on one hand, PANEL creates more cohesive clusters than HEED, and, on the other hand, that PANEL is more energy efficient than HEED.


Author(s):  
A. E. Khaytbaev ◽  
A. M. Eshmuradov

The purpose of the article is to study the possibilities of improving the efficiency of the sensory network management technique, using the neural network method. The presented model of the wireless sensor network takes into account the charging of the environment. The article also tests the hypothesis of the possibility of organizing distributed computing in wireless sensor networks. To achieve this goal, a number of tasks are allocated: review and analysis of existing methods for managing BSS nodes; definition of simulation model components and their properties of neural networks and their features; testing the results of using the developed method. The article explores the major historical insights of the application of the neural network technologies in wireless sensor networks in the following practical fields: engineering, farming, utility communication networks, manufacturing, emergency notification services, oil and gas wells, forest fires prevention equipment systems, etc. The relevant applications for the continuous monitoring of security and safety measures are critically analyzed in the context of the relevancy of specific decisions to be implemented within the system architecture. The study is focused on the modernization of methods of control and management for the wireless sensor networks considering the environmental factors to be allocated using senor systems for data maintenance, including the information on temperature, humidity, motion, radiation, etc. The article contains the relevant and adequate comparative analysis of the updated versions of node control protocols, the components of the simulation model, and the control method based on neural networks to be identified and tested within the practical organizational settings.


Author(s):  
A. Sobeih ◽  
Wei-Peng Chen ◽  
J.C. Hou ◽  
Lu-Chuan Kung ◽  
Ning Li ◽  
...  

2021 ◽  
Author(s):  
László Hajdu ◽  
Balázs Dávid ◽  
Miklós Krész

AbstractBecause of the wide variety of possible application fields and the spread of smart devices, the research of wireless sensor networks has become an increasingly important area in the last decade. During the design of these networks, several important aspects have to be considered, for example the lifetime of the network, expected battery usage, or robustness of the installed system. In this paper a simulation environment is introduced that enables the testing of different information spreading methods on the network and provides suggestions for gateway placements with different objectives.


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