Back to Search Start Over

Evaluation of the functionality of mobile wireless sensor networks using stochastic reward nets.

Authors :
Asadi, A. Naghash
Azgomi, M. Abdollahi
Entezari-Maleki, R.
Source :
Scientia Iranica. Transaction D, Computer Science & Engineering & Electrical Engineering; Jan/Feb2023, Vol. 30 Issue 1, p91-103, 13p
Publication Year :
2023

Abstract

In this paper, the functionality of Mobile Wireless Sensor Networks (MWSNs) is analytically modeled and evaluated using Stochastic Reward Nets (SRNs). In MWSNs, mobile nodes can move around to collect data from the environment and send them to the sink. These nodes use a limited battery as the power source which can be charged according to environmental conditions. If the battery does not have enough power, the mobile node is disabled and, therefore, it cannot move around to collect/send data. The data collected by the nodes will expire if they are not received by the sink in a timely manner. In order to avoid data expiration, mobile nodes can send their data to other nodes around themselves, but this also increases the power consumption because of further communication. Furthermore, moving faster in the environment, the power consumption of the nodes increases. Therefore, environmental and movement conditions as well as communication between nodes can have a major impact on the functionality of the MWSNs. These challenges are considered in the paper and the proposed models analyze the impact of different conditions on the functionality of MWSNs. The results obtained from the comparison of different scenarios demonstrate that the environmental and movement conditions have a greater impact on system functionality than the communication conditions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10263098
Volume :
30
Issue :
1
Database :
Complementary Index
Journal :
Scientia Iranica. Transaction D, Computer Science & Engineering & Electrical Engineering
Publication Type :
Academic Journal
Accession number :
161998553
Full Text :
https://doi.org/10.24200/sci.2022.58441.5732