Coverage Providing in Directional Sensor Networks through Learning Algorithms (Learning Automata)

被引:0
作者
Rezaeiye, Payam Porkar [1 ]
Sadegh, Elahe Karbalayi [2 ]
Rezaeiyeh, Pasha Porkar [3 ]
机构
[1] Islamic Azad Univ, Damavand Branch, Dept Comp, Damavand, Iran
[2] Islamic Azad Univ, Pardis Branch, Young Researchers & Elite Club, Pardis, Iran
[3] Islamic Azad Univ, Elect Branch, Young Researchers & Elite Club, Tehran, Iran
来源
AMAZONIA INVESTIGA | 2018年 / 7卷 / 14期
关键词
Directed Wireless Sensor Network; Increased coverage; improved energy consumption; machine learning; learning automata;
D O I
暂无
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
Today, wireless sensor networks due to application development are widely used. There are significant issues in these networks; they can be more effective if they would be fixed. One of these problems is the low coverage of these networks due to their low power. If coverage increases only by increasing the power of sending and receiving power, it can increase network consumption as a catastrophic disaster, while the lack of energy is one of the most important constraints on these networks. To do this, the antenna coverage is oriented in some sensor networks to cover the most important places. This method tries to improves the efficiency and coverage of directional sensor networks by providing a mechanism based on the learning algorithm of the machine called learning automata. Results show this method outperform the before methods at least 20%.
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页码:240 / 256
页数:17
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