Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network
المؤلفون المشاركون
Soni, Santosh
Shrivastava, Manish
المصدر
Wireless Communications and Mobile Computing
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-08-16
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
Generally, wireless sensor network is a group of sensor nodes which is used to continuously monitor and record the various physical, environmental, and critical real time application data.
Data traffic received by sink in WSN decreases the energy of nearby sensor nodes as compared to other sensor nodes.
This problem is known as hot spot problem in wireless sensor network.
In this research study, two novel algorithms are proposed based upon reinforcement learning to solve hot spot problem in wireless sensor network.
The first proposed algorithm RLBCA, created cluster heads to reduce the energy consumption and save about 40% of battery power.
In the second proposed algorithm ODMST, mobile sink is used to collect the data from cluster heads as per the demand/request generated from cluster heads.
Here mobile sink is used to keep record of incoming request from cluster heads in a routing table and visits accordingly.
These algorithms did not create the extra overhead on mobile sink and save the energy as well.
Finally, the proposed algorithms are compared with existing algorithms like CLIQUE, TTDD, DBRkM, EPMS, RLLO, and RL-CRC to better prove this research study.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Soni, Santosh& Shrivastava, Manish. 2018. Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network. Wireless Communications and Mobile Computing،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1216238
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Soni, Santosh& Shrivastava, Manish. Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network. Wireless Communications and Mobile Computing No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1216238
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Soni, Santosh& Shrivastava, Manish. Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network. Wireless Communications and Mobile Computing. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1216238
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1216238
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر