Increase energy aware for wireless sensor network using lowpan
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Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Altınbaş Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
There are many networks in remote areas to support all areas and applications. Networks That
allow connectivity covering a range of square kilometers are critical for these remote deployments.
The widely used star topology is not ideal for a rural environment as the coverage is limited by the
central axis positioning which also contributes to being a single point of failure. It is clear that
mesh networks are more attractive in this respect, but scalability has always been an issue for mesh
networks, especially with regard to routing. Saving power very fundamental in remote IoT
deployments, where devices can be left in isolated fields for an extended period of time. In this
thesis we dealt with the steering problem of remote sensors by introducing reinforcement learning
energy-aware routing algorithms. We determined the strength of the RL routing algorithm for
remote sensing networks. This thesis also presents a step-by-step detailed analysis of the RL
routing algorithm to To prove the effectiveness of the algorithm. We model the network operating
in a region bounded by a finite number of randomly distributed nodes within the region in this
algorithm. Hence, we have defined the service area of the target network assuming network
limitations in the model.
Açıklama
Anahtar Kelimeler
Wireless Sensor Network, Energy Aware, LPWAN, IOT, Reinforcement Learning Algorithm
Kaynak
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Al-Sarray, Z. A. S. (2021). Increase energy aware for wireless sensor network using lowpan (Yayınlanmış yüksek lisans tezi). Altınbaş Üniversitesi, Lisansüstü Eğitim Enstitüsü, İstanbul.
