Authors :
R. Suganya; Dr. Vasantha Kalyani David
Volume/Issue :
Volume 6 - 2021, Issue 11 - November
Google Scholar :
http://bitly.ws/gu88
Scribd :
https://bit.ly/3oaC5jL
Abstract :
Mobile Adhoc Networks (MANETs) commonly
use innovative technologies to improve Quality-of-Service
(QoS) while transporting different data speeds. Due to
variations in the node's proximity, this type of network has
a significant forwarding latency and inefficient data
transmission rates. To combat this challenge, an Extending
Lifespan and QoS-Satisfied Multicast using Multiple
Learned rate (ELQSSM-ML)-based routing protocol was
suggested which reduces the energy usage and allocates the
transmit energy in an adaptive manner. But, the dynamics
of the buffer were not considered, which causes the data
loss and latency. Hence, this article proposes an Extending
Lifespan and Enhanced QSSM-ML (ELEQSSM-ML)-
based routing protocol to decrease the packet loss by
applying an adaptive hop-aware buffer handling
technique. First, the buffer size of all nodes in the network
is partitioned into different segments according to the
number of hops and QoS for multiple classes of packets.
Then, the dimension of each segment is adaptively finetuned based on the traffic load and reliability thresholds.
Here, the reliability thresholds for each class of packet are
optimized by using the Reinforcement Learning (RL)
strategy to defend the packet loss. Further, the simulation
outcomes show that the ELEQSSM-ML-based protocol
achieves superior efficiency in multicast routing compared
to the traditional protocols.
Keywords :
Multi-rate MANET, Multicast routing, ELQSSMML, Buffer handling, Hop count, Reinforcement learning.
Mobile Adhoc Networks (MANETs) commonly
use innovative technologies to improve Quality-of-Service
(QoS) while transporting different data speeds. Due to
variations in the node's proximity, this type of network has
a significant forwarding latency and inefficient data
transmission rates. To combat this challenge, an Extending
Lifespan and QoS-Satisfied Multicast using Multiple
Learned rate (ELQSSM-ML)-based routing protocol was
suggested which reduces the energy usage and allocates the
transmit energy in an adaptive manner. But, the dynamics
of the buffer were not considered, which causes the data
loss and latency. Hence, this article proposes an Extending
Lifespan and Enhanced QSSM-ML (ELEQSSM-ML)-
based routing protocol to decrease the packet loss by
applying an adaptive hop-aware buffer handling
technique. First, the buffer size of all nodes in the network
is partitioned into different segments according to the
number of hops and QoS for multiple classes of packets.
Then, the dimension of each segment is adaptively finetuned based on the traffic load and reliability thresholds.
Here, the reliability thresholds for each class of packet are
optimized by using the Reinforcement Learning (RL)
strategy to defend the packet loss. Further, the simulation
outcomes show that the ELEQSSM-ML-based protocol
achieves superior efficiency in multicast routing compared
to the traditional protocols.
Keywords :
Multi-rate MANET, Multicast routing, ELQSSMML, Buffer handling, Hop count, Reinforcement learning.
