scholarly journals Adaptive Contention Window Design Using Deep Q-Learning

Author(s):  
Abhishek Kumar ◽  
Gunjan Verma ◽  
Chirag Rao ◽  
Ananthram Swami ◽  
Santiago Segarra
2020 ◽  
Vol 25 (6) ◽  
pp. 803-811
Author(s):  
Nadia Zerguine ◽  
Mohammed Mostefai ◽  
Zibouda Aliouat ◽  
Yacine Slimani

Mobile ad hoc networks (MANETs) consist of self-configured mobile wireless nodes capable of communicating with each other without any fixed infrastructure or centralized administration using the medium radio. Wireless technology is based on standard IEEE.802.11. The IEEE 802.11 Distributed Coordination Function (DCF) MAC layer uses the Binary Exponential Backoff (BEB) algorithm to deal with wireless network collisions. BEB is considered effective in reducing the probability of collisions but at the expense of numerous network performance measures, such as throughput and packets delivery ratio, mainly in high traffic load. Deep Reinforcement Learning (DRL) is a DL technique in which an agent can achieve a goal by interacting with the environment. In this paper, using one of the DRL models, we propose Q-learning (QL) to optimize MAC protocols' performance based on the contention window (CW) in MANETs. The intelligent proposed MISQ takes into account the number of packets to be transmitted and the collisions committed by each station to select the appropriate contention window. The performance of the proposed mechanism is evaluated by using in-depth simulations. The outputs indicate that the intelligent proposal mechanism learns various MANETS environments and optimizes performance over standard MAC protocol. The performance of MISQ is evaluated in various networks with throughput, channel access delay, and packets delivery rate as performance measures.


Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6092
Author(s):  
Zhonghui Pei ◽  
Xiaojun Wang ◽  
Zhen Lei ◽  
Hongjiang Zheng ◽  
Luyao Du ◽  
...  

Beacon messages and emergency messages in vehicular ad hoc networks (VANETs) require a lower delay and higher reliability. The optimal MAC protocol can effectively reduce data collision in VANETs communication, thus minimizing delay and improving reliability. In this paper, we propose a Q-learning MAC protocol based on detecting the number of two-hop neighbors. The number of two-hop neighbors in highway scenarios is calculated with very little overhead using the beacon messages and neighbor locations to reduce the impact of hidden nodes. Vehicle nodes are regarded as agents, using Q-learning and beacon messages to train the near-optimal contention window value of the MAC layer under different vehicle densities to reduce the collision probability of beacon messages. Furthermore, based on the contention window value after training, a multi-hop broadcast protocol combined with contention window adjustment for emergency messages in highway scenarios is proposed to reduce forwarding delay and improve forwarding reliability. We use the trained contention window value and the state information of neighboring vehicles to assign an appropriate forwarding waiting time to the forwarding node. Simulation experiments are conducted to evaluate the proposed MAC protocol and multi-hop broadcast protocol and compare them with other related protocols. The results show that our proposed protocols outperform the other related protocols on several different evaluation metrics.


1984 ◽  
Author(s):  
J. Thomas Murray ◽  
Markku T. Hakkinen ◽  
James D. Mackraz

2018 ◽  
pp. 5-26 ◽  
Author(s):  
Stanislav Darula

Three elements mainly wind, water and sun seemed to determine in ancient ages the basic phenomena of life on Earth. Architectural history documented the importance of sun influence on urban and building construction already in layouts of Mesopotamian and Greek houses. Not only sun radiation but especially daylight played a significant role in the creation of indoor environment. Later, in the 20th century, a search of interaction between human life in buildings and natural conditions were studied considering well­being and energy conscious design recently using computer tools in complex research and more detail interdisciplinary solutions. At the same time the restricted daytime availability of natural light was supplemented by more efficient and continually cheaper artificial lighting of interiors. There are two main approaches to standardize the design and evaluation of indoor visual environment. The first is based on the determination of the minimum requirements respecting human health and visibility needs in all activities while the second emphasizes the behaviour and comfort of occupants in buildings considering year­around natural changes of physical quantities like light, temperature, noise and energy consumption. The new current standardization basis for daylight evaluation and window design criteria stimulate the study of methodology principles that historically were based on the overcast type of sky luminance pattern avoiding yearly availability of sky illuminance levels. New trends to base the daylight standardization on yearly or long­term availability of daylight are using the averages or median sky illuminance levels to characterise local climatological conditions. This paper offers the review and discussion about the principles of the natural light standardization with a short introduction to the history and current state, with a trial to focus on the possible development of lighting engineering and its standards in future.


Sign in / Sign up

Export Citation Format

Share Document