TY  - JOUR
AU  - Moqimi, Ehsan 
AU  - Najafi, Amir 
AU  - Ajami, Mojtaba 
PY  - 2020
TI  - An Enhanced Dynamic Source Routing Algorithm for the Mobile Ad-Hoc Network using Reinforcement learning under the COVID-19 Conditions
JF  - Journal of Computer Science
VL  - 16
IS  - 10
DO  - 10.3844/jcssp.2020.1477.1490
UR  - https://thescipub.com/abstract/jcssp.2020.1477.1490
AB  - Today, the use of computer networks is evident in all walks of life, including mobile phones, vehicles, personal computers, the workplace and more. Creating and operating networks between each of the above-mentioned devices require good infrastructure to be able to communicate between these devices. To solve this problem, there were networks called ad-hoc networks, which were able to network with each other without the need for specific infrastructure and only through direct and wireless communication between the equipment. But how to make the right connections in these types of networks, as well as high-speed communication for devices, are also challenges for researchers. In this study, we try to implement the communication between these devices by the DSR routing algorithm and, using the Q learning technique of the reinforced learning algorithm, we enhance it to respond to QOS in Ad-Hoc mobile networks compared to previous solutions. In addition to what has been improved in this article. In the following articles, we will try to improve the discussion of communication security using this method and also apply this method to routing VANETs networks.