Mostakim, MoinTarin, SuraiyaRoy, Anu Pria2017-05-292017-05-2920174/19/2017ID 13201062http://hdl.handle.net/10361/8201Cataloged from PDF version of thesis report.Includes bibliographical references (page 22-23).This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.Peers can share internet by creating hotspot networks. The main driver device needs to decide when and which device it needs to connect and gives more internet to perform the operation. By the help of the Q-learning we will try to make a candidate set of best peers so that it can minimize the internet sharing. Q-learning method not only learns from the network parameters as processing capacity, number of resources in the peers but also learns from their state of congestion. According to the proposed method , the data stored in the P2P network is spread across a large number of nodes as the distribution of data can be random and the desired resources are located more quickly without being forwarded and at the same time the network traffic will be minimized.23 pagesenBRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Q- learningHotspot networkThesis