Campus Access Only
All rights reserved. This publication is intended for use solely by faculty, students, and staff of Nova Southeastern University. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, now known or later developed, including but not limited to photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the author or the publisher.
Date of Award
Dissertation - NSU Access Only
Doctor of Philosophy in Computer Information Systems (DCIS)
Graduate School of Computer and Information Sciences
Network Optimization, network performance, peer selection strategy, Peer-to-peer Networks
The download duration of peer-to-peer overlay networks is highly dependent upon the client's selection of candidate node-servers and the algorithms used in that process. Recent findings suggest that as node-server network capacity increases the deviation from the average total download time can vary as much as 300 percent between selection algorithms. This work investigated the current selection algorithms based upon chunk size, parallel connections, permanent connection, and time based switching.
The time based switching algorithm is a variation of the chunk based algorithm. Time based switching enables a client to randomly select a new node-server regardless of connection speed at predetermined time slots. Simulations indicate a 41% percent decrease in download time when compared to chunk based switching.
The effects of inserting chokepoints in the time based switching algorithm were investigated. This work investigated improving a client's download performance by preemptively releasing a client from a poor performing node-server. To achieve this, the client will gather a peer-to-peer network overlay capacity from a global catalog. This information will be used to seed a client choke algorithm. Clients will then be able to continually update a local capacity average based upon past download sessions. This local average will be used to make a comparison between the current download session and the previously calculated average. A margin has been introduced to allow the client to vary from the average calculated capacity. The client will perform comparisons against chokepoints and make performance decisions to depart a node-server that does not meet minimum capacity standards.
Experimental results in this research demonstrated the effectiveness of applying a choking algorithm to improve upon client download duration as well as increasing the accuracy of download duration estimates. In the single downloader scenario, the choke based algorithm improved performance up to 44% in extreme congestion and a more modest 13% under normal conditions. The multiple client scenarios yielded on average a 1% decrease in client download duration along with a 44% increase download homogeneity. Furthermore, the results indicate that a client based choking algorithm can decrease overall peer-to-peer network congestion buy improving upon client selection of node-servers.
Michael Richard Lehrfeld. 2010. Peer selection Algorithm in Stochastic Content Delivery Networks to Reduce File Download Time. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, Graduate School of Computer and Information Sciences. (211)