Early Burst Drop Prediction Technique in Optical Burst Switching N/W | Evolution to OBS Network System

Sharadchandra Kawale (u. a.)

ISBN 10: 3659621811 / ISBN 13: 9783659621819

Published by LAP LAMBERT Academic Publishing, 2014

About this Item

Early Burst Drop Prediction Technique in Optical Burst Switching N/W | Evolution to OBS Network System | Sharadchandra Kawale (u. a.) | Taschenbuch | 92 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659621819 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 105009188

Bibliographic Details

• Title: Early Burst Drop Prediction Technique in Optical Burst Switching N/W | Evolution to OBS Network System
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2014
• Language: English
• ISBN 10: 3659621811
• ISBN 13: 9783659621819
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 7D millimeters 220 millimeters width by 150 millimeters height by 7 millimeters depth
• Weight: 155 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Wavelength division multiplexing (WDM) optical network has emerged as the transmission technology for the next generation Internet backbone. In WDM networks, the huge bandwidth offered by fiber is managed by splitting it into a number of wavelengths, each acting as an independent communication channel at Gbps data rate. One of the key issue in OBS networks is efficient scheduling. Basically there are two types of scheduling algorithms, horizon scheduling algorithm and void filling scheduling algorithm used for scheduling in OBS network. If we calculate burst drop probability before scheduling then it will help to decrease burst drop ratio. The previous burst drop probability technique is based on the burst size and offset time that implemented on edge node. We are extending this technique which will help to improve efficiency of scheduling algorithms. So this book propose early burst drop prediction technique at core node also that processes control packets of bursts which will allow control packets for scheduling. Simulation result shows that the burst drop ratio is improved by proposed technique.

About the Author

Mr. Sharadchandra KawaleM.E. CSEH.O.D. Department of Computer Science & EngineeringSVERI's COE (Poly.), Pandharpur