Early Burst Drop Prediction Technique in Optical Burst Switching N/W » książka
Early Burst Drop Prediction Technique in Optical Burst Switching N/W
ISBN-13: 9783659621819 / Angielski / Miękka / 2014 / 92 str.
Early Burst Drop Prediction Technique in Optical Burst Switching N/W
ISBN-13: 9783659621819 / Angielski / Miękka / 2014 / 92 str.
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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.
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.
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