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Blocking Probability in OBS Networks

  • T. Venkatesh
  • C. Siva Ram Murthy
Chapter

Abstract

Computing the blocking probability of bursts at the core nodes in an OBS network is important for many reasons. First, it helps to understand the loss process of bursts and provide exact analytical expression for the loss rate of bursts at the core nodes. Second, it helps to give bounds for the loss rate which is an important measure of QoS in OBS network. Finally, it helps to design new loss minimization mechanisms at various places in the network in order to improve the performance of the network at higher layers. Computation of blocking probability in OBS networks is challenging due to the lack of optical buffers at the core nodes and the unacknowledged nature of switching. Contention losses which are different from the traditional losses due to buffer overflow (congestion) lead to an additional complexity in formulating analytical expressions for blocking probability of bursts. In the circuit switching, arriving connection requests are blocked at the source due to lack of bandwidth. In packet switching, packets are buffered at the intermediate nodes if bandwidth is not available. Packets are dropped only when the buffer overflows. Unlike these two switching paradigms, which are analyzed with traditional queueing systems, losses in OBS network occur whenever two or more bursts request the same wavelength for the same duration. These losses are completely random and do not necessarily indicate congestion in the network. To a certain extent such contention is resolved either in the space domain by switching onto an alternate wavelength (wavelength conversion) or in the time domain by delaying the optical burst (using FDLs). When both these techniques cannot resolve the contention for a wavelength, bursts are dropped. The probability of bursts getting dropped due to contention at a node is commonly referred to as the blocking probability or the BLP.

Keywords

Wavelength Conversion Blocking Probability Core Node Wavelength Converter Output Link 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringIndian Institute of TechnologyGuwahatiIndia
  2. 2.Department of Computer Science and EngineeringIndian Institute of TechnologyChennaiIndia

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