Localised QoS routing is a relatively new, alternative and viable approach to solve the problems of traditional QoS routing algorithms which use global state information resulting in the imposition of a large communication overhead and route flapping. They make use of a localised view of the network QoS state in source nodes to select paths and route flows to destination nodes. Proportional Sticky Routing (PSR) and Credit Based Routing (CBR) have been proposed as localised QoS routing schemes and these can offer comparable performances. However, since network state information for a specific path is only updated when the path is used, PSR and CBR operate with decision criteria that are often stale for paths that are used infrequently. The aim of this thesis is to focus on localised QoS routing and contribute to enhancing the scalability of QoS routing algorithms. In this thesis we have developed three new localised QoS routing schemes which are called Score Based QoS Routing (SBR), Bandwidth Based QoS Routing (BBR) and Delay Based Routing (DBR). In some of these schemes, the path setup procedure is distributed and uses the current network state to make decisions thus avoiding problems of staleness. The methods also avoid any complicated calculations. Both SBR and BBR use bandwidth as the QoS metric and mean delay is used as the QoS metric in DBR. Extensive simulations are applied to compare the performance of our proposed algorithms with CBR and the global Dijkstra's algorithm for different update intervals of link state, different network topologies and using different flow arrival distributions under a wide range of traffic loads. It is demonstrated by simulation that the three proposed algorithms offer a superior performance under comparable conditions to the other localised and global algorithms.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:535429 |
| Date | January 2010 |
| Creators | Li, Ding |
| Contributors | Woodward, Mike E. |
| Publisher | University of Bradford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10454/4912 |
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