• Journal of the Korea Society of Computer and Information
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• v.21 no.4
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• pp.17-24
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• 2016

In this paper, we propose a AH LSU(Advanced Hybrid QoS Routing Link State Update) Algorithm that improves the performance of Hybrid LSU(Hybrid QoS Link State State Update) Algorithm with statistical information of flow holding time in network. AH LSU algorithm has had both advantages of LSU message control in periodic QoS routing LSU algorithm and QoS routing performance in adaptive LSU algorithm. It has the mechanism that calculate LSU message transmission priority using the flow of statistical request bandwidth and available bandwidth and include MLMR(Meaningless LSU Message Removal) mechanism. MLMR mechanism can remove the meaningless LSU message generating repeatedly in short time. We have evaluated the performance of the MLMR mechanism, the proposed algorithm and the existing algorithms on MCI simulation network. We use the performance metric as the QoS routing blocking rate and the mean update rate per link, it thus appears that we have verified the performance of this algorithm.

• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.55-62
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• 2014

This paper has proposed Hybrid QoS Routing Link State Update(LSU) Algorithm that has had a both advantage of LSU message control in periodic QoS routing LSU algorithm and QoS routing performance in adaptive LSU algorithm. Hybrid LSU algorithm can adapt the threshold based network traffic information and has the mechanism that calculate LSU message transmission priority using the flow of statistical request bandwidth and available bandwidth and determine the transmission of the message according to update rate per a unit of time. We have evaluated the performance of the proposed algorithm and the existing algorithms on MCI simulation network using the performance metric as the QoS routing blocking rate and the mean update rate per link, it thus appears that we have verified the performance of this algorithm that it can diminish to 10% of the LSU message count.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.75-81
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• 2012

This paper has proposed Message Count Control Mechanism based Link State Update(LSU) Algorithm that has not had a strong influence on the depreciation of QoS routing performance. Most existing LSU algorithms have the limit that cannot control the count of LSU message. Especially, adaptive algorithms have a bad performance when traffic are excessive and fickle. We classify as the importance of LSU message that have a influence on available bandwidth and determine the transmission of the message according to update rate per a unit of time. We have evaluated the performance of the proposed model and the existing algorithms on MCI simulation network using the performance metric as the QoS routing blocking rate and the mean update rate per link, it thus appears that we have verified the performance of this algorithm.

• Journal of the Korea Society for Simulation
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• v.15 no.1
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• pp.27-33
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• 2006

To guarantee QoS (Quality of Service), routers should determine routing paths satisfying service requirements, based on link state information as well as network topology. Link status database (LSD) in routers should be efficiently managed to effectively reflect the current state of all links. However, there is a trade off between the exact reflection of the current link status and its update cost. For exactly reflecting the current link status, each router immediately notifies its neighbors that link state information is changed. This may degrade performance of the router due to the processing of link state update messages. On the other side, if the current link state information is not updated appropriately, a route setup request can be rejected because of the discrepancy between the current link state information and previously updated link state information in LSD. In this paper, we propose a traffic variation based link state update algorithm for adaptively controlling the generation of link state update messages and compare its performance with those of four existing algorithms by intensive simulations.