Efficient hierarchical QoS routing in ATM networks

  • Authors:

  • Ben-Jye Chang;Ren-Hung Hwang

  • Affiliations:

  • Department of Computer Science and Information Engineering, National Chung Cheng University, Chia-Yi, Taiwan, ROC;Department of Computer Science and Information Engineering, National Chung Cheng University, Chia-Yi, Taiwan, ROC

  • Venue:
  • Computer Communications
  • Year:
  • 2001

Quantified Score

Hi-index 0.24

Visualization

Abstract

For reducing network information to achieve scalability in large ATM networks, ATM Private Network-to-Network Interface (PNNI) adopts hierarchical routing. Consequently, although routing complexity is significantly reduced, numerous issues in PNNI routing require further study to achieve more efficient, accurate, scalable, and QoS-aware routing. Several methods are adopted herein to achieve efficient, scalable, and QoS-aware ATM PNNI routing. First, an efficient aggregation scheme, referred to as Asymmetric Simple, is proposed. The aggregated routing information includes available bandwidth, delay and cost. Second, two approaches for defining link costs are investigated, namely, the Markov Decision Process (MDP) approach and the Competitive On-Line (COL) routing approach, and these are compared with the Widest Path (WP) approach. Finally, a dynamic update policy, referred to as the dynamic cost-based update (DCU) policy, is proposed to improve the accuracy of the aggregated information and the performance of hierarchical routing, while decreasing the frequency of re-aggregation and information distribution. Simulation results demonstrate that the proposed Asymmetric Simple aggregation scheme yields very good network utilization while significantly reducing the amount of advertised information. Between these two link cost functions, the MDP approach provides a systematic method of defining call admission function and yields better network utilization than the COL approach. The proposed DCU policy also yields an enhanced network utilization while significantly reducing the frequency of re-aggregation and the amount of distributed aggregation information.