A typical user is concerned only with the quality of service of a network on an end-to-end basis. Therefore, how end-to-end requirements are mapped into the local switching node requirements and maximum network utilization is a function of network internal design. In this paper, we address the problem of QOS allocation. We derived an optimal QOS allocation policy and decided the maximum utilization bound in a deterministic traffic model. We adopted the worst case delay bound as the end-to-end and local QOS requirement. With (σ, ρ) traffic model, we derived a formula for delay bound and the number of connections. We found that with the delay bound as the QOS metric, there is a significant difference in the performance of allocation policies. We also developed an evaluation strategy to analyze allocation policies. The numerical results for two simple network topologies: tandem network model and uneven traffic load model, compare the equal allocation policy with the optimal allocation policy and show the correctness and efficiency of QOS allocation policy.

To implement the PGPS packet scheduling algorithm in high speed networks is more difficult since it is based on real time simulation of an equivalent fluid-model system leading to a higher implementation time complexity. A modified approach to PGPS is the SCFQ scheme. This scheme is easy to implement, but has an increasing end-to-end delay bound. The VC packet scheduling algorithm provides the same end-to-end delay bound as PGPS does, but has the disadvantage of unfairness. As SCFQ, SFQ is much easier to implement than PGPS and achieves the same fairness, but has a higher end-to-end delay bound than PGPS. We propose a new packet scheduling algorithm, called Minimum Starting-tag Fair Queueing (MSFQ), which assigns the virtual time to be the minimum starting tag over all backlogged connections. MSFQ is much easier to implement than PGPS and provides the same end-to-end delay bound for each connection and fairness as PGPS. In this paper, we will show the end-to-end delay bound and fairness of MSFQ and compare 5 rate-based packet scheduling algorithms including PGPS, VC, SCFQ, SFQ, and MSFQ focusing on end-to-end delay bound, fairness, and implementation time complexity.