Network level performance of differentiated services (diffserv) networks

The Differentiated Services (DiffServ) architecture is a promising means of providing Quality of Service (QoS) in Internet. In DiffServ networks, three service classes, or Per-hop Behaviors (PHBs), have been defined: Expedited Forwarding (EF), Assured Forwarding (AF) and Best Effort (BE). In this dissertation, the performance of DiffServ networks at the network level, such as end-to-end QoS, network stability, and fairness of bandwidth allocation over the entire network have been extensively investigated. It has been shown in literature that the end-to-end delay of EF traffic can go to infinity even in an over-provisioned network. In this dissertation, a simple scalable aggregate scheduling scheme, called Youngest Serve First (YSF) algorithm is proposed. YSF is not only able to guarantee finite end-to-end delay, but also to keep a low scheduling complexity. With respect to the Best Effort traffic, Random Exponential Marking (REM), an existing AQM scheme is studied under a new continuous time model, and its local stable condition is presented. Next, a novel virtual queue and rate based AQM scheme (VQR) is proposed, and its local stability condition has been presented. Then, a new AQM framework, Edge-based AQM (EAQM) is proposed. EAQM is easier to implement, and it achieves similar or better performance than traditional AQM schemes. With respect to the Assured Forwarding, a network-assist packet marking (NPM) scheme has been proposed. It has been demonstrated that NPM can fairly distribute bandwidth among AF aggregates based on their Committed Information Rates (CIRs) in both single and multiple bottleneck link networks

Quality-of-service provisioning in high speed networks : routing perspectives

The continuous growth in both commercial and public network traffic with various quality-of-service (QoS) requirements is calling for better service than the current Internet\u27s best effort mechanism. One of the challenging issues is to select feasible paths that satisfy the different requirements of various applications. This problem is known as QoS routing. In general, two issues are related to QoS routing: state distribution and routing strategy. Routing strategy is used to find a feasible path that meets the QoS requirements. State distribution addresses the issue of exchanging the state information throughout the network, and can be further divided into two sub-problems: when to update and how to disseminate the state information. In this dissertation, the issue of when to update link state information from the perspective of information theory is addressed. Based on the rate-distortion analysis, an efficient scheme, which outperforms the state of the art in terms of both protocol overhead and accuracy of link state information, is presented. Second, a reliable scheme is proposed so that, when a link is broken, link state information is still reachable to all network nodes as long as the network is connected. Meanwhile, the protocol overhead is low enough to be implemented in real networks. Third, QoS routing is NP-complete. Hence, tackling this problem requires heuristics. A common approach is to convert this problem into a shortest path or k-shortest path problem and solve it by using existing algorithms such as Bellman-Ford and Dijkstra algorithms. However, this approach suffers from either high computational complexity or low success ratio in finding the feasible paths. Hence, a new problem, All Hops k-shortest Path (AHKP), is introduced and investigated. Based on the solution to AHKP, an efficient self-adaptive routing algorithm is presented, which can guarantee in finding feasible paths with fairly low average computational complexity. One of its most distinguished properties is its progressive property, which is very useful in practice: it can self-adaptively minimize its computational complexity without sacrificing its performance. In addition, routing without considering the staleness of link state information may generate a significant percentage of false routing. Our proposed routing algorithm is capable of minimizing the impact of stale link state information without stochastic link state knowledge. Fourth, the computational complexities of existing s-approximation algorithms are linearly proportional to the adopted linear scaling factors. Therefore, two efficient algorithms are proposed for finding the optimal (the smallest) linear scaling factor such that the computational complexities are reduced. Finally, an efficient algorithm is proposed for finding the least hop(s) multiple additive constrained path for the purpose of saving network resources