With network components increasingly reliable, routing is playing an ever greater role in determining network reliability. This has spurred much activity in improving routing stability and reaction to failures and rekindled interest in centralized routing solutions, at least within a single routing domain. Centralizing decisions eliminates uncertainty and many inconsistencies and offers added flexibility in computing routes that meet different criteria. However, it also introduces new challenges, especially in reacting to failures where centralization can increase latency. This paper leverages the flexibility afforded by centralized routing to address these challenges. Specifically, we explore when and how standby backup forwarding options can be activated while waiting for an update from the centralized server after the failure of an individual component (link or node). We provide analytical insight into the feasibility of such backups as a function of network structure and quantify their computational complexity. We also develop an efficient heuristic reconciling protectability and performance, and demonstrate its effectiveness in a broad range of scenarios. The results should facilitate deployments of centralized routing solutions.

With network components increasingly reliable, routing is playing an ever greater role in determining network reliability. This has spurred much activity in improving routing stability and reaction to failures, and rekindled interest in centralized routing solutions, at least within a single routing domain. Centralizing decisions eliminates uncertainty and many inconsistencies, and offers added flexibility in computing routes that meet different criteria. However, it also introduces new challenges; especially in reacting to failures where centralization can increase latency. This paper leverages the flexibility afforded by centralized routing to address these challenges. Specifically, we explore when and how standby backup forwarding options can be activated, while waiting for an update from the centralized server after the failure of an individual component (link or node). We provide analytical insight into the feasibility of such backups as a function of network structure, and quantify their computational complexity. We also develop an efficient heuristic reconciling protectability and performance, and demonstrate its effectiveness in a broad range of scenarios. The results should facilitate deployments of centralized routing solutions.

Modern networks face the challenging task of handling increasingly diverse traffic that is displaying a growing intolerance to disruptions. This has given rise to many initiatives, and in this paper we focus on multiple topology routing as the primary vehicle for meeting those demands. Specifically, we seek routing solutions capable of not just accommodating different performance goals, but also preserving them in the presence of disruptions. The main challenge is computational, i.e., to identify among the enormous number of possible routing solutions the one that yields the best compromise between performance and robustness. This is where our principal contribution lies, as we expand the definition of critical links - a key concept in improving the efficiency of routing computation - and develop a precise methodology to efficiently converge on those solutions. Using this new methodology, we demonstrate that one can compute routing solutions that are both flexible in accommodating different performance requirements and robust in maintaining them in the presence of failures and traffic fluctuations.

While the overall bandwidth of peer-to-peer live video streaming system scales automatically as peers collectively contribute the bandwidth, each peer also demands to download at the specified video playback rate so as to play the video smoothly. Therefore, a fundamental problem arisen is how to balance the bandwidth supply and demand in the peer-to-peer system to enjoy peers with the best video quality. To address this problem, we propose a fully distributed peer-to-peer video streaming framework which automatically adapts the network towards full bandwidth utilization. Our design possesses two unique features. First, a speciallink-level homogenousoverlay network is formed in which all the overlay links approach to have an identical bandwidth value. With such a feature, video flowing through the overlay links will not encounter any bottlenecks, and peers can thus achieve the guaranteed downloading rates. Second, based on the peer downloading rate observed locally at the streaming server, the server can adaptively adjust the video playback rate so that peers can achieve the best video quality with full bandwidth utilization. The effectiveness of our framework is verified through extensive simulations.

Modern networks face the daunting task of handling increasingly diverse traffic that is displaying a growing intolerance to disruptions. This has given rise to many initiatives, and in this paper we focus on multiple topology routing as the primary vehicle for meeting those demands. Specifically, we seek routing solutions capable of not just accommodating different performance goals, but also preserving them in the presence of disruptions. The main challenge is computational, i.e., to identify among the enormous number of possible routing solutions the one that yields the best compromise between performance and robustness. This is where our principal contribution lies, as we expand the definition of critical links -- a key concept in improving the efficiency of routing computation -- and develop a precise methodology to efficiently converge on those solutions. Using this new methodology, we demonstrate that one can compute routing solutions that are both flexible in accommodating different performance requirements and robust in maintaining them in the presence of failures and traffic fluctuations.

The convergence on IP of a wide variety of traffic types has strengthened the need for service differentiation. Service differentiation relies on two equally important components: (i) resource allocation, i.e., what resources does a given service class have access to; and (ii) contention resolution, i.e., how is access to shared resources arbitrated between services classes. The latter has been well studied with numerous mechanisms, e.g., scheduling and buffer management, supporting it in modern routers. In contrast, relatively few studies exist on the former, and in particular on the impact of routing that determines the resources a given service class is assigned to. This is the focus of the paper, which seeks to investigate how routing influences a network's ability to efficiently support different service classes. Of particular interest is the extent to which the ability to route service classes separately is beneficial. This question is explored for a base configuration involving two classes with either similar or entirely different service objectives (cost functions). The paper's contributions are in demonstrating and quantifying the benefits that the added flexibility of different (dual) routing affords, and in developing an efficient heuristic for computing jointly optimal routing solutions. The former can motivate the deployment of newly standardized multi-topology routing (MTR) functionality. The latter is a key enabler for the effective use of such capability.

When constructing an unstructured P2P topology, one should consider the application running on top of it in order to achieve a good performance for the whole P2P system. It is not enough only to consider the "topology" objective when forming an overlay such as minimizing a P2P network diameter because it does not achieve a good performance for the whole P2P system. For example, minimizing a P2P network diameter may overload some peers under a flooding search application because of their excess connections. Therefore, one should consider the behavior of the application on top of the topology such that the topology can adapt itself in order to benefit the application. To fulfil this objective, we propose an application-aware topology formation algorithm which can be "tuned" so as to achieve load-balancing for a spectrum of P2P applications. Furthermore, we provide a very detailed analytical model to understand the behavior of our algorithm under any heterogeneous environment. The analytical results are validated by the simulations.