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. ABSTRACTThe 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.

In this paper we propose an adaptive P2P video streaming framework to address the challenges due to bandwidth heterogeneity and peer churn on the Internet. This adaptive streaming framework consists of two major components, source rate adaptation and adaptive overlay topology formation, to maximize the video quality and fully utilize the overall peer upload capacity. In the source rate adaptation, the video server adapts the video source rate automatically based on the local measurement of peers' download rates, so that the P2P network is not overloaded beyond its bandwidth Parts of the results in this paper have been presented in capacity and peers are able to achieve smooth video playback. To combat bandwidth heterogeneity, we propose to construct a desirable link-level homogeneous overlay topology using a Markov chain Monte Carlo method, so that peers achieve an equal per-connection upload/download bandwidth. In this link-level homogeneous network, video flows do not encounter any bottlenecks along the delivery paths, and peers achieve high download rates to ensure smooth video playback. We also design a fully distributed algorithm to implement the dual mechanisms of the adaptive topology formation and the source rate maximization. To evaluate the performance of our streaming framework, we conduct both mathematical analysis and extensive simulations. The simulation results confirm our analysis and show that the proposed distributed algorithm is able to maximize the video playback quality with fast convergence.

In this paper, we consider the fairness issue of BT and tackle the problem with a general framework using proactive topology adaptations. The topology formed possesses a special link-level homogeneity property with each peer having the same capacity per out-degree value. Such property guarantees that each directional link has the same uploading bandwidth. Together with the Tit-for-Tat policy, peers upload and download at the same rate over each connection and therefore achieve fairness.

Peer-to-Peer (P2P) file sharing is the hottest, fastest growing application on the Internet. When designing Gnutella-like applications, the most important consideration is the scalability problem, because P2P systems typically support millions of users online concurrently. Gnutella suffers from poor scaling due to its flooding-based search, resulting in excessive amounts of repeated query messages. Therefore, a good search protocol plays an important role in a system's scalability. However, congestion, due to large query loads from users, definitely impacts on the performance of search protocols, and this consideration has received little attention from the research community. In this paper, we propose a congestionaware search protocol for unstructured P2P networks. Our protocol consists of three partsCongestion-Aware Forwarding, Random Early Stop and Emergency Signaling. The aim of our protocol is to integrate congestion control and object discovery functionality so that the search protocol can achieve good performance under congested networks and flash crowds. We perform extensive simulations to study our proposed protocol. The results show that our protocol can significantly reduce the hit delay while maintaining the high hit rate and also the congestion problems such as query loss and the peer overloading problem can be effectively alleviated.