Virtual Private Networks (VPNs) are overlay networks established on top of a public network backbone with the goal of providing a service comparable to Private Networks (PNs). The recently proposed VPN hose-model provides customers with flexible and convenient ways to specify their bandwidth requirements. To meet the specified bandwidth requirements, the Network Service Provider (NSP) must reserve sufficient bandwidth on the data transmission paths between each pair of endpoints in a VPN. In addition, the reliability of a VPN depends on the reliability of the data transmission paths. Italiano et al. proposed an algorithm that finds a set of backup paths for a given VPN (VPN tree) under the single-link failure model [1]. When a link failure is detected on a VPN tree, a backup path corresponding to the failed link can be activated to restore the disconnected VPN tree into a new one, thereby ensuring the reliability of the VPN. However, Italiano's algorithm cannot guarantee that the specified bandwidth requirement of the given VPN under the single-link failure model will be met. To address this issue, we propose a new backup path set selection algorithm called BANGUAD in this paper. In addition, the problem of establishing multiple bandwidth-guaranteed hose-model VPNs under the single-link failure model has not been investigated previously. However in this problem, bandwidth-sharing algorithms have the potential to improve the performance of a provisioning algorithm significantly. Therefore, we also propose a bandwidth sharing algorithm and three provisioning algorithms for establishing multiple bandwidth-guaranteed hose-model VPNs under the single-link failure model. Simulations that compare the performance of the proposed algorithms are reported.

As the current Internet becomes popular in information access, demands for real-time display and playback of continuous media are ever increasing. The applications include real-time audio/video clips embedded in WWW, electronic commerce, and video-on-demand. In this paper, we present a new control protocol R3CP for real-time applications that transmit stored MPEG video stream over a lossy and best-effort based network environment like the Internet. Several control mechanisms are used: a) packet framing based on the meta data; b) adaptive queue-length based rate control scheme; c) data preloading; and d) look-ahead pre-retransmission for lost packet recovery. Different from many adaptive rate control schemes proposed in the past, the proposed flow control is to ensure continuous, periodic playback of video frames by keeping the receiver buffer queue length at a target value to minimize the probability that player finds an empty buffer. Contrary to the widespread belief that "Retransmission of lost packets is unnecessary for real-time applications," we show the effective use of combining look-ahead pre-retransmission control with proper data preloading and adaptive rate control scheme to improve the real-time playback performance. The performance of the proposed protocol is studied via simulation using actual video traces and actual delay traces collected from the Internet. The simulation results show that R3CP can significantly improve frame playback performance especially for transmission paths with poor packet delivery condition.

Disk-zoning technique has been widely adopted to increase disks capacities. As a result of disparity of capacities of inner and outer zones, the data transfer rates of the outer zones of a zoned-disk are higher than the inner zones that post a great challenge for zoned-disk based multimedia playback. In this paper, we study the data placement problem of VBR (variable bit rate) videos on zoned-disks. Our objective is to minimize video server buffer size and simultaneously to maximize disk utilization subject to the zone constraints of disk. We introduce the CRT (constant read time) method that allocates each user a constant time period in every service round to retrieve a variable-sized disk block. The CRT method can be formulated as constrained combinatorial problems that its optimum solution can be obtained by employing dynamic programming. Two heuristics are also explored to reduce time and space complexities. According to experiment results, the heuristic algorithms obtain near optimum solutions with shorter computation time.