In the next generation network (NGN) environment specific consideration is on bandwidth minimization, because this reduces the cost of network. In response to the growing market demand for multimedia traffic transmission, NGN concept has been produced. The next generation network provides multimedia services over high speed networks, which supports DVD quality video on demand. Although it has numerous advantages, more exploration of the large-scale deployment video on demand is still needed. The focus of the research presented in this paper is a class based admission control by the complete partitioning of the video on demand server. In this paper we present analytically and by simulation how the blockage probability of the server significantly affects the on demand video request and the service. We also present how the blockage probability affects the performance of the video on demand server.
Video-on-Demand (VoD) systems are expected to be one of the most important services supported by the next generation of high speed networks, video servers, and distributed multimedia file system. Typically a large number of video files are stored in a set of centralized video servers and played through high-speed communication networks . The geographically distributed clients will be able to submit their request for a video from any place at any time through the network. Due to stringent response time requirements , continuous delivery of a video stream has to be guaranteed by reserving an I/O stream and an isochronous channel needed for the delivery. In this paper we consider the complete partition of the server for efficiently handling the client request. In this work we present the system performance of video on demand server with respect to the blockage probability at the individual VoD servers. Over the last two decades researchers have focused on analyzing the packet loss, packets delay, jitter to find the performance of the different types of network system [ 1 ]. To maximize the utilization of these channels, efficient scheduling techniques have been proposed by Vin and Rangan [18],Ozden et al. [19,20], Freedman and Dewitt [21], Keeton and Katz [22], Oyang et al. [23] just to name a few. These techniques are sometimes referred to as user centered [24,25] in the sense that the channels are allocated among the users. Although this approach simplifies the implementation, dedicating a stream for each viewer will quickly exhaust the network -I/O bandwidth at the server communication ports. In fact the Network -I/O bottleneck has been ! observed in many systems, such as Time Warner cable's Full Service Network project in Orlando , Microsoft's Tiger video Fileserver and so.
Previous research in VoD systems have focused on the disk scheduling, disk stripping, video block placement, admission control at the level of disks and disk groups [2], [3], [4], [5]. Chen et al [6] introduces the concept of distinguishing between high and low priority classes but the resource capacity is partitioned between the two classes. Admission control is enforced on the dedicated partition of server capacity as a separate M/M/C/C queue. Therefore, a cost effective design for the VoD system, needs to evaluate a collection of various VoD system components [7]. In terms of VoD transmission network, the system design must guarantee the required bandwidth for video traffic.This bandwidth must support the VoD service quality needs to meet its packet loss polices. Video content delivery consumes large amounts of bandwidth in the networks, due to its scalability. In addition, system client must comply with the necessary buffer size and video request for the VoD delivery policy [8]. O vector et al. [9] develops a performance evaluation tool for the system design and a user activity model to describe the utilization of the network bandwidth and video server usage. It becomes important to get better performance from the system by allocating the dedicating channel to the user through the fixed ports. With the increase of the population size the load on the server becomes heavy. It is essential to divide the ports into smaller groups and allocated the individual smaller group to particular class of user. This paper is structured as follows: Section 2 introduces the Network architecture of video on demand system which briefly represents the incoming traffic pattern to the video on demand server . Section 3 illustrate the analytic from of the ‘Admission control’ based on the partition of the ports of video server. Section 4 present the parameters description of the simulation environment. Section 5 presents the simulation result with respect to the proposed algorithms . Section 6 and 7 presents conclusion remarks and acknowledgements.
The request comes from the client to the VoD server for the two types of movies one for the popular movies and other for the unpopular movies. The request also is for two types in the VoD Network. The first one request is for initializing or starting the video movie. The other type is the request for interactive service (e.g. stop/pause, jump forward, fast reverse etc) to be performed on the viewed movies. Since each of these request is independent from each other, and arrival requests come from large numbers of client set-up terminals, the arrival process of normal requests as well as of interactive requests to the video server can be modeled as a Poisson distribution with average rates S λ ( for steady session) and I λ ( for interactive session)
respectively. With this assumption, the distribution of the sum of K of independent identically distributed random variables, representing the request inter -arrival times (Which are exponential distributed mutually independent random variables ) is then the Erlang distribution.
A typical VoD architecture consists of three critical subsystems : single or cluster v
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