Efficient memory management in VOD disk array servers usingPer-Storage-Device buffering

We present a buffering technique that reduces video-on-demand server memory requirements in more than one order of magnitude. This technique, Per-Storage-Device Buffering (PSDB), is based on the allocation of a fixed number of buffers per storage device, as opposed to existing solutions based on per-stream buffering allocation. The combination of this technique with disk array servers is studied in detail, as well as the influence of Variable Bit Streams. We also present an interleaved data placement strategy, Constant Time Length Declustering, that results in optimal performance in the service of VBR streams. PSDB is evaluated by extensive simulation of a disk array server model that incorporates a simulation based admission test.This research was supported in part by the National R&D Program of Spain, Project Number TIC97-0438.Publicad

Efficient memory management in video on demand servers

In this article we present, analyse and evaluate a new memory management technique for video-on-demand servers. Our proposal, Memory Reservation Per Storage Device (MRPSD), relies on the allocation of a fixed, small number of memory buffers per storage device. Selecting adequate scheduling algorithms, information storage strategies and admission control mechanisms, we demonstrate that MRPSD is suited for the deterministic service of variable bit rate streams to intolerant clients. MRPSD allows large memory savings compared to traditional memory management techniques, based on the allocation of a certain amount of memory per client served, without a significant performance penaltyPublicad

Promote-IT: An efficient Real-Time Tertiary-Storage Scheduler

Promote-IT is an efficient heuristic scheduler that provides QoS guarantees for accessing data from tertiary storage. It can deal with a wide variety of requests and jukebox hardware. It provides short response and confirmation times, and makes good use of the jukebox resources. It separates the scheduling and dispatching functionality and effectively uses this separation to dispatch tasks earlier than scheduled, provided that the resource constraints are respected and no task misses its deadline. To prove the efficiency of Promote-IT we implemented alternative schedulers based on different scheduling models and scheduling paradigms. The evaluation shows that Promote-IT performs better than the other heuristic schedulers. Additionally, Promote-IT provides response-times near the optimum in cases where the optimal scheduler can be computed

Cooperative Interval Caching in Clustered Multimedia Servers

In this project, we design a cooperative interval caching (CIC) algorithm for clustered video servers, and evaluate its performance through simulation. The CIC algorithm describes how distributed caches in the cluster cooperate to serve a given request. With CIC, a clustered server can accommodate twice (95%) more number of cached streams than the clustered server without cache cooperation. There are two major processes of CIC to find available cache space for a given request in the cluster: to find the server containing the information about the preceding request of the given request; and to find another server which may have available cache space if the current server turns out not to have enough cache space. The performance study shows that it is better to direct the requests of the same movie to the same server so that a request can always find the information of its preceding request from the same server. The CIC algorithm uses scoreboard mechanism to achieve this goal. The performance results also show that when the current server fails to find cache space for a given request, randomly selecting a server works well to find the next server which may have available cache space. The combination of scoreboard and random selection to find the preceding request information and the next available server outperforms other combinations of different approaches by 86%. With CIC, the cooperative distributed caches can support as many cached streams as one integrated cache does. In some cases, the cooperative distributed caches accommodate more number of cached streams than one integrated cache would do. The CIC algorithm makes every server in the cluster perform identical tasks to eliminate any single point of failure, there by increasing availability of the server cluster. The CIC algorithm also specifies how to smoothly add or remove a server to or from the cluster to provide the server with scalability

Power Management Techniques for Data Centers: A Survey

With growing use of internet and exponential growth in amount of data to be stored and processed (known as 'big data'), the size of data centers has greatly increased. This, however, has resulted in significant increase in the power consumption of the data centers. For this reason, managing power consumption of data centers has become essential. In this paper, we highlight the need of achieving energy efficiency in data centers and survey several recent architectural techniques designed for power management of data centers. We also present a classification of these techniques based on their characteristics. This paper aims to provide insights into the techniques for improving energy efficiency of data centers and encourage the designers to invent novel solutions for managing the large power dissipation of data centers.Comment: Keywords: Data Centers, Power Management, Low-power Design, Energy Efficiency, Green Computing, DVFS, Server Consolidatio

Class Based Admission Control by Complete Partitioning -Video on Demand Server

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.Comment: 12 Pages, IJCN

Performance analysis of server selection schemes for Video on Demand servers

Web Services have gained considerable attention over the last few years. This is due to increase in use of the Internet which results in increased web traffic. Web servers find applications in E-commerce and Video-on-Demand(VoD) systems which have resulted in speedy growth of the web traffic. Therefore the concept of load balancer aimed to distribute the tasks to different Web Servers to reduce response times was introduced. Each request was assigned a Web Server decided by the load balancer in such a way that tasks were uniformly distributed among the available servers. Server selection algorithms are aimed to meet the QoS for interactive VoD.This thesis attempts to analyze the performance of FCFS, Randomized, Genetic algorithms and Heuristics algorithms for selecting server to meet the VoD requirement . Performance of these algorithms have been simulated with parameters like makespan and average resource utilization for different server models. This thesis presents an efficient heuristic called Ga-max-min for distributing the load among different servers. Heuristics like min-min and max-min are also applied to heterogeneous server farms and the result is compared with the proposed heuristic for VoD Servers. Ga-max-min was found to provide lower makespan and higher resource utilization than the genetic algorithm.Extensive simulations have been carried out by the simulator designed using MATLAB R2010a