Divyesh Jadav

Designing and implementing high-performance media-on-demand servers

Of the many potential interactive multimedia applications, media-on-demand (MOD) has generated the most excitement. MOD lets users receive services from remote resources interactively, at their own pace. The quintessential example of these services is video-on-demand. Consumers are able to order and view movies of their choice, at their convenience, from their home, using a remote control. This scenario, though achievable, remains just a concept. Although recent advances in networking, processing, and storage have brought this concept closer to reality, large-scale deployment of MOD services remains a complex problem. We believe that using high-performance computers as MOD servers offers the best solution. However, implementing these servers poses its own challenges. The article examines such a servers requirements and implementation problems. >

Design and evaluation of data access strategies in a high performance multimedia-on-demand server

One of the key components of a multi user multimedia on demand system is the data server. Digitization of traditionally analog data such as video and audio, and the feasibility of obtaining network bandwidths above the gigabit per second range are two important advances that have made possible the realization, in the near future, of interactive distributed multimedia systems. Secondary-to-main memory I/O technology has not kept pace with advances in networking, main memory and CPU processing power. Consequently, the performance of the server has a direct bearing on the overall performance of such a system. We develop a model for the architecture of a server for such a system. Parallelism of data retrieval is achieved by striping the data across multiple disks. The performance of any server ultimately depends on the data access patterns. Two modifications of the basic retrieval algorithm are presented to exploit data access patterns in order to improve system throughput and response time. A complementary information caching optimization is discussed. Finally, we present performance results of these algorithms on the IBM SP1 and Intel Paragon parallel computers.

Techniques for Scheduling I/O in a High Performance Multimedia-on-Demand Server

One of the key components of a multiuser multimedia-on-demand system is the data server. Digitalization of traditionally analog data such as video and audio, and the feasibility of obtaining network bandwidths above the gigabit-per-second range, are two important advances that have made possible the realization, in the near future, of interactive distributed multimedia systems. Secondary-to-main memory I/O technology has not kept pace with advances in networking, main memory, and CPU processing power. Consequently, the performance of the server has a direct bearing on the overall performance of such a system. In this paper, we present a highperformance solution to the I/O retrieval problem in a distributed multimedia system. We develop a model for the architecture of a server for such a system. Parallelism of data retrieval is achieved by striping the data across multiple disks. We present the algorithms for server operation when servicing a constant number of streams, as well as the admission control policy for accepting requests for new streams. The performance of any server ultimately depends on the data access patterns. Two modifications of the basic retrieval algorithm are presented to exploit data access patterns in order to improve system throughput and response time. Finally, we present preliminary performance results of these algorithms on the IBM SP1 and Intel Paragon parallel computers.

An evaluation of design trade-offs in a high-performance, media-on-demand server

Abstract.We present a high-performance solution to the I/O retrieval problem in a distributed multimedia system. Parallelism of data retrieval is achieved by striping the data across multiple disks. We identify the components that contribute to media data-retrieval delay. The variable delays among these have a great bearing on the server throughput under varying load conditions. We present a buffering scheme to minimize these variations. We have implemented our model on the Intel Paragon parallel computer. The results of component-wise instrumentation of the server operation are presented and analyzed. Experimental results that demonstrate the efficacy of the buffering scheme are presented. Based on our experiments, a dynamic admission-control policy that takes server workloads into account is proposed.n

Caching of large database objects in Web servers

The popularity of the World Wide Web has been increasing at an exponential rate of late. As such growth was unanticipated, the infrastructure is increasingly experiencing problems. The combination of increased network bandwidth demand and overloaded servers results in increased data retrieval latency for the end-user. Caching data at appropriate points in the Web helps alleviate this problem. Almost all previous and existing Web servers use a flat file approach to store data, with use of database management systems (DBMSs) rudimentary, if extant at all. Storing pages in a file system may result in faster retrieval, but storing them in a DBMS gives the user greater administrative control. The use of a DBMS in a Web server, and the concomitant implication of frequently changing data, complicates the caching problem an Web-based applications. The Illustra Object Relational DBMS provides a flexible and user-friendly environment for building Web applications where all the server data is stored in the DBMS. The authors develop a caching scheme for large objects in the Web DataBlade module of the Illustra ORDBMS. Implementation details and preliminary performance results are presented.

Design and evaluation of data storage and retrieval strategies in a distributed memory continuous media server

High-performance servers and high-speed networks will form the backbone of the infrastructure required for distributed multimedia information systems. Given that the goal of such a server is to support hundreds of interactive data streams simultaneously, various tradeoffs are possible with respect to the storage of data on secondary memory and its retrieval In this paper, we identify and evaluate these tradeoffs. We evaluate the effect of varying the stripe factor and also the performance of batched retrieval of disk-resident data. We develop a methodology to predict the stream capacity of such a server. The evaluation is done for both uniform and skewed access patterns. Experimental results on the Intel Paragon computer are presented.

Techniques for increasing the stream capacity of a multimedia server

A server for an interactive distributed multimedia system may require thousands of gigabytes of storage space and high I/O bandwidth. In order to maximize system utilization, and thus minimize cost, the load must be balanced among the servers disks, interconnection network and scheduler. Many algorithms for maximizing retrieval capacity from the storage system have been proposed. This paper presents techniques for improving server capacity by assigning media requests to the nodes of a server so as to balance the load on the interconnection network and the scheduling nodes. Five policies for request assignment are developed. The performance of these policies on a server model developed earlier is presented.

Batching and dynamic allocation techniques for increasing the stream capacity of an on-demand media server

A server for an interactive distributed multimedia system may require thousands of gigabytes of storage space and high I/O bandwidth. In order to maximize system utilization, and thus minimize cost, the load must be balanced among the servers disks, interconnection network and scheduler. Many algorithms for maximizing retrieval capacity from the storage system have been proposed. The paper presents techniques for improving server capacity by assigning media requests to the nodes of a server so as to balance the load on the interconnection network and the scheduling nodes. Five policies for request assignment are developed. The performance of these policies on an implementation of a server model developed earlier is presented.

Dynamic allocation and replication techniques for increasing the stream capacity of a media server

High performance servers and high speed networks will form the backbone of the infrastructure required for distributed multimedia information systems. A server for an interactive distributed multimedia system may require thousands of gigabytes of storage space and high I/O bandwidth. In order to maximize system utilization, and thus minimize cost, it is essential that the load be balanced among each of the servers components vis. the disks, the interconnection network and the scheduler. Many algorithms for maximizing retrieval capacity from the storage system have been proposed in the literature. This paper presents techniques for improving server capacity by assigning media requests to the noes of a server so as to balance the load on the interconnection network and the scheduling nodes. Five policies for request assignment, round robin, minimum link allocation, minimum contention allocation, weighted minimum link allocation and weighted minimum contention allocation are developed. We also consider the issue of file replication, and develop two schemes for storing the replicas. The performance of these policies on a server model developed earlier is presented.