Popularity-based assignment of movies to storage devices in a video-on-demand system

Little, Thomas D. C.; Venkatesh, Dinesh

doi:10.1007/bf01225245

Cited by 107 publications

(61 citation statements)

References 13 publications

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“…In this scheme, the average time between successive channel allocation is given by , and hence (by Little's formula) (9) In a local server, the precached data (of average amount of minutes) is flushed at the end of minutes if no request arrives within that time (which occurs with probability ) and the stream is not started by the server (which occurs with probability ). Since the two events are independent, the probability that the precached data is flushed is given by (10) Therefore, the average buffer size used in the local server is given by (11)…”

Section: Subject To Formentioning

confidence: 99%

“…While the paper studies the symmetric case in which request rates across the servers at a given tree level are the same, we make no such assumption here. Lie et al [9] and Little et al [10] consider a video system in which video files can be replicated in order to reduce user loss rate. All the work above treat a video file as a single entity, and hence a movie is either completely stored in a local server or not at all.…”

Section: Previous Workmentioning

confidence: 99%

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Distributed servers architecture for networked video services

Chan

Tobagi

2001

IEEE/ACM Trans. Networking

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Abstract-In an on-demand video system, the video repository generally has limited streaming capacities and may be far from the users. In order to achieve higher user capacity and lower network transmission cost, distributed servers architecture can be used, in which multiple local servers are placed close to user pools and, according to their local demands, dynamically cache the contents streamed from the repository. We study in this paper a number of caching schemes as applied in the local servers depending on whether the repository is able to multicast movie contents to the local servers or not, and whether the local servers can exchange their cached contents among themselves or not. Our caching schemes keep a circular buffer of data for the movie requested, and hence movies are partially cached. By adjusting the size of the buffer, such caching is able to achieve better tradeoff between network channels and local storage as compared to the traditional caching in which a movie is treated as an entity. For each caching scheme, we study the tradeoff between the local storage and the network channels, and address how the total cost of the system can be minimized by appropriately sizing the buffer. As compared to a number of traditional operations (request batching and multicasting, true-VOD, etc.), we show that distributed servers architecture is able to achieve much lower system cost to offer on-demand video services.Index Terms-Caching schemes, distributed servers architecture, network channels and local storage tradeoff, unicast and multicast, video-on-demand.

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Section: Subject To Formentioning

confidence: 99%

Section: Previous Workmentioning

confidence: 99%

Distributed servers architecture for networked video services

Chan

Tobagi

2001

IEEE/ACM Trans. Networking

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“…In other words, the relative popularities of different quality points for the same media object do not change. This assumption is found to be reasonable in many systems [12,13]. We understand that a solution for more general situation is also meaningful and we leave it as future work.…”

Section: Dynamic Data Replicationmentioning

confidence: 99%

“…In [4], specification of quality parameters in multimedia databases is discussed. The traditional data replication problem has been studied extensively in the context of web [10,11], distributed databases [8], and multimedia systems [12,13]. The web caching and replication problem aims at higher availability of data and load balancing at the web servers.…”

Section: Related Workmentioning

confidence: 99%

Quality-Aware Replication of Multimedia Data

Yan

Prabhakar

2005

Lecture Notes in Computer Science

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Abstract. In contrast to alpha-numerical data, multimedia data can have a wide range of quality parameters such as spatial and temporal resolution, and compression format. Users can request data with a specific quality requirement due to the needs of their applications, or the limitations of their resources. On-the-fly conversion of multimedia data (such as video transcoding) is very CPU intensive and can limit the level of concurrent access supported by the database. Storing all possible replicas, on the other hand, requires unacceptable increases in storage requirements. Although replication has been well studied, to the best of our knowledge, the problem of multiple-quality replication has not been addressed. In this paper we address the problem of multiple-quality replica selection subject to an overall storage constraint.We establish that the problem is NP-hard and provide heuristic solutions under a soft quality system model where users are willing to negotiate their quality needs. An important optimization goal under such a model is to minimize utility loss. We propose a powerful greedy algorithm to solve this optimization problem. Extensive simulations show that our algorithm finds near-optimal solutions. The algorithm is flexible in that it can be extended to deal with replica selection for multiple media objects and changes of query pattern. We also discuss an extended version of the algorithm with potentially better performance.

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“…One approach is the modeling of single video streams as they are accessed and played.This is generally done in order to understand how the operation of a single machine or cluster of machines can be optimized. Little and Venkatesh take this approach in [10]with the goal of optimizing disk I/O operations in a single system. Their approach is to build an analytical model for access probabilities based on the work by Ramarao and Ramamoorthy [12].…”

Section: Related Workmentioning

confidence: 99%

Life-Cycle Considerations for Wide-Area Distribution of Multimedia Data

Griwodz

Steinmetz²

1999

High-Performance Networks for Multimedia Applications

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Abstract:Various applications for world-wide multimedia object distribution arise currently as more and more companies integrate streamed continuous media elements in their web pages and as TV broadcasters add computer programs and data to their video streams.Currently, the streams that can be found on the web have only very small data volume, but as network capacities increase, the data volume that is used by applications will also be increased. TV applications have a lack of networking support and are unable to give feedback to the sender. In the future the integration of computer networks, telephony and broadcast networks will achieve a functional integration of these two worlds.But as the amount of continuous media data which is offered for everybody to retrieve increases, simple caching mechanisms that work currently well will not be appropriate any more. To address this danger, the introduction of distribution mechanisms which provide more coordination among caches is necessary. As a basis for such a development, we investigate the probability of movies to be requested. This is chosen as a starting point because the current simple caching mechanisms operate very successfully for small-volume data such as text or icons, and high-quality movies are currently the most attractive medium which has the very high requirements in terms of storage as well as bandwidth. In this paper, we review current models on access probabilities and we give strong indication that the current assumptions about hit rates are invalid if the number of users connecting to an individual server differ widely. Since on-demand retrieval of large continuous media streams (especially movies) is currently available only as music CD and movie rental or sale, we take that data as a basis to create a model for access probabilities on this most storage-and bandwidth-demanding multimedia data. 168CHAPTER 10

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Popularity-based assignment of movies to storage devices in a video-on-demand system

Cited by 107 publications

References 13 publications

Distributed servers architecture for networked video services

Distributed servers architecture for networked video services

Quality-Aware Replication of Multimedia Data

Life-Cycle Considerations for Wide-Area Distribution of Multimedia Data

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