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Open AccessJournal Article

Dynamic data delivery in wireless communication environments

Qinglong Hu, +2 more
- 01 Jan 1999 - 
- Vol. 1552, pp 218-229
TLDR
A dynamic data delivery model where data are disseminated through various storage mediums according to the dynamically collected data access patterns and performance evaluation of the model is conducted by simulation studies.
Abstract
Information broadcasting, caching of frequently accessed data, and pull-based data delivery are commonly used techniques to reduce data access time of wireless information services. Most of the studies in the literature focused either on individual technique or a combination of them with some restrictive assumptions. In this paper, we propose a dynamic data delivery model where these three techniques work together in an integrated manner. A particular feature of our model is that data are disseminated through various storage mediums according to the dynamically collected data access patterns. Performance evaluation of the model is conducted by simulation studies.

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Citations
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Journal ArticleDOI

Dependent data broadcasting for unordered queries in a multiple channel mobile environment

TL;DR: By analyzing the model of dependent data broadcasting, several theoretical properties for the average access time in a multiple channel environment are derived and a genetic algorithm is developed to generate broadcast programs of very high quality.
Proceedings ArticleDOI

Dependent data broadcasting for unordered queries in a multiple channel mobile environment

TL;DR: By analyzing the model of dependent data broadcasting, several theoretical properties for the average access time in a multiple channel environment are derived and a genetic algorithm is developed to generate broadcast programs of very high quality.
Proceedings ArticleDOI

Performance evaluation of a wireless hierarchical data dissemination system

TL;DR: An important feature of the proposed dynamic data delivery model is that data are disseminated through various storage mediums according to the dynamically collected data access patterns.
Journal ArticleDOI

Exploiting locality of demand to improve the performance of wireless data broadcasting

TL;DR: A mechanism that exploits locality of demand in order to increase the performance of wireless data dissemination systems and trades the received energy per bit redundancy at distances smaller than the radius of the service area for an increased bit rate for transmission of items demanded by clients at such distances.
Proceedings ArticleDOI

Dynamic data broadcasting with traffic awareness

TL;DR: The existence of client impatience is addressed and accordingly an online traffic awareness mechanism based on a novel selective deferment and reflection (SDR) technique to estimate the dynamic workloads and access patterns in a granularity of a broadcast cycle is devised.
References
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Proceedings ArticleDOI

The LRU-K page replacement algorithm for database disk buffering

TL;DR: The LRU-K algorithm surpasses conventional buffering algorithms in discriminating between frequently and infrequently referenced pages, and adapts in real time to changing patterns of access.

Broadcast Disks: Data Management for Asymmetric Communication Environments.

TL;DR: In this paper, the use of repetitive broadcast as a way of augmenting the memory hierarchy of clients in an asymmetric communication environment has been proposed, and a new technique called "broadcast disks" for structuring the broadcast in a way that provides improved performance for non-uniformly accessed data.
Proceedings Article

Sleepers and Workaholics: Caching Strategies in Mobile Environments

TL;DR: In this paper, a taxonomy of different cache invalidation strategies and study the impact of client's disconnection times on their performance is presented, and the authors determine that for the units which are often disconnected (sleepers) the best cache invalidization strategy is based on signatures previously used for efficient file comparison.
Proceedings ArticleDOI

Balancing push and pull for data broadcast

TL;DR: The results show that a client back channel can provide significant performance improvement in the broadcast environment, but that unconstrained use of the backchannel can result in scalability problems due to server saturation.
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