Bandwidth optimizations for standards-based publish/subscribe in disadvantaged grids

Skjervold, Espen; Lund, Ketil; Bloebaum, Trude H.; Johnsen, Frank T.

doi:10.1109/milcom.2012.6415635

Cited by 4 publications

(1 citation statement)

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“…This problem suffers from the challenges of the sheer speed of data as well as bandwidth constrains in the system. The basic idea is to reduce the volume of data and to optimize the quality of service by compression, as done in other publish/subscribe systems [32].…”

Section: Introductionmentioning

confidence: 99%

Multi-scale dissemination of time series data

Guo

Zhou

2013

Proceedings of the 25th International Conference on Scientific and Statistical Database Management

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In this paper, we consider the problem of continuous dissemination of time series data, such as sensor measurements, to a large number of subscribers. These subscribers fall into multiple subscription levels, where each subscription level is specified by the bandwidth constraint of a subscriber, which is an abstract indicator for both the physical limits and the amount of data that the subscriber would like to handle. To handle this problem, we propose a system framework for multi-scale time series data dissemination that employs a typical tree-based dissemination network and existing time-series compression models. Due to the bandwidth limits regarding to potentially sheer speed of data, it is inevitable to compress and re-compress data along the dissemination paths according to the subscription level of each node. Compression would caused the accuracy loss of data, thus we devise several algorithms to optimize the average accuracies of the data received by all subscribers within the dissemination network. Finally, we have conducted extensive experiments to study the performance of the algorithms.

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Section: Introductionmentioning

confidence: 99%