Compression of Short Text on Embedded Systems

Rein, Stephan; Gühmann, Clemens; Fitzek, Frank H. P.

doi:10.4304/jcp.1.6.1-10

Cited by 12 publications

(17 citation statements)

References 18 publications

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“…For each form, we took 20 samples of the gateway power consumption using gnome-power-statistics, showing that a mean value of 21.42W and 21.03W were consumed by the first and second form, respectively. In this way, the power that can be consumed by performing the compression is mitigated by the gains of using less power to send less information, particularly over the wireless medium, as is substantiated by [17].…”

Section: ) Compression Energy Consumptionmentioning

confidence: 93%

A framework for flexible sensor information dissemination

Corujo

Lebre

Gomes

et al. 2011

2011 International Conference on Distributed Computing in Sensor Systems and Workshops (DCOSS)

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The integration of the digital world into every aspect of our lives is becoming more and more preeminent. Nowadays, not only humans but also devices and the environments where we dwell are also able to provide their own information, through the usage of sensors. Through their interconnection over communication networks, sensors enable Ambient Intelligent scenarios achieving a true Internet of Things, and crossing the gap between computer systems and the real world. However, the different sensing devices and information generated by them, are of such disparate nature that it becomes increasingly difficult to access and make use of such heterogeneous data. In this paper, we propose a framework which not only considers a media independent information access to sensors and their supplied data, but is also flexible enough to configure and provide different means to best transport collected sensor information via wireless gateways, facilitating its deployment in different scenarios. We demonstrate its usefulness by providing a throughput efficient approach towards the collection and dissemination of sensing data, through sensing information compression and aggregation of multiple sources.

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Section: ) Compression Energy Consumptionmentioning

confidence: 93%

A framework for flexible sensor information dissemination

Corujo

Lebre

Gomes

et al. 2011

2011 International Conference on Distributed Computing in Sensor Systems and Workshops (DCOSS)

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“…Most of the work is designed for compressing large size text and does not consider devices with limited resources. The researchers of (Rein et al, 2006a) indicated that many of the well known compression require memory from 0.5 to more than 100 Mbyte. On the other hand, most of the sensor networks' data compression techniques use statistical correlations between the typically larger data of multiple sensors as they all observe the same phenomenon which make them unsuitable for text compression.…”

Section: Methodsmentioning

confidence: 99%

“…These algorithms are based on the idea of replacing the strings in the text with a pointer to where they have occurred earlier in the text. This family of algorithms are generally derived from one of the two approaches namely LZ77 and LZ78, respectively (Rein et al, 2006a).…”

Section: Methodsmentioning

confidence: 99%

“…Statistical coding schemes make use of the fact that different symbols usually occur at different frequencies and assign shorter codes to symbols that occur more frequently and longer codes to less frequently used symbols. They employ a statistical context model to compute the appropriate probabilities (Rein et al, 2006a). Then, the probabilities are coded with a proper encoding such as Huffman (1952), Arithmetic coding (Witten et al, 1987) or any entropy coder.…”

Section: Introductionmentioning

confidence: 99%

“…The statistical coders give better compression performance than the dictionary coders. However, generally, they require large amounts memory (Rein et al, 2006a).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Arabic Short Text Compression

Omer¹

2010

Journal of Computer Science

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Problem statement: Text compression permits representing a document by using less space. This is useful not only to save disk space, but more importantly, to save disk transfer and network transmission time. With the continues increase in the number of Arabic short text messages sent by mobile phones, the use of a suitable compression scheme would allow users to use more characters than the default value specified by the provider. The development of an efficient compression scheme to compress short Arabic texts is not a straight forward task. Approach: This study combined the benefits of pre-processing, entropy reduction through splitting files and hybrid dynamic coding: A new technique proposed in this study that uses the fact that Arabic texts have single case letters. Experimental tests had been performed on short Arabic texts and a comparison with the well known plain Huffman compression was made to measure the performance of the proposed schema for Arabic short text. Results: The proposed schema can achieve a compression ratio around 4.6 bits byte^-1 for very short Arabic text sequences of 15 bytes and around 4 bits byte^-1 for 50 bytes text sequences, using only 8 Kbytes overhead of memory. Conclusion: Furthermore, a reasonable compression ratio can be achieved using less than 0.4 KB of memory overhead. We recommended the use of proposed schema to compress small Arabic text with recourses limited

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Sensor Networks for Distributed Computing

Rein

Gühmann

Fitzek

Mobile Phone Programming

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Compression of Short Text on Embedded Systems

Cited by 12 publications

References 18 publications

A framework for flexible sensor information dissemination

A framework for flexible sensor information dissemination

Arabic Short Text Compression

Sensor Networks for Distributed Computing

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