The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Este artigo propõe dois algoritmos para equilibrar o consumo de energia entre nós sensores, distribuindo a carga de trabalho das tarefas de compressão de imagens dentro de um cluster em redes de sensores sem fio. O ponto principal dos algoritmos propostos é adotar o limite de energia, que é utilizado quando implementamos a troca e/ou atribuição de tarefas entre nós sensores. O limite é bem adaptável à energia residual dos nós sensores, imagem de entrada, saída compactada e parâmetros de rede. Aplicamos a técnica de transformação lapidada, uma versão estendida da transformada discreta de cosseno e a codificação de comprimento de execução antes da codificação Lempel-Ziv-Welch aos algoritmos propostos para melhorar a qualidade e a taxa de compressão no esquema de compressão de imagem. Conduzimos extensivamente experimentos computacionais para verificar nossos métodos e descobrimos que os algoritmos propostos alcançam não apenas o equilíbrio do consumo total de energia entre os nós sensores e, assim, aumentando a vida útil geral da rede, mas também reduzindo o ruído de bloco na compressão de imagens.
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Phat NGUYEN HUU, Vinh TRAN-QUANG, Takumi MIYOSHI, "Low-Complexity and Energy-Efficient Algorithms on Image Compression for Wireless Sensor Networks" in IEICE TRANSACTIONS on Communications,
vol. E93-B, no. 12, pp. 3438-3447, December 2010, doi: 10.1587/transcom.E93.B.3438.
Abstract: This paper proposes two algorithms to balance energy consumption among sensor nodes by distributing the workload of image compression tasks within a cluster on wireless sensor networks. The main point of the proposed algorithms is to adopt the energy threshold, which is used when we implement the exchange and/or assignment of tasks among sensor nodes. The threshold is well adaptive to the residual energy of sensor nodes, input image, compressed output, and network parameters. We apply the lapped transform technique, an extended version of the discrete cosine transform, and run length encoding before Lempel-Ziv-Welch coding to the proposed algorithms to improve both quality and compression rate in image compression scheme. We extensively conduct computational experiments to verify the our methods and find that the proposed algorithms achieve not only balancing the total energy consumption among sensor nodes and, thus, increasing the overall network lifetime, but also reducing block noise in image compression.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E93.B.3438/_p
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@ARTICLE{e93-b_12_3438,
author={Phat NGUYEN HUU, Vinh TRAN-QUANG, Takumi MIYOSHI, },
journal={IEICE TRANSACTIONS on Communications},
title={Low-Complexity and Energy-Efficient Algorithms on Image Compression for Wireless Sensor Networks},
year={2010},
volume={E93-B},
number={12},
pages={3438-3447},
abstract={This paper proposes two algorithms to balance energy consumption among sensor nodes by distributing the workload of image compression tasks within a cluster on wireless sensor networks. The main point of the proposed algorithms is to adopt the energy threshold, which is used when we implement the exchange and/or assignment of tasks among sensor nodes. The threshold is well adaptive to the residual energy of sensor nodes, input image, compressed output, and network parameters. We apply the lapped transform technique, an extended version of the discrete cosine transform, and run length encoding before Lempel-Ziv-Welch coding to the proposed algorithms to improve both quality and compression rate in image compression scheme. We extensively conduct computational experiments to verify the our methods and find that the proposed algorithms achieve not only balancing the total energy consumption among sensor nodes and, thus, increasing the overall network lifetime, but also reducing block noise in image compression.},
keywords={},
doi={10.1587/transcom.E93.B.3438},
ISSN={1745-1345},
month={December},}
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TY - JOUR
TI - Low-Complexity and Energy-Efficient Algorithms on Image Compression for Wireless Sensor Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 3438
EP - 3447
AU - Phat NGUYEN HUU
AU - Vinh TRAN-QUANG
AU - Takumi MIYOSHI
PY - 2010
DO - 10.1587/transcom.E93.B.3438
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E93-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 2010
AB - This paper proposes two algorithms to balance energy consumption among sensor nodes by distributing the workload of image compression tasks within a cluster on wireless sensor networks. The main point of the proposed algorithms is to adopt the energy threshold, which is used when we implement the exchange and/or assignment of tasks among sensor nodes. The threshold is well adaptive to the residual energy of sensor nodes, input image, compressed output, and network parameters. We apply the lapped transform technique, an extended version of the discrete cosine transform, and run length encoding before Lempel-Ziv-Welch coding to the proposed algorithms to improve both quality and compression rate in image compression scheme. We extensively conduct computational experiments to verify the our methods and find that the proposed algorithms achieve not only balancing the total energy consumption among sensor nodes and, thus, increasing the overall network lifetime, but also reducing block noise in image compression.
ER -