Entropy Based Image Segmentation for Energy Efficient LTE System with Cloud
Abstract Nowadays LTE network provides high speed data transmission for advanced web based applications and consumes lot of energy. Energy consumption needs to be minimized for a mobile devices running on batteries. In this paper, we have considered a problem of minimizing total energy consumption o...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Mittal, Anshu [verfasserIn] Kundu, Chinmoy [verfasserIn] Bose, Ranjan [verfasserIn] Shevgaonkar, R. K. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Wireless personal communications - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994, 92(2016), 3 vom: 10. Aug., Seite 1145-1162 |
|---|---|
| Übergeordnetes Werk: |
volume:92 ; year:2016 ; number:3 ; day:10 ; month:08 ; pages:1145-1162 |
| Links: |
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| DOI / URN: |
10.1007/s11277-016-3598-9 |
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| Katalog-ID: |
SPR018578446 |
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| 245 | 1 | 0 | |a Entropy Based Image Segmentation for Energy Efficient LTE System with Cloud |
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| 520 | |a Abstract Nowadays LTE network provides high speed data transmission for advanced web based applications and consumes lot of energy. Energy consumption needs to be minimized for a mobile devices running on batteries. In this paper, we have considered a problem of minimizing total energy consumption of a mobile device transmitting an image to cloud through LTE network with a specific bit error rate requirement. Total energy consumption per information bit is calculated by measuring computation energy, circuit energy and radio energy. We have also proposed an algorithm to minimize the total energy consumption while transferring the image. The algorithm makes use of the information entropy of the segments that the image contains. We have also given the complexity of the algorithm in terms of the total number of required operations. As compared to the energy required for transferring the fully uncompressed or fully compressed image, our optimized algorithm can save upto 26 % energy. Energy saving depends on transmission distance and required bit error rate. | ||
| 650 | 4 | |a Energy consumption |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Energy per bit optimization |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Entropy |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Image segmentation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a LTE uplink transmission |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Kundu, Chinmoy |e verfasserin |4 aut | |
| 700 | 1 | |a Bose, Ranjan |e verfasserin |4 aut | |
| 700 | 1 | |a Shevgaonkar, R. K. |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Wireless personal communications |d Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 |g 92(2016), 3 vom: 10. Aug., Seite 1145-1162 |w (DE-627)271179120 |w (DE-600)1479327-1 |x 1572-834X |7 nnns |
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10.1007/s11277-016-3598-9 doi (DE-627)SPR018578446 (SPR)s11277-016-3598-9-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Mittal, Anshu verfasserin aut Entropy Based Image Segmentation for Energy Efficient LTE System with Cloud 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Nowadays LTE network provides high speed data transmission for advanced web based applications and consumes lot of energy. Energy consumption needs to be minimized for a mobile devices running on batteries. In this paper, we have considered a problem of minimizing total energy consumption of a mobile device transmitting an image to cloud through LTE network with a specific bit error rate requirement. Total energy consumption per information bit is calculated by measuring computation energy, circuit energy and radio energy. We have also proposed an algorithm to minimize the total energy consumption while transferring the image. The algorithm makes use of the information entropy of the segments that the image contains. We have also given the complexity of the algorithm in terms of the total number of required operations. As compared to the energy required for transferring the fully uncompressed or fully compressed image, our optimized algorithm can save upto 26 % energy. Energy saving depends on transmission distance and required bit error rate. Energy consumption (dpeaa)DE-He213 Energy per bit optimization (dpeaa)DE-He213 Entropy (dpeaa)DE-He213 Image segmentation (dpeaa)DE-He213 LTE uplink transmission (dpeaa)DE-He213 Kundu, Chinmoy verfasserin aut Bose, Ranjan verfasserin aut Shevgaonkar, R. K. verfasserin aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 92(2016), 3 vom: 10. Aug., Seite 1145-1162 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:92 year:2016 number:3 day:10 month:08 pages:1145-1162 https://dx.doi.org/10.1007/s11277-016-3598-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.00 ASE AR 92 2016 3 10 08 1145-1162 |
| spelling |
10.1007/s11277-016-3598-9 doi (DE-627)SPR018578446 (SPR)s11277-016-3598-9-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Mittal, Anshu verfasserin aut Entropy Based Image Segmentation for Energy Efficient LTE System with Cloud 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Nowadays LTE network provides high speed data transmission for advanced web based applications and consumes lot of energy. Energy consumption needs to be minimized for a mobile devices running on batteries. In this paper, we have considered a problem of minimizing total energy consumption of a mobile device transmitting an image to cloud through LTE network with a specific bit error rate requirement. Total energy consumption per information bit is calculated by measuring computation energy, circuit energy and radio energy. We have also proposed an algorithm to minimize the total energy consumption while transferring the image. The algorithm makes use of the information entropy of the segments that the image contains. We have also given the complexity of the algorithm in terms of the total number of required operations. As compared to the energy required for transferring the fully uncompressed or fully compressed image, our optimized algorithm can save upto 26 % energy. Energy saving depends on transmission distance and required bit error rate. Energy consumption (dpeaa)DE-He213 Energy per bit optimization (dpeaa)DE-He213 Entropy (dpeaa)DE-He213 Image segmentation (dpeaa)DE-He213 LTE uplink transmission (dpeaa)DE-He213 Kundu, Chinmoy verfasserin aut Bose, Ranjan verfasserin aut Shevgaonkar, R. K. verfasserin aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 92(2016), 3 vom: 10. Aug., Seite 1145-1162 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:92 year:2016 number:3 day:10 month:08 pages:1145-1162 https://dx.doi.org/10.1007/s11277-016-3598-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.00 ASE AR 92 2016 3 10 08 1145-1162 |
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10.1007/s11277-016-3598-9 doi (DE-627)SPR018578446 (SPR)s11277-016-3598-9-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Mittal, Anshu verfasserin aut Entropy Based Image Segmentation for Energy Efficient LTE System with Cloud 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Nowadays LTE network provides high speed data transmission for advanced web based applications and consumes lot of energy. Energy consumption needs to be minimized for a mobile devices running on batteries. In this paper, we have considered a problem of minimizing total energy consumption of a mobile device transmitting an image to cloud through LTE network with a specific bit error rate requirement. Total energy consumption per information bit is calculated by measuring computation energy, circuit energy and radio energy. We have also proposed an algorithm to minimize the total energy consumption while transferring the image. The algorithm makes use of the information entropy of the segments that the image contains. We have also given the complexity of the algorithm in terms of the total number of required operations. As compared to the energy required for transferring the fully uncompressed or fully compressed image, our optimized algorithm can save upto 26 % energy. Energy saving depends on transmission distance and required bit error rate. Energy consumption (dpeaa)DE-He213 Energy per bit optimization (dpeaa)DE-He213 Entropy (dpeaa)DE-He213 Image segmentation (dpeaa)DE-He213 LTE uplink transmission (dpeaa)DE-He213 Kundu, Chinmoy verfasserin aut Bose, Ranjan verfasserin aut Shevgaonkar, R. K. verfasserin aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 92(2016), 3 vom: 10. Aug., Seite 1145-1162 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:92 year:2016 number:3 day:10 month:08 pages:1145-1162 https://dx.doi.org/10.1007/s11277-016-3598-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.00 ASE AR 92 2016 3 10 08 1145-1162 |
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10.1007/s11277-016-3598-9 doi (DE-627)SPR018578446 (SPR)s11277-016-3598-9-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Mittal, Anshu verfasserin aut Entropy Based Image Segmentation for Energy Efficient LTE System with Cloud 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Nowadays LTE network provides high speed data transmission for advanced web based applications and consumes lot of energy. Energy consumption needs to be minimized for a mobile devices running on batteries. In this paper, we have considered a problem of minimizing total energy consumption of a mobile device transmitting an image to cloud through LTE network with a specific bit error rate requirement. Total energy consumption per information bit is calculated by measuring computation energy, circuit energy and radio energy. We have also proposed an algorithm to minimize the total energy consumption while transferring the image. The algorithm makes use of the information entropy of the segments that the image contains. We have also given the complexity of the algorithm in terms of the total number of required operations. As compared to the energy required for transferring the fully uncompressed or fully compressed image, our optimized algorithm can save upto 26 % energy. Energy saving depends on transmission distance and required bit error rate. Energy consumption (dpeaa)DE-He213 Energy per bit optimization (dpeaa)DE-He213 Entropy (dpeaa)DE-He213 Image segmentation (dpeaa)DE-He213 LTE uplink transmission (dpeaa)DE-He213 Kundu, Chinmoy verfasserin aut Bose, Ranjan verfasserin aut Shevgaonkar, R. K. verfasserin aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 92(2016), 3 vom: 10. Aug., Seite 1145-1162 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:92 year:2016 number:3 day:10 month:08 pages:1145-1162 https://dx.doi.org/10.1007/s11277-016-3598-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.00 ASE AR 92 2016 3 10 08 1145-1162 |
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10.1007/s11277-016-3598-9 doi (DE-627)SPR018578446 (SPR)s11277-016-3598-9-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Mittal, Anshu verfasserin aut Entropy Based Image Segmentation for Energy Efficient LTE System with Cloud 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Nowadays LTE network provides high speed data transmission for advanced web based applications and consumes lot of energy. Energy consumption needs to be minimized for a mobile devices running on batteries. In this paper, we have considered a problem of minimizing total energy consumption of a mobile device transmitting an image to cloud through LTE network with a specific bit error rate requirement. Total energy consumption per information bit is calculated by measuring computation energy, circuit energy and radio energy. We have also proposed an algorithm to minimize the total energy consumption while transferring the image. The algorithm makes use of the information entropy of the segments that the image contains. We have also given the complexity of the algorithm in terms of the total number of required operations. As compared to the energy required for transferring the fully uncompressed or fully compressed image, our optimized algorithm can save upto 26 % energy. Energy saving depends on transmission distance and required bit error rate. Energy consumption (dpeaa)DE-He213 Energy per bit optimization (dpeaa)DE-He213 Entropy (dpeaa)DE-He213 Image segmentation (dpeaa)DE-He213 LTE uplink transmission (dpeaa)DE-He213 Kundu, Chinmoy verfasserin aut Bose, Ranjan verfasserin aut Shevgaonkar, R. K. verfasserin aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 92(2016), 3 vom: 10. Aug., Seite 1145-1162 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:92 year:2016 number:3 day:10 month:08 pages:1145-1162 https://dx.doi.org/10.1007/s11277-016-3598-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.00 ASE AR 92 2016 3 10 08 1145-1162 |
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Enthalten in Wireless personal communications 92(2016), 3 vom: 10. Aug., Seite 1145-1162 volume:92 year:2016 number:3 day:10 month:08 pages:1145-1162 |
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Enthalten in Wireless personal communications 92(2016), 3 vom: 10. Aug., Seite 1145-1162 volume:92 year:2016 number:3 day:10 month:08 pages:1145-1162 |
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Energy consumption Energy per bit optimization Entropy Image segmentation LTE uplink transmission |
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Wireless personal communications |
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Mittal, Anshu @@aut@@ Kundu, Chinmoy @@aut@@ Bose, Ranjan @@aut@@ Shevgaonkar, R. K. @@aut@@ |
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2016-08-10T00:00:00Z |
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| author |
Mittal, Anshu |
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Mittal, Anshu ddc 620 bkl 53.00 misc Energy consumption misc Energy per bit optimization misc Entropy misc Image segmentation misc LTE uplink transmission Entropy Based Image Segmentation for Energy Efficient LTE System with Cloud |
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620 ASE 53.00 bkl Entropy Based Image Segmentation for Energy Efficient LTE System with Cloud Energy consumption (dpeaa)DE-He213 Energy per bit optimization (dpeaa)DE-He213 Entropy (dpeaa)DE-He213 Image segmentation (dpeaa)DE-He213 LTE uplink transmission (dpeaa)DE-He213 |
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ddc 620 bkl 53.00 misc Energy consumption misc Energy per bit optimization misc Entropy misc Image segmentation misc LTE uplink transmission |
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Entropy Based Image Segmentation for Energy Efficient LTE System with Cloud |
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entropy based image segmentation for energy efficient lte system with cloud |
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Entropy Based Image Segmentation for Energy Efficient LTE System with Cloud |
| abstract |
Abstract Nowadays LTE network provides high speed data transmission for advanced web based applications and consumes lot of energy. Energy consumption needs to be minimized for a mobile devices running on batteries. In this paper, we have considered a problem of minimizing total energy consumption of a mobile device transmitting an image to cloud through LTE network with a specific bit error rate requirement. Total energy consumption per information bit is calculated by measuring computation energy, circuit energy and radio energy. We have also proposed an algorithm to minimize the total energy consumption while transferring the image. The algorithm makes use of the information entropy of the segments that the image contains. We have also given the complexity of the algorithm in terms of the total number of required operations. As compared to the energy required for transferring the fully uncompressed or fully compressed image, our optimized algorithm can save upto 26 % energy. Energy saving depends on transmission distance and required bit error rate. |
| abstractGer |
Abstract Nowadays LTE network provides high speed data transmission for advanced web based applications and consumes lot of energy. Energy consumption needs to be minimized for a mobile devices running on batteries. In this paper, we have considered a problem of minimizing total energy consumption of a mobile device transmitting an image to cloud through LTE network with a specific bit error rate requirement. Total energy consumption per information bit is calculated by measuring computation energy, circuit energy and radio energy. We have also proposed an algorithm to minimize the total energy consumption while transferring the image. The algorithm makes use of the information entropy of the segments that the image contains. We have also given the complexity of the algorithm in terms of the total number of required operations. As compared to the energy required for transferring the fully uncompressed or fully compressed image, our optimized algorithm can save upto 26 % energy. Energy saving depends on transmission distance and required bit error rate. |
| abstract_unstemmed |
Abstract Nowadays LTE network provides high speed data transmission for advanced web based applications and consumes lot of energy. Energy consumption needs to be minimized for a mobile devices running on batteries. In this paper, we have considered a problem of minimizing total energy consumption of a mobile device transmitting an image to cloud through LTE network with a specific bit error rate requirement. Total energy consumption per information bit is calculated by measuring computation energy, circuit energy and radio energy. We have also proposed an algorithm to minimize the total energy consumption while transferring the image. The algorithm makes use of the information entropy of the segments that the image contains. We have also given the complexity of the algorithm in terms of the total number of required operations. As compared to the energy required for transferring the fully uncompressed or fully compressed image, our optimized algorithm can save upto 26 % energy. Energy saving depends on transmission distance and required bit error rate. |
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Entropy Based Image Segmentation for Energy Efficient LTE System with Cloud |
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https://dx.doi.org/10.1007/s11277-016-3598-9 |
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Kundu, Chinmoy Bose, Ranjan Shevgaonkar, R. K. |
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Kundu, Chinmoy Bose, Ranjan Shevgaonkar, R. K. |
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| doi_str |
10.1007/s11277-016-3598-9 |
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2024-07-03T20:42:51.485Z |
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| score |
7.402237 |