Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network

Abstract At first, the entanglement source deployment problem is studied in a quantum multi-hop network, which has a significant influence on quantum connectivity. Two optimization algorithms are introduced with limited entanglement sources in this paper. A deployment algorithm based on node positio...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Zou, Zhen-Zhen [verfasserIn] Yu, Xu-Tao [verfasserIn] Zhang, Zai-Chen [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	entanglement source deployment quantum connectivity deployment algorithm

Übergeordnetes Werk:	Enthalten in: Frontiers of physics in China - Berlin : Heidelberg : Springer, 2006, 13(2017), 2 vom: 30. Sept.
Übergeordnetes Werk:	volume:13 ; year:2017 ; number:2 ; day:30 ; month:09

Links:	Volltext

DOI / URN:	10.1007/s11467-017-0721-7

Katalog-ID:	SPR019881533

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allfields	10.1007/s11467-017-0721-7 doi (DE-627)SPR019881533 (SPR)s11467-017-0721-7-e DE-627 ger DE-627 rakwb eng 530 ASE Zou, Zhen-Zhen verfasserin aut Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract At first, the entanglement source deployment problem is studied in a quantum multi-hop network, which has a significant influence on quantum connectivity. Two optimization algorithms are introduced with limited entanglement sources in this paper. A deployment algorithm based on node position (DNP) improves connectivity by guaranteeing that all overlapping areas of the distribution ranges of the entanglement sources contain nodes. In addition, a deployment algorithm based on an improved genetic algorithm (DIGA) is implemented by dividing the region into grids. From the simulation results, DNP and DIGA improve quantum connectivity by 213.73% and 248.83% compared to random deployment, respectively, and the latter performs better in terms of connectivity. However, DNP is more flexible and adaptive to change, as it stops running when all nodes are covered. entanglement source deployment (dpeaa)DE-He213 quantum connectivity (dpeaa)DE-He213 deployment algorithm (dpeaa)DE-He213 Yu, Xu-Tao verfasserin aut Zhang, Zai-Chen verfasserin aut Enthalten in Frontiers of physics in China Berlin : Heidelberg : Springer, 2006 13(2017), 2 vom: 30. Sept. (DE-627)509758428 (DE-600)2228431-X 1673-3606 nnns volume:13 year:2017 number:2 day:30 month:09 https://dx.doi.org/10.1007/s11467-017-0721-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 13 2017 2 30 09
spelling	10.1007/s11467-017-0721-7 doi (DE-627)SPR019881533 (SPR)s11467-017-0721-7-e DE-627 ger DE-627 rakwb eng 530 ASE Zou, Zhen-Zhen verfasserin aut Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract At first, the entanglement source deployment problem is studied in a quantum multi-hop network, which has a significant influence on quantum connectivity. Two optimization algorithms are introduced with limited entanglement sources in this paper. A deployment algorithm based on node position (DNP) improves connectivity by guaranteeing that all overlapping areas of the distribution ranges of the entanglement sources contain nodes. In addition, a deployment algorithm based on an improved genetic algorithm (DIGA) is implemented by dividing the region into grids. From the simulation results, DNP and DIGA improve quantum connectivity by 213.73% and 248.83% compared to random deployment, respectively, and the latter performs better in terms of connectivity. However, DNP is more flexible and adaptive to change, as it stops running when all nodes are covered. entanglement source deployment (dpeaa)DE-He213 quantum connectivity (dpeaa)DE-He213 deployment algorithm (dpeaa)DE-He213 Yu, Xu-Tao verfasserin aut Zhang, Zai-Chen verfasserin aut Enthalten in Frontiers of physics in China Berlin : Heidelberg : Springer, 2006 13(2017), 2 vom: 30. Sept. (DE-627)509758428 (DE-600)2228431-X 1673-3606 nnns volume:13 year:2017 number:2 day:30 month:09 https://dx.doi.org/10.1007/s11467-017-0721-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 13 2017 2 30 09
allfields_unstemmed	10.1007/s11467-017-0721-7 doi (DE-627)SPR019881533 (SPR)s11467-017-0721-7-e DE-627 ger DE-627 rakwb eng 530 ASE Zou, Zhen-Zhen verfasserin aut Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract At first, the entanglement source deployment problem is studied in a quantum multi-hop network, which has a significant influence on quantum connectivity. Two optimization algorithms are introduced with limited entanglement sources in this paper. A deployment algorithm based on node position (DNP) improves connectivity by guaranteeing that all overlapping areas of the distribution ranges of the entanglement sources contain nodes. In addition, a deployment algorithm based on an improved genetic algorithm (DIGA) is implemented by dividing the region into grids. From the simulation results, DNP and DIGA improve quantum connectivity by 213.73% and 248.83% compared to random deployment, respectively, and the latter performs better in terms of connectivity. However, DNP is more flexible and adaptive to change, as it stops running when all nodes are covered. entanglement source deployment (dpeaa)DE-He213 quantum connectivity (dpeaa)DE-He213 deployment algorithm (dpeaa)DE-He213 Yu, Xu-Tao verfasserin aut Zhang, Zai-Chen verfasserin aut Enthalten in Frontiers of physics in China Berlin : Heidelberg : Springer, 2006 13(2017), 2 vom: 30. Sept. (DE-627)509758428 (DE-600)2228431-X 1673-3606 nnns volume:13 year:2017 number:2 day:30 month:09 https://dx.doi.org/10.1007/s11467-017-0721-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 13 2017 2 30 09
allfieldsGer	10.1007/s11467-017-0721-7 doi (DE-627)SPR019881533 (SPR)s11467-017-0721-7-e DE-627 ger DE-627 rakwb eng 530 ASE Zou, Zhen-Zhen verfasserin aut Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract At first, the entanglement source deployment problem is studied in a quantum multi-hop network, which has a significant influence on quantum connectivity. Two optimization algorithms are introduced with limited entanglement sources in this paper. A deployment algorithm based on node position (DNP) improves connectivity by guaranteeing that all overlapping areas of the distribution ranges of the entanglement sources contain nodes. In addition, a deployment algorithm based on an improved genetic algorithm (DIGA) is implemented by dividing the region into grids. From the simulation results, DNP and DIGA improve quantum connectivity by 213.73% and 248.83% compared to random deployment, respectively, and the latter performs better in terms of connectivity. However, DNP is more flexible and adaptive to change, as it stops running when all nodes are covered. entanglement source deployment (dpeaa)DE-He213 quantum connectivity (dpeaa)DE-He213 deployment algorithm (dpeaa)DE-He213 Yu, Xu-Tao verfasserin aut Zhang, Zai-Chen verfasserin aut Enthalten in Frontiers of physics in China Berlin : Heidelberg : Springer, 2006 13(2017), 2 vom: 30. Sept. (DE-627)509758428 (DE-600)2228431-X 1673-3606 nnns volume:13 year:2017 number:2 day:30 month:09 https://dx.doi.org/10.1007/s11467-017-0721-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 13 2017 2 30 09
allfieldsSound	10.1007/s11467-017-0721-7 doi (DE-627)SPR019881533 (SPR)s11467-017-0721-7-e DE-627 ger DE-627 rakwb eng 530 ASE Zou, Zhen-Zhen verfasserin aut Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract At first, the entanglement source deployment problem is studied in a quantum multi-hop network, which has a significant influence on quantum connectivity. Two optimization algorithms are introduced with limited entanglement sources in this paper. A deployment algorithm based on node position (DNP) improves connectivity by guaranteeing that all overlapping areas of the distribution ranges of the entanglement sources contain nodes. In addition, a deployment algorithm based on an improved genetic algorithm (DIGA) is implemented by dividing the region into grids. From the simulation results, DNP and DIGA improve quantum connectivity by 213.73% and 248.83% compared to random deployment, respectively, and the latter performs better in terms of connectivity. However, DNP is more flexible and adaptive to change, as it stops running when all nodes are covered. entanglement source deployment (dpeaa)DE-He213 quantum connectivity (dpeaa)DE-He213 deployment algorithm (dpeaa)DE-He213 Yu, Xu-Tao verfasserin aut Zhang, Zai-Chen verfasserin aut Enthalten in Frontiers of physics in China Berlin : Heidelberg : Springer, 2006 13(2017), 2 vom: 30. Sept. (DE-627)509758428 (DE-600)2228431-X 1673-3606 nnns volume:13 year:2017 number:2 day:30 month:09 https://dx.doi.org/10.1007/s11467-017-0721-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 13 2017 2 30 09
language	English
source	Enthalten in Frontiers of physics in China 13(2017), 2 vom: 30. Sept. volume:13 year:2017 number:2 day:30 month:09
sourceStr	Enthalten in Frontiers of physics in China 13(2017), 2 vom: 30. Sept. volume:13 year:2017 number:2 day:30 month:09
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	entanglement source deployment quantum connectivity deployment algorithm
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authorswithroles_txt_mv	Zou, Zhen-Zhen @@aut@@ Yu, Xu-Tao @@aut@@ Zhang, Zai-Chen @@aut@@
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author	Zou, Zhen-Zhen
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topic_title	530 ASE Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network entanglement source deployment (dpeaa)DE-He213 quantum connectivity (dpeaa)DE-He213 deployment algorithm (dpeaa)DE-He213
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title	Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network
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title_full	Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network
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title_sort	quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network
title_auth	Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network
abstract	Abstract At first, the entanglement source deployment problem is studied in a quantum multi-hop network, which has a significant influence on quantum connectivity. Two optimization algorithms are introduced with limited entanglement sources in this paper. A deployment algorithm based on node position (DNP) improves connectivity by guaranteeing that all overlapping areas of the distribution ranges of the entanglement sources contain nodes. In addition, a deployment algorithm based on an improved genetic algorithm (DIGA) is implemented by dividing the region into grids. From the simulation results, DNP and DIGA improve quantum connectivity by 213.73% and 248.83% compared to random deployment, respectively, and the latter performs better in terms of connectivity. However, DNP is more flexible and adaptive to change, as it stops running when all nodes are covered.
abstractGer	Abstract At first, the entanglement source deployment problem is studied in a quantum multi-hop network, which has a significant influence on quantum connectivity. Two optimization algorithms are introduced with limited entanglement sources in this paper. A deployment algorithm based on node position (DNP) improves connectivity by guaranteeing that all overlapping areas of the distribution ranges of the entanglement sources contain nodes. In addition, a deployment algorithm based on an improved genetic algorithm (DIGA) is implemented by dividing the region into grids. From the simulation results, DNP and DIGA improve quantum connectivity by 213.73% and 248.83% compared to random deployment, respectively, and the latter performs better in terms of connectivity. However, DNP is more flexible and adaptive to change, as it stops running when all nodes are covered.
abstract_unstemmed	Abstract At first, the entanglement source deployment problem is studied in a quantum multi-hop network, which has a significant influence on quantum connectivity. Two optimization algorithms are introduced with limited entanglement sources in this paper. A deployment algorithm based on node position (DNP) improves connectivity by guaranteeing that all overlapping areas of the distribution ranges of the entanglement sources contain nodes. In addition, a deployment algorithm based on an improved genetic algorithm (DIGA) is implemented by dividing the region into grids. From the simulation results, DNP and DIGA improve quantum connectivity by 213.73% and 248.83% compared to random deployment, respectively, and the latter performs better in terms of connectivity. However, DNP is more flexible and adaptive to change, as it stops running when all nodes are covered.
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title_short	Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network
url	https://dx.doi.org/10.1007/s11467-017-0721-7
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up_date	2024-07-04T03:12:26.478Z
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