Network robustness improvement via long-range links
Abstract Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what e...
Ausführliche Beschreibung
Autor*in: |
Carchiolo, Vincenza [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2019 |
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Anmerkung: |
© The Author(s) 2019 |
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Übergeordnetes Werk: |
Enthalten in: Computational Social Networks - New York, NY [u.a.] : Springer international, 2014, 6(2019), 1 vom: 19. Nov. |
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Übergeordnetes Werk: |
volume:6 ; year:2019 ; number:1 ; day:19 ; month:11 |
Links: |
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DOI / URN: |
10.1186/s40649-019-0073-2 |
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Katalog-ID: |
SPR037115316 |
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10.1186/s40649-019-0073-2 doi (DE-627)SPR037115316 (SPR)s40649-019-0073-2-e DE-627 ger DE-627 rakwb eng Carchiolo, Vincenza verfasserin aut Network robustness improvement via long-range links 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Abstract Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies. Complex networks (dpeaa)DE-He213 Robustness (dpeaa)DE-He213 Network attacks (dpeaa)DE-He213 Long-distance links (dpeaa)DE-He213 Grassia, Marco aut Longheu, Alessandro aut Malgeri, Michele aut Mangioni, Giuseppe aut Enthalten in Computational Social Networks New York, NY [u.a.] : Springer international, 2014 6(2019), 1 vom: 19. Nov. (DE-627)815913907 (DE-600)2806588-8 2197-4314 nnns volume:6 year:2019 number:1 day:19 month:11 https://dx.doi.org/10.1186/s40649-019-0073-2 kostenfrei 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_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2019 1 19 11 |
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10.1186/s40649-019-0073-2 doi (DE-627)SPR037115316 (SPR)s40649-019-0073-2-e DE-627 ger DE-627 rakwb eng Carchiolo, Vincenza verfasserin aut Network robustness improvement via long-range links 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Abstract Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies. Complex networks (dpeaa)DE-He213 Robustness (dpeaa)DE-He213 Network attacks (dpeaa)DE-He213 Long-distance links (dpeaa)DE-He213 Grassia, Marco aut Longheu, Alessandro aut Malgeri, Michele aut Mangioni, Giuseppe aut Enthalten in Computational Social Networks New York, NY [u.a.] : Springer international, 2014 6(2019), 1 vom: 19. Nov. (DE-627)815913907 (DE-600)2806588-8 2197-4314 nnns volume:6 year:2019 number:1 day:19 month:11 https://dx.doi.org/10.1186/s40649-019-0073-2 kostenfrei 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_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2019 1 19 11 |
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10.1186/s40649-019-0073-2 doi (DE-627)SPR037115316 (SPR)s40649-019-0073-2-e DE-627 ger DE-627 rakwb eng Carchiolo, Vincenza verfasserin aut Network robustness improvement via long-range links 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Abstract Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies. Complex networks (dpeaa)DE-He213 Robustness (dpeaa)DE-He213 Network attacks (dpeaa)DE-He213 Long-distance links (dpeaa)DE-He213 Grassia, Marco aut Longheu, Alessandro aut Malgeri, Michele aut Mangioni, Giuseppe aut Enthalten in Computational Social Networks New York, NY [u.a.] : Springer international, 2014 6(2019), 1 vom: 19. Nov. (DE-627)815913907 (DE-600)2806588-8 2197-4314 nnns volume:6 year:2019 number:1 day:19 month:11 https://dx.doi.org/10.1186/s40649-019-0073-2 kostenfrei 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_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2019 1 19 11 |
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10.1186/s40649-019-0073-2 doi (DE-627)SPR037115316 (SPR)s40649-019-0073-2-e DE-627 ger DE-627 rakwb eng Carchiolo, Vincenza verfasserin aut Network robustness improvement via long-range links 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Abstract Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies. Complex networks (dpeaa)DE-He213 Robustness (dpeaa)DE-He213 Network attacks (dpeaa)DE-He213 Long-distance links (dpeaa)DE-He213 Grassia, Marco aut Longheu, Alessandro aut Malgeri, Michele aut Mangioni, Giuseppe aut Enthalten in Computational Social Networks New York, NY [u.a.] : Springer international, 2014 6(2019), 1 vom: 19. Nov. (DE-627)815913907 (DE-600)2806588-8 2197-4314 nnns volume:6 year:2019 number:1 day:19 month:11 https://dx.doi.org/10.1186/s40649-019-0073-2 kostenfrei 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_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2019 1 19 11 |
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10.1186/s40649-019-0073-2 doi (DE-627)SPR037115316 (SPR)s40649-019-0073-2-e DE-627 ger DE-627 rakwb eng Carchiolo, Vincenza verfasserin aut Network robustness improvement via long-range links 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Abstract Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies. Complex networks (dpeaa)DE-He213 Robustness (dpeaa)DE-He213 Network attacks (dpeaa)DE-He213 Long-distance links (dpeaa)DE-He213 Grassia, Marco aut Longheu, Alessandro aut Malgeri, Michele aut Mangioni, Giuseppe aut Enthalten in Computational Social Networks New York, NY [u.a.] : Springer international, 2014 6(2019), 1 vom: 19. Nov. (DE-627)815913907 (DE-600)2806588-8 2197-4314 nnns volume:6 year:2019 number:1 day:19 month:11 https://dx.doi.org/10.1186/s40649-019-0073-2 kostenfrei 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_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2019 1 19 11 |
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Abstract Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies. © The Author(s) 2019 |
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Abstract Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies. © The Author(s) 2019 |
abstract_unstemmed |
Abstract Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies. © The Author(s) 2019 |
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