Survey on the scheme evaluation, opportunities and challenges of software defined‐information centric network
Abstract As a promising architecture of next‐generation network, software defined‐information centric network (SD‐ICN) inherits the advantages of software defined network (SDN) and information‐centric network (ICN) to enable flexible and fast content retrieval, especially in the current era of artif...
Ausführliche Beschreibung
Autor*in: |
Zhengyang Ai [verfasserIn] Ming Zhang [verfasserIn] Weiting Zhang [verfasserIn] Jiawen Kang [verfasserIn] Lingling Tong [verfasserIn] Yunqiang Duan [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2023 |
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Übergeordnetes Werk: |
In: IET Communications - Wiley, 2021, 17(2023), 20, Seite 2237-2274 |
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Übergeordnetes Werk: |
volume:17 ; year:2023 ; number:20 ; pages:2237-2274 |
Links: |
Link aufrufen |
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DOI / URN: |
10.1049/cmu2.12694 |
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Katalog-ID: |
DOAJ09904823X |
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10.1049/cmu2.12694 doi (DE-627)DOAJ09904823X (DE-599)DOAJ92fa54f749ae49308055baedf7e35c70 DE-627 ger DE-627 rakwb eng TK5101-6720 Zhengyang Ai verfasserin aut Survey on the scheme evaluation, opportunities and challenges of software defined‐information centric network 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract As a promising architecture of next‐generation network, software defined‐information centric network (SD‐ICN) inherits the advantages of software defined network (SDN) and information‐centric network (ICN) to enable flexible and fast content retrieval, especially in the current era of artificial intelligence. However, the existing researches mainly focus on a single respective in this field, which motivates in comprehensively providing a forward‐looking guidance and development direction for scholars and engineers. To this end, the latest developments of SD‐ICN is presented. First, the widely‐accepted concepts and impacts on traditional networks are introduced. Second, the shortcomings of SDN and ICN over conventional networks are respectively analyzed to illustrate the necessity of SD‐ICN. Third, based on extensive analysis and deep deliberation, a methodical taxonomy for existing combination studies is proposed. They are divided into SDN over ICN, ICN over SDN, and mutual immersive pattern. Fourth, the performances of three integration categories are compared and the limitations of related works are highlighted. Fifth, the maturity index from six development indicators are evaluated. Further, the maturity and practicality of these schemes are generalized. Based on the above studies and comparisons, the lessons learned by SDN and ICN developments are concluded. Finally, future research directions and opportunities are discussed for the readers. computer networks next generation networks Telecommunication Ming Zhang verfasserin aut Weiting Zhang verfasserin aut Jiawen Kang verfasserin aut Lingling Tong verfasserin aut Yunqiang Duan verfasserin aut In IET Communications Wiley, 2021 17(2023), 20, Seite 2237-2274 (DE-627)521691621 (DE-600)2264240-7 17518636 nnns volume:17 year:2023 number:20 pages:2237-2274 https://doi.org/10.1049/cmu2.12694 kostenfrei https://doaj.org/article/92fa54f749ae49308055baedf7e35c70 kostenfrei https://doi.org/10.1049/cmu2.12694 kostenfrei https://doaj.org/toc/1751-8628 Journal toc kostenfrei https://doaj.org/toc/1751-8636 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 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_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 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_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 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_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 17 2023 20 2237-2274 |
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10.1049/cmu2.12694 doi (DE-627)DOAJ09904823X (DE-599)DOAJ92fa54f749ae49308055baedf7e35c70 DE-627 ger DE-627 rakwb eng TK5101-6720 Zhengyang Ai verfasserin aut Survey on the scheme evaluation, opportunities and challenges of software defined‐information centric network 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract As a promising architecture of next‐generation network, software defined‐information centric network (SD‐ICN) inherits the advantages of software defined network (SDN) and information‐centric network (ICN) to enable flexible and fast content retrieval, especially in the current era of artificial intelligence. However, the existing researches mainly focus on a single respective in this field, which motivates in comprehensively providing a forward‐looking guidance and development direction for scholars and engineers. To this end, the latest developments of SD‐ICN is presented. First, the widely‐accepted concepts and impacts on traditional networks are introduced. Second, the shortcomings of SDN and ICN over conventional networks are respectively analyzed to illustrate the necessity of SD‐ICN. Third, based on extensive analysis and deep deliberation, a methodical taxonomy for existing combination studies is proposed. They are divided into SDN over ICN, ICN over SDN, and mutual immersive pattern. Fourth, the performances of three integration categories are compared and the limitations of related works are highlighted. Fifth, the maturity index from six development indicators are evaluated. Further, the maturity and practicality of these schemes are generalized. Based on the above studies and comparisons, the lessons learned by SDN and ICN developments are concluded. Finally, future research directions and opportunities are discussed for the readers. computer networks next generation networks Telecommunication Ming Zhang verfasserin aut Weiting Zhang verfasserin aut Jiawen Kang verfasserin aut Lingling Tong verfasserin aut Yunqiang Duan verfasserin aut In IET Communications Wiley, 2021 17(2023), 20, Seite 2237-2274 (DE-627)521691621 (DE-600)2264240-7 17518636 nnns volume:17 year:2023 number:20 pages:2237-2274 https://doi.org/10.1049/cmu2.12694 kostenfrei https://doaj.org/article/92fa54f749ae49308055baedf7e35c70 kostenfrei https://doi.org/10.1049/cmu2.12694 kostenfrei https://doaj.org/toc/1751-8628 Journal toc kostenfrei https://doaj.org/toc/1751-8636 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 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_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 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_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 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_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 17 2023 20 2237-2274 |
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Survey on the scheme evaluation, opportunities and challenges of software defined‐information centric network |
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Abstract As a promising architecture of next‐generation network, software defined‐information centric network (SD‐ICN) inherits the advantages of software defined network (SDN) and information‐centric network (ICN) to enable flexible and fast content retrieval, especially in the current era of artificial intelligence. However, the existing researches mainly focus on a single respective in this field, which motivates in comprehensively providing a forward‐looking guidance and development direction for scholars and engineers. To this end, the latest developments of SD‐ICN is presented. First, the widely‐accepted concepts and impacts on traditional networks are introduced. Second, the shortcomings of SDN and ICN over conventional networks are respectively analyzed to illustrate the necessity of SD‐ICN. Third, based on extensive analysis and deep deliberation, a methodical taxonomy for existing combination studies is proposed. They are divided into SDN over ICN, ICN over SDN, and mutual immersive pattern. Fourth, the performances of three integration categories are compared and the limitations of related works are highlighted. Fifth, the maturity index from six development indicators are evaluated. Further, the maturity and practicality of these schemes are generalized. Based on the above studies and comparisons, the lessons learned by SDN and ICN developments are concluded. Finally, future research directions and opportunities are discussed for the readers. |
abstractGer |
Abstract As a promising architecture of next‐generation network, software defined‐information centric network (SD‐ICN) inherits the advantages of software defined network (SDN) and information‐centric network (ICN) to enable flexible and fast content retrieval, especially in the current era of artificial intelligence. However, the existing researches mainly focus on a single respective in this field, which motivates in comprehensively providing a forward‐looking guidance and development direction for scholars and engineers. To this end, the latest developments of SD‐ICN is presented. First, the widely‐accepted concepts and impacts on traditional networks are introduced. Second, the shortcomings of SDN and ICN over conventional networks are respectively analyzed to illustrate the necessity of SD‐ICN. Third, based on extensive analysis and deep deliberation, a methodical taxonomy for existing combination studies is proposed. They are divided into SDN over ICN, ICN over SDN, and mutual immersive pattern. Fourth, the performances of three integration categories are compared and the limitations of related works are highlighted. Fifth, the maturity index from six development indicators are evaluated. Further, the maturity and practicality of these schemes are generalized. Based on the above studies and comparisons, the lessons learned by SDN and ICN developments are concluded. Finally, future research directions and opportunities are discussed for the readers. |
abstract_unstemmed |
Abstract As a promising architecture of next‐generation network, software defined‐information centric network (SD‐ICN) inherits the advantages of software defined network (SDN) and information‐centric network (ICN) to enable flexible and fast content retrieval, especially in the current era of artificial intelligence. However, the existing researches mainly focus on a single respective in this field, which motivates in comprehensively providing a forward‐looking guidance and development direction for scholars and engineers. To this end, the latest developments of SD‐ICN is presented. First, the widely‐accepted concepts and impacts on traditional networks are introduced. Second, the shortcomings of SDN and ICN over conventional networks are respectively analyzed to illustrate the necessity of SD‐ICN. Third, based on extensive analysis and deep deliberation, a methodical taxonomy for existing combination studies is proposed. They are divided into SDN over ICN, ICN over SDN, and mutual immersive pattern. Fourth, the performances of three integration categories are compared and the limitations of related works are highlighted. Fifth, the maturity index from six development indicators are evaluated. Further, the maturity and practicality of these schemes are generalized. Based on the above studies and comparisons, the lessons learned by SDN and ICN developments are concluded. Finally, future research directions and opportunities are discussed for the readers. |
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However, the existing researches mainly focus on a single respective in this field, which motivates in comprehensively providing a forward‐looking guidance and development direction for scholars and engineers. To this end, the latest developments of SD‐ICN is presented. First, the widely‐accepted concepts and impacts on traditional networks are introduced. Second, the shortcomings of SDN and ICN over conventional networks are respectively analyzed to illustrate the necessity of SD‐ICN. Third, based on extensive analysis and deep deliberation, a methodical taxonomy for existing combination studies is proposed. They are divided into SDN over ICN, ICN over SDN, and mutual immersive pattern. Fourth, the performances of three integration categories are compared and the limitations of related works are highlighted. Fifth, the maturity index from six development indicators are evaluated. Further, the maturity and practicality of these schemes are generalized. Based on the above studies and comparisons, the lessons learned by SDN and ICN developments are concluded. 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