WoS-CoMS: Work Stealing-Based Congestion Management Scheme for SDN Programmable Networks
Abstract In recent years, the software-defined networking (SDN) paradigm emerged as an easy way to manage large-scale network infrastructures through programmability brought out and its control plane/data plane decoupling logic. This allows infrastructure and service providers to better deploy, conf...
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| Autor*in: |
Yankam, Yannick Florian [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2024 |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Journal of network and systems management - Dordrecht [u.a.] : Springer Science + Business Media, 1993, 32(2024), 1 vom: Jan. |
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| Übergeordnetes Werk: |
volume:32 ; year:2024 ; number:1 ; month:01 |
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| DOI / URN: |
10.1007/s10922-023-09798-1 |
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| Katalog-ID: |
SPR054381657 |
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| 520 | |a Abstract In recent years, the software-defined networking (SDN) paradigm emerged as an easy way to manage large-scale network infrastructures through programmability brought out and its control plane/data plane decoupling logic. This allows infrastructure and service providers to better deploy, configure and automate their traffic management policies and network equipments. However, congestion control remains a concern due to the evolution of increasingly complex and resource-intensive user requirements [(virtual reality, metaverse, Internet of Things (IoT), Artificial Intelligence (AI), Cloud,...] on network infrastructures. This server state leads to high latency in request processing and data loss. This paper proposes, in such a controller-supervised environment, a congestion management scheme within network service servers to maintain an acceptable quality of service. The strategy relies on work stealing to ensure a better workload balance. Simulations show that the proposed solution can reduce congestion load on the servers by up to 22%, depending on the request grain size, with shorter latency than other works in the literature. Moreover, the proposed solution allows stolen tasks to be completed within a shorter time frame. | ||
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| 650 | 4 | |a Congestion control |7 (dpeaa)DE-He213 | |
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| 650 | 4 | |a Task scheduling |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Quality of service |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Tchendji, Vianney Kengne |0 (orcid)0000-0003-3836-1859 |4 aut | |
| 700 | 1 | |a Myoupo, Jean Frédéric |0 (orcid)0000-0003-3657-2556 |4 aut | |
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10.1007/s10922-023-09798-1 doi (DE-627)SPR054381657 (SPR)s10922-023-09798-1-e DE-627 ger DE-627 rakwb eng Yankam, Yannick Florian verfasserin (orcid)0000-0001-6002-9719 aut WoS-CoMS: Work Stealing-Based Congestion Management Scheme for SDN Programmable Networks 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In recent years, the software-defined networking (SDN) paradigm emerged as an easy way to manage large-scale network infrastructures through programmability brought out and its control plane/data plane decoupling logic. This allows infrastructure and service providers to better deploy, configure and automate their traffic management policies and network equipments. However, congestion control remains a concern due to the evolution of increasingly complex and resource-intensive user requirements [(virtual reality, metaverse, Internet of Things (IoT), Artificial Intelligence (AI), Cloud,...] on network infrastructures. This server state leads to high latency in request processing and data loss. This paper proposes, in such a controller-supervised environment, a congestion management scheme within network service servers to maintain an acceptable quality of service. The strategy relies on work stealing to ensure a better workload balance. Simulations show that the proposed solution can reduce congestion load on the servers by up to 22%, depending on the request grain size, with shorter latency than other works in the literature. Moreover, the proposed solution allows stolen tasks to be completed within a shorter time frame. Work stealing (dpeaa)DE-He213 Congestion control (dpeaa)DE-He213 SDN (dpeaa)DE-He213 Task scheduling (dpeaa)DE-He213 Quality of service (dpeaa)DE-He213 Tchendji, Vianney Kengne (orcid)0000-0003-3836-1859 aut Myoupo, Jean Frédéric (orcid)0000-0003-3657-2556 aut Enthalten in Journal of network and systems management Dordrecht [u.a.] : Springer Science + Business Media, 1993 32(2024), 1 vom: Jan. (DE-627)320575756 (DE-600)2017028-2 1573-7705 nnns volume:32 year:2024 number:1 month:01 https://dx.doi.org/10.1007/s10922-023-09798-1 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_101 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_1200 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_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_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 AR 32 2024 1 01 |
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10.1007/s10922-023-09798-1 doi (DE-627)SPR054381657 (SPR)s10922-023-09798-1-e DE-627 ger DE-627 rakwb eng Yankam, Yannick Florian verfasserin (orcid)0000-0001-6002-9719 aut WoS-CoMS: Work Stealing-Based Congestion Management Scheme for SDN Programmable Networks 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In recent years, the software-defined networking (SDN) paradigm emerged as an easy way to manage large-scale network infrastructures through programmability brought out and its control plane/data plane decoupling logic. This allows infrastructure and service providers to better deploy, configure and automate their traffic management policies and network equipments. However, congestion control remains a concern due to the evolution of increasingly complex and resource-intensive user requirements [(virtual reality, metaverse, Internet of Things (IoT), Artificial Intelligence (AI), Cloud,...] on network infrastructures. This server state leads to high latency in request processing and data loss. This paper proposes, in such a controller-supervised environment, a congestion management scheme within network service servers to maintain an acceptable quality of service. The strategy relies on work stealing to ensure a better workload balance. Simulations show that the proposed solution can reduce congestion load on the servers by up to 22%, depending on the request grain size, with shorter latency than other works in the literature. Moreover, the proposed solution allows stolen tasks to be completed within a shorter time frame. Work stealing (dpeaa)DE-He213 Congestion control (dpeaa)DE-He213 SDN (dpeaa)DE-He213 Task scheduling (dpeaa)DE-He213 Quality of service (dpeaa)DE-He213 Tchendji, Vianney Kengne (orcid)0000-0003-3836-1859 aut Myoupo, Jean Frédéric (orcid)0000-0003-3657-2556 aut Enthalten in Journal of network and systems management Dordrecht [u.a.] : Springer Science + Business Media, 1993 32(2024), 1 vom: Jan. (DE-627)320575756 (DE-600)2017028-2 1573-7705 nnns volume:32 year:2024 number:1 month:01 https://dx.doi.org/10.1007/s10922-023-09798-1 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_101 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_1200 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_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_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 AR 32 2024 1 01 |
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10.1007/s10922-023-09798-1 doi (DE-627)SPR054381657 (SPR)s10922-023-09798-1-e DE-627 ger DE-627 rakwb eng Yankam, Yannick Florian verfasserin (orcid)0000-0001-6002-9719 aut WoS-CoMS: Work Stealing-Based Congestion Management Scheme for SDN Programmable Networks 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In recent years, the software-defined networking (SDN) paradigm emerged as an easy way to manage large-scale network infrastructures through programmability brought out and its control plane/data plane decoupling logic. This allows infrastructure and service providers to better deploy, configure and automate their traffic management policies and network equipments. However, congestion control remains a concern due to the evolution of increasingly complex and resource-intensive user requirements [(virtual reality, metaverse, Internet of Things (IoT), Artificial Intelligence (AI), Cloud,...] on network infrastructures. This server state leads to high latency in request processing and data loss. This paper proposes, in such a controller-supervised environment, a congestion management scheme within network service servers to maintain an acceptable quality of service. The strategy relies on work stealing to ensure a better workload balance. Simulations show that the proposed solution can reduce congestion load on the servers by up to 22%, depending on the request grain size, with shorter latency than other works in the literature. Moreover, the proposed solution allows stolen tasks to be completed within a shorter time frame. Work stealing (dpeaa)DE-He213 Congestion control (dpeaa)DE-He213 SDN (dpeaa)DE-He213 Task scheduling (dpeaa)DE-He213 Quality of service (dpeaa)DE-He213 Tchendji, Vianney Kengne (orcid)0000-0003-3836-1859 aut Myoupo, Jean Frédéric (orcid)0000-0003-3657-2556 aut Enthalten in Journal of network and systems management Dordrecht [u.a.] : Springer Science + Business Media, 1993 32(2024), 1 vom: Jan. (DE-627)320575756 (DE-600)2017028-2 1573-7705 nnns volume:32 year:2024 number:1 month:01 https://dx.doi.org/10.1007/s10922-023-09798-1 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_101 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_1200 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_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_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 AR 32 2024 1 01 |
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10.1007/s10922-023-09798-1 doi (DE-627)SPR054381657 (SPR)s10922-023-09798-1-e DE-627 ger DE-627 rakwb eng Yankam, Yannick Florian verfasserin (orcid)0000-0001-6002-9719 aut WoS-CoMS: Work Stealing-Based Congestion Management Scheme for SDN Programmable Networks 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In recent years, the software-defined networking (SDN) paradigm emerged as an easy way to manage large-scale network infrastructures through programmability brought out and its control plane/data plane decoupling logic. This allows infrastructure and service providers to better deploy, configure and automate their traffic management policies and network equipments. However, congestion control remains a concern due to the evolution of increasingly complex and resource-intensive user requirements [(virtual reality, metaverse, Internet of Things (IoT), Artificial Intelligence (AI), Cloud,...] on network infrastructures. This server state leads to high latency in request processing and data loss. This paper proposes, in such a controller-supervised environment, a congestion management scheme within network service servers to maintain an acceptable quality of service. The strategy relies on work stealing to ensure a better workload balance. Simulations show that the proposed solution can reduce congestion load on the servers by up to 22%, depending on the request grain size, with shorter latency than other works in the literature. Moreover, the proposed solution allows stolen tasks to be completed within a shorter time frame. Work stealing (dpeaa)DE-He213 Congestion control (dpeaa)DE-He213 SDN (dpeaa)DE-He213 Task scheduling (dpeaa)DE-He213 Quality of service (dpeaa)DE-He213 Tchendji, Vianney Kengne (orcid)0000-0003-3836-1859 aut Myoupo, Jean Frédéric (orcid)0000-0003-3657-2556 aut Enthalten in Journal of network and systems management Dordrecht [u.a.] : Springer Science + Business Media, 1993 32(2024), 1 vom: Jan. (DE-627)320575756 (DE-600)2017028-2 1573-7705 nnns volume:32 year:2024 number:1 month:01 https://dx.doi.org/10.1007/s10922-023-09798-1 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_101 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_1200 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_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_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 AR 32 2024 1 01 |
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10.1007/s10922-023-09798-1 doi (DE-627)SPR054381657 (SPR)s10922-023-09798-1-e DE-627 ger DE-627 rakwb eng Yankam, Yannick Florian verfasserin (orcid)0000-0001-6002-9719 aut WoS-CoMS: Work Stealing-Based Congestion Management Scheme for SDN Programmable Networks 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In recent years, the software-defined networking (SDN) paradigm emerged as an easy way to manage large-scale network infrastructures through programmability brought out and its control plane/data plane decoupling logic. This allows infrastructure and service providers to better deploy, configure and automate their traffic management policies and network equipments. However, congestion control remains a concern due to the evolution of increasingly complex and resource-intensive user requirements [(virtual reality, metaverse, Internet of Things (IoT), Artificial Intelligence (AI), Cloud,...] on network infrastructures. This server state leads to high latency in request processing and data loss. This paper proposes, in such a controller-supervised environment, a congestion management scheme within network service servers to maintain an acceptable quality of service. The strategy relies on work stealing to ensure a better workload balance. Simulations show that the proposed solution can reduce congestion load on the servers by up to 22%, depending on the request grain size, with shorter latency than other works in the literature. Moreover, the proposed solution allows stolen tasks to be completed within a shorter time frame. Work stealing (dpeaa)DE-He213 Congestion control (dpeaa)DE-He213 SDN (dpeaa)DE-He213 Task scheduling (dpeaa)DE-He213 Quality of service (dpeaa)DE-He213 Tchendji, Vianney Kengne (orcid)0000-0003-3836-1859 aut Myoupo, Jean Frédéric (orcid)0000-0003-3657-2556 aut Enthalten in Journal of network and systems management Dordrecht [u.a.] : Springer Science + Business Media, 1993 32(2024), 1 vom: Jan. (DE-627)320575756 (DE-600)2017028-2 1573-7705 nnns volume:32 year:2024 number:1 month:01 https://dx.doi.org/10.1007/s10922-023-09798-1 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_101 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_1200 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_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_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 AR 32 2024 1 01 |
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wos-coms: work stealing-based congestion management scheme for sdn programmable networks |
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WoS-CoMS: Work Stealing-Based Congestion Management Scheme for SDN Programmable Networks |
| abstract |
Abstract In recent years, the software-defined networking (SDN) paradigm emerged as an easy way to manage large-scale network infrastructures through programmability brought out and its control plane/data plane decoupling logic. This allows infrastructure and service providers to better deploy, configure and automate their traffic management policies and network equipments. However, congestion control remains a concern due to the evolution of increasingly complex and resource-intensive user requirements [(virtual reality, metaverse, Internet of Things (IoT), Artificial Intelligence (AI), Cloud,...] on network infrastructures. This server state leads to high latency in request processing and data loss. This paper proposes, in such a controller-supervised environment, a congestion management scheme within network service servers to maintain an acceptable quality of service. The strategy relies on work stealing to ensure a better workload balance. Simulations show that the proposed solution can reduce congestion load on the servers by up to 22%, depending on the request grain size, with shorter latency than other works in the literature. Moreover, the proposed solution allows stolen tasks to be completed within a shorter time frame. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract In recent years, the software-defined networking (SDN) paradigm emerged as an easy way to manage large-scale network infrastructures through programmability brought out and its control plane/data plane decoupling logic. This allows infrastructure and service providers to better deploy, configure and automate their traffic management policies and network equipments. However, congestion control remains a concern due to the evolution of increasingly complex and resource-intensive user requirements [(virtual reality, metaverse, Internet of Things (IoT), Artificial Intelligence (AI), Cloud,...] on network infrastructures. This server state leads to high latency in request processing and data loss. This paper proposes, in such a controller-supervised environment, a congestion management scheme within network service servers to maintain an acceptable quality of service. The strategy relies on work stealing to ensure a better workload balance. Simulations show that the proposed solution can reduce congestion load on the servers by up to 22%, depending on the request grain size, with shorter latency than other works in the literature. Moreover, the proposed solution allows stolen tasks to be completed within a shorter time frame. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract In recent years, the software-defined networking (SDN) paradigm emerged as an easy way to manage large-scale network infrastructures through programmability brought out and its control plane/data plane decoupling logic. This allows infrastructure and service providers to better deploy, configure and automate their traffic management policies and network equipments. However, congestion control remains a concern due to the evolution of increasingly complex and resource-intensive user requirements [(virtual reality, metaverse, Internet of Things (IoT), Artificial Intelligence (AI), Cloud,...] on network infrastructures. This server state leads to high latency in request processing and data loss. This paper proposes, in such a controller-supervised environment, a congestion management scheme within network service servers to maintain an acceptable quality of service. The strategy relies on work stealing to ensure a better workload balance. Simulations show that the proposed solution can reduce congestion load on the servers by up to 22%, depending on the request grain size, with shorter latency than other works in the literature. Moreover, the proposed solution allows stolen tasks to be completed within a shorter time frame. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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WoS-CoMS: Work Stealing-Based Congestion Management Scheme for SDN Programmable Networks |
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https://dx.doi.org/10.1007/s10922-023-09798-1 |
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Tchendji, Vianney Kengne Myoupo, Jean Frédéric |
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Tchendji, Vianney Kengne Myoupo, Jean Frédéric |
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10.1007/s10922-023-09798-1 |
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2024-07-04T01:20:28.655Z |
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| score |
7.3998976 |