DOS by Dynamic Groups: a Coalition Formation Game Perspective
Abstract In this paper, the problem of distributed opportunistic scheduling by mobile users is investigated for a wireless cooperative network. Based on coalition formation game model, a theoretic framework is built in which users cooperate in accessing the shared channel in an individual view of av...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Xie, Jia [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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| Übergeordnetes Werk: |
Enthalten in: Mobile networks and applications - New York, NY : ACM, 1996, 28(2022), 1 vom: 30. Apr., Seite 334-345 |
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| Übergeordnetes Werk: |
volume:28 ; year:2022 ; number:1 ; day:30 ; month:04 ; pages:334-345 |
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| DOI / URN: |
10.1007/s11036-022-01952-4 |
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| Katalog-ID: |
SPR053008170 |
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| 520 | |a Abstract In this paper, the problem of distributed opportunistic scheduling by mobile users is investigated for a wireless cooperative network. Based on coalition formation game model, a theoretic framework is built in which users cooperate in accessing the shared channel in an individual view of average throughput. To analyze users rational behaviors, we propose a coalition formation approach which guides cooperative delivery by mobile users in distributed manner. Under the approach, users form a coalition structure in a dynamic manner, for which an optimal distributed cooperative scheduling strategy is derived maximizing average network throughput. Based on individual utilities, users make their own decisions to join or leave a coalition. To obtain a stable coalition structure, a distributed coalition formation algorithm is designed to adapt coalitions to environmental changes. The effectiveness and efficiency are verified by numerical simulations. | ||
| 650 | 4 | |a Cooperative distributed opportunistic scheduling |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Coalition formation game |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Zhang, Zhou |4 aut | |
| 700 | 1 | |a Yan, Ye |4 aut | |
| 700 | 1 | |a Zhang, Hailin |4 aut | |
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10.1007/s11036-022-01952-4 doi (DE-627)SPR053008170 (SPR)s11036-022-01952-4-e DE-627 ger DE-627 rakwb eng Xie, Jia verfasserin aut DOS by Dynamic Groups: a Coalition Formation Game Perspective 2022 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 2022 Abstract In this paper, the problem of distributed opportunistic scheduling by mobile users is investigated for a wireless cooperative network. Based on coalition formation game model, a theoretic framework is built in which users cooperate in accessing the shared channel in an individual view of average throughput. To analyze users rational behaviors, we propose a coalition formation approach which guides cooperative delivery by mobile users in distributed manner. Under the approach, users form a coalition structure in a dynamic manner, for which an optimal distributed cooperative scheduling strategy is derived maximizing average network throughput. Based on individual utilities, users make their own decisions to join or leave a coalition. To obtain a stable coalition structure, a distributed coalition formation algorithm is designed to adapt coalitions to environmental changes. The effectiveness and efficiency are verified by numerical simulations. Cooperative distributed opportunistic scheduling (dpeaa)DE-He213 Coalition formation game (dpeaa)DE-He213 Zhang, Zhou aut Yan, Ye aut Zhang, Hailin aut Enthalten in Mobile networks and applications New York, NY : ACM, 1996 28(2022), 1 vom: 30. Apr., Seite 334-345 (DE-627)318370794 (DE-600)2000637-8 1572-8153 nnns volume:28 year:2022 number:1 day:30 month:04 pages:334-345 https://dx.doi.org/10.1007/s11036-022-01952-4 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_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_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 28 2022 1 30 04 334-345 |
| spelling |
10.1007/s11036-022-01952-4 doi (DE-627)SPR053008170 (SPR)s11036-022-01952-4-e DE-627 ger DE-627 rakwb eng Xie, Jia verfasserin aut DOS by Dynamic Groups: a Coalition Formation Game Perspective 2022 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 2022 Abstract In this paper, the problem of distributed opportunistic scheduling by mobile users is investigated for a wireless cooperative network. Based on coalition formation game model, a theoretic framework is built in which users cooperate in accessing the shared channel in an individual view of average throughput. To analyze users rational behaviors, we propose a coalition formation approach which guides cooperative delivery by mobile users in distributed manner. Under the approach, users form a coalition structure in a dynamic manner, for which an optimal distributed cooperative scheduling strategy is derived maximizing average network throughput. Based on individual utilities, users make their own decisions to join or leave a coalition. To obtain a stable coalition structure, a distributed coalition formation algorithm is designed to adapt coalitions to environmental changes. The effectiveness and efficiency are verified by numerical simulations. Cooperative distributed opportunistic scheduling (dpeaa)DE-He213 Coalition formation game (dpeaa)DE-He213 Zhang, Zhou aut Yan, Ye aut Zhang, Hailin aut Enthalten in Mobile networks and applications New York, NY : ACM, 1996 28(2022), 1 vom: 30. Apr., Seite 334-345 (DE-627)318370794 (DE-600)2000637-8 1572-8153 nnns volume:28 year:2022 number:1 day:30 month:04 pages:334-345 https://dx.doi.org/10.1007/s11036-022-01952-4 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_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_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 28 2022 1 30 04 334-345 |
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10.1007/s11036-022-01952-4 doi (DE-627)SPR053008170 (SPR)s11036-022-01952-4-e DE-627 ger DE-627 rakwb eng Xie, Jia verfasserin aut DOS by Dynamic Groups: a Coalition Formation Game Perspective 2022 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 2022 Abstract In this paper, the problem of distributed opportunistic scheduling by mobile users is investigated for a wireless cooperative network. Based on coalition formation game model, a theoretic framework is built in which users cooperate in accessing the shared channel in an individual view of average throughput. To analyze users rational behaviors, we propose a coalition formation approach which guides cooperative delivery by mobile users in distributed manner. Under the approach, users form a coalition structure in a dynamic manner, for which an optimal distributed cooperative scheduling strategy is derived maximizing average network throughput. Based on individual utilities, users make their own decisions to join or leave a coalition. To obtain a stable coalition structure, a distributed coalition formation algorithm is designed to adapt coalitions to environmental changes. The effectiveness and efficiency are verified by numerical simulations. Cooperative distributed opportunistic scheduling (dpeaa)DE-He213 Coalition formation game (dpeaa)DE-He213 Zhang, Zhou aut Yan, Ye aut Zhang, Hailin aut Enthalten in Mobile networks and applications New York, NY : ACM, 1996 28(2022), 1 vom: 30. Apr., Seite 334-345 (DE-627)318370794 (DE-600)2000637-8 1572-8153 nnns volume:28 year:2022 number:1 day:30 month:04 pages:334-345 https://dx.doi.org/10.1007/s11036-022-01952-4 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_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_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 28 2022 1 30 04 334-345 |
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10.1007/s11036-022-01952-4 doi (DE-627)SPR053008170 (SPR)s11036-022-01952-4-e DE-627 ger DE-627 rakwb eng Xie, Jia verfasserin aut DOS by Dynamic Groups: a Coalition Formation Game Perspective 2022 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 2022 Abstract In this paper, the problem of distributed opportunistic scheduling by mobile users is investigated for a wireless cooperative network. Based on coalition formation game model, a theoretic framework is built in which users cooperate in accessing the shared channel in an individual view of average throughput. To analyze users rational behaviors, we propose a coalition formation approach which guides cooperative delivery by mobile users in distributed manner. Under the approach, users form a coalition structure in a dynamic manner, for which an optimal distributed cooperative scheduling strategy is derived maximizing average network throughput. Based on individual utilities, users make their own decisions to join or leave a coalition. To obtain a stable coalition structure, a distributed coalition formation algorithm is designed to adapt coalitions to environmental changes. The effectiveness and efficiency are verified by numerical simulations. Cooperative distributed opportunistic scheduling (dpeaa)DE-He213 Coalition formation game (dpeaa)DE-He213 Zhang, Zhou aut Yan, Ye aut Zhang, Hailin aut Enthalten in Mobile networks and applications New York, NY : ACM, 1996 28(2022), 1 vom: 30. Apr., Seite 334-345 (DE-627)318370794 (DE-600)2000637-8 1572-8153 nnns volume:28 year:2022 number:1 day:30 month:04 pages:334-345 https://dx.doi.org/10.1007/s11036-022-01952-4 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_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_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 28 2022 1 30 04 334-345 |
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10.1007/s11036-022-01952-4 doi (DE-627)SPR053008170 (SPR)s11036-022-01952-4-e DE-627 ger DE-627 rakwb eng Xie, Jia verfasserin aut DOS by Dynamic Groups: a Coalition Formation Game Perspective 2022 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 2022 Abstract In this paper, the problem of distributed opportunistic scheduling by mobile users is investigated for a wireless cooperative network. Based on coalition formation game model, a theoretic framework is built in which users cooperate in accessing the shared channel in an individual view of average throughput. To analyze users rational behaviors, we propose a coalition formation approach which guides cooperative delivery by mobile users in distributed manner. Under the approach, users form a coalition structure in a dynamic manner, for which an optimal distributed cooperative scheduling strategy is derived maximizing average network throughput. Based on individual utilities, users make their own decisions to join or leave a coalition. To obtain a stable coalition structure, a distributed coalition formation algorithm is designed to adapt coalitions to environmental changes. The effectiveness and efficiency are verified by numerical simulations. Cooperative distributed opportunistic scheduling (dpeaa)DE-He213 Coalition formation game (dpeaa)DE-He213 Zhang, Zhou aut Yan, Ye aut Zhang, Hailin aut Enthalten in Mobile networks and applications New York, NY : ACM, 1996 28(2022), 1 vom: 30. Apr., Seite 334-345 (DE-627)318370794 (DE-600)2000637-8 1572-8153 nnns volume:28 year:2022 number:1 day:30 month:04 pages:334-345 https://dx.doi.org/10.1007/s11036-022-01952-4 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_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_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 28 2022 1 30 04 334-345 |
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Abstract In this paper, the problem of distributed opportunistic scheduling by mobile users is investigated for a wireless cooperative network. Based on coalition formation game model, a theoretic framework is built in which users cooperate in accessing the shared channel in an individual view of average throughput. To analyze users rational behaviors, we propose a coalition formation approach which guides cooperative delivery by mobile users in distributed manner. Under the approach, users form a coalition structure in a dynamic manner, for which an optimal distributed cooperative scheduling strategy is derived maximizing average network throughput. Based on individual utilities, users make their own decisions to join or leave a coalition. To obtain a stable coalition structure, a distributed coalition formation algorithm is designed to adapt coalitions to environmental changes. The effectiveness and efficiency are verified by numerical simulations. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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Abstract In this paper, the problem of distributed opportunistic scheduling by mobile users is investigated for a wireless cooperative network. Based on coalition formation game model, a theoretic framework is built in which users cooperate in accessing the shared channel in an individual view of average throughput. To analyze users rational behaviors, we propose a coalition formation approach which guides cooperative delivery by mobile users in distributed manner. Under the approach, users form a coalition structure in a dynamic manner, for which an optimal distributed cooperative scheduling strategy is derived maximizing average network throughput. Based on individual utilities, users make their own decisions to join or leave a coalition. To obtain a stable coalition structure, a distributed coalition formation algorithm is designed to adapt coalitions to environmental changes. The effectiveness and efficiency are verified by numerical simulations. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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Abstract In this paper, the problem of distributed opportunistic scheduling by mobile users is investigated for a wireless cooperative network. Based on coalition formation game model, a theoretic framework is built in which users cooperate in accessing the shared channel in an individual view of average throughput. To analyze users rational behaviors, we propose a coalition formation approach which guides cooperative delivery by mobile users in distributed manner. Under the approach, users form a coalition structure in a dynamic manner, for which an optimal distributed cooperative scheduling strategy is derived maximizing average network throughput. Based on individual utilities, users make their own decisions to join or leave a coalition. To obtain a stable coalition structure, a distributed coalition formation algorithm is designed to adapt coalitions to environmental changes. The effectiveness and efficiency are verified by numerical simulations. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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Based on coalition formation game model, a theoretic framework is built in which users cooperate in accessing the shared channel in an individual view of average throughput. To analyze users rational behaviors, we propose a coalition formation approach which guides cooperative delivery by mobile users in distributed manner. Under the approach, users form a coalition structure in a dynamic manner, for which an optimal distributed cooperative scheduling strategy is derived maximizing average network throughput. Based on individual utilities, users make their own decisions to join or leave a coalition. To obtain a stable coalition structure, a distributed coalition formation algorithm is designed to adapt coalitions to environmental changes. 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Apr., Seite 334-345</subfield><subfield code="w">(DE-627)318370794</subfield><subfield code="w">(DE-600)2000637-8</subfield><subfield code="x">1572-8153</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:28</subfield><subfield code="g">year:2022</subfield><subfield code="g">number:1</subfield><subfield code="g">day:30</subfield><subfield code="g">month:04</subfield><subfield code="g">pages:334-345</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s11036-022-01952-4</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" 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