A bipartite model for load balancing in grid computing environments
Abstract In this paper, a bipartite model for load balancing (LB) in grid computing environments, called Transverse viewpoint-based Bi-Tier model (TBT), is proposed. TBT can efficiently eliminate topology mismatching between overlay- and physical-networks during the load transfer process. As an impl...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Jiang, Wenchao [verfasserIn] Baumgarten, Matthias [verfasserIn] Zhou, Yanhong [verfasserIn] Jin, Hai [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2009 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Frontiers of computer science in China - Beijing : Higher Education Press, 2007, 3(2009), 4 vom: 22. Okt. |
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| Übergeordnetes Werk: |
volume:3 ; year:2009 ; number:4 ; day:22 ; month:10 |
| Links: |
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| DOI / URN: |
10.1007/s11704-009-0036-0 |
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| Katalog-ID: |
SPR021934452 |
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| 245 | 1 | 2 | |a A bipartite model for load balancing in grid computing environments |
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| 520 | |a Abstract In this paper, a bipartite model for load balancing (LB) in grid computing environments, called Transverse viewpoint-based Bi-Tier model (TBT), is proposed. TBT can efficiently eliminate topology mismatching between overlay- and physical-networks during the load transfer process. As an implementation of TBT, a novel LB policy called $ M^{2} $ON (Min-cost and Max-flow Channel based Overlay Network) is presented. In $ M^{2} $ON, the communication capability is denoted as $ M^{2} $C (Min-cost and Max-flow Channel) which is obtained using a Labeled Tree Probing (LTP) method. The computing capacity is denoted as the Idle Factor (IF) which is obtained from the semantic overlay. The higher- and lower-level characteristics are combined into an Integrated Impacting Factor (IIF) using a Double Linear Inserting (DLI) function. Based on IIF, optimal topology matching can be achieved in the LB process. Extensive experiments and simulations have been performed and will be discussed. The results show that $ M^{2} $ON achieves more accurate topology matching with a minimum increment in the overall locating time yet achieving higher system performance as a whole. | ||
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| 650 | 4 | |a load balancing (LB) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a min-cost and max-flow channel (M |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a C) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a topology mismatching |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a labeled tree probing (LTP) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a double linear inserting (DLI) |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Baumgarten, Matthias |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Yanhong |e verfasserin |4 aut | |
| 700 | 1 | |a Jin, Hai |e verfasserin |4 aut | |
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10.1007/s11704-009-0036-0 doi (DE-627)SPR021934452 (SPR)s11704-009-0036-0-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Jiang, Wenchao verfasserin aut A bipartite model for load balancing in grid computing environments 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper, a bipartite model for load balancing (LB) in grid computing environments, called Transverse viewpoint-based Bi-Tier model (TBT), is proposed. TBT can efficiently eliminate topology mismatching between overlay- and physical-networks during the load transfer process. As an implementation of TBT, a novel LB policy called $ M^{2} $ON (Min-cost and Max-flow Channel based Overlay Network) is presented. In $ M^{2} $ON, the communication capability is denoted as $ M^{2} $C (Min-cost and Max-flow Channel) which is obtained using a Labeled Tree Probing (LTP) method. The computing capacity is denoted as the Idle Factor (IF) which is obtained from the semantic overlay. The higher- and lower-level characteristics are combined into an Integrated Impacting Factor (IIF) using a Double Linear Inserting (DLI) function. Based on IIF, optimal topology matching can be achieved in the LB process. Extensive experiments and simulations have been performed and will be discussed. The results show that $ M^{2} $ON achieves more accurate topology matching with a minimum increment in the overall locating time yet achieving higher system performance as a whole. grid computing (dpeaa)DE-He213 load balancing (LB) (dpeaa)DE-He213 min-cost and max-flow channel (M (dpeaa)DE-He213 C) (dpeaa)DE-He213 topology mismatching (dpeaa)DE-He213 labeled tree probing (LTP) (dpeaa)DE-He213 double linear inserting (DLI) (dpeaa)DE-He213 Baumgarten, Matthias verfasserin aut Zhou, Yanhong verfasserin aut Jin, Hai verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 3(2009), 4 vom: 22. Okt. (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:3 year:2009 number:4 day:22 month:10 https://dx.doi.org/10.1007/s11704-009-0036-0 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_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_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_266 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.00 ASE AR 3 2009 4 22 10 |
| spelling |
10.1007/s11704-009-0036-0 doi (DE-627)SPR021934452 (SPR)s11704-009-0036-0-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Jiang, Wenchao verfasserin aut A bipartite model for load balancing in grid computing environments 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper, a bipartite model for load balancing (LB) in grid computing environments, called Transverse viewpoint-based Bi-Tier model (TBT), is proposed. TBT can efficiently eliminate topology mismatching between overlay- and physical-networks during the load transfer process. As an implementation of TBT, a novel LB policy called $ M^{2} $ON (Min-cost and Max-flow Channel based Overlay Network) is presented. In $ M^{2} $ON, the communication capability is denoted as $ M^{2} $C (Min-cost and Max-flow Channel) which is obtained using a Labeled Tree Probing (LTP) method. The computing capacity is denoted as the Idle Factor (IF) which is obtained from the semantic overlay. The higher- and lower-level characteristics are combined into an Integrated Impacting Factor (IIF) using a Double Linear Inserting (DLI) function. Based on IIF, optimal topology matching can be achieved in the LB process. Extensive experiments and simulations have been performed and will be discussed. The results show that $ M^{2} $ON achieves more accurate topology matching with a minimum increment in the overall locating time yet achieving higher system performance as a whole. grid computing (dpeaa)DE-He213 load balancing (LB) (dpeaa)DE-He213 min-cost and max-flow channel (M (dpeaa)DE-He213 C) (dpeaa)DE-He213 topology mismatching (dpeaa)DE-He213 labeled tree probing (LTP) (dpeaa)DE-He213 double linear inserting (DLI) (dpeaa)DE-He213 Baumgarten, Matthias verfasserin aut Zhou, Yanhong verfasserin aut Jin, Hai verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 3(2009), 4 vom: 22. Okt. (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:3 year:2009 number:4 day:22 month:10 https://dx.doi.org/10.1007/s11704-009-0036-0 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_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_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_266 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.00 ASE AR 3 2009 4 22 10 |
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10.1007/s11704-009-0036-0 doi (DE-627)SPR021934452 (SPR)s11704-009-0036-0-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Jiang, Wenchao verfasserin aut A bipartite model for load balancing in grid computing environments 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper, a bipartite model for load balancing (LB) in grid computing environments, called Transverse viewpoint-based Bi-Tier model (TBT), is proposed. TBT can efficiently eliminate topology mismatching between overlay- and physical-networks during the load transfer process. As an implementation of TBT, a novel LB policy called $ M^{2} $ON (Min-cost and Max-flow Channel based Overlay Network) is presented. In $ M^{2} $ON, the communication capability is denoted as $ M^{2} $C (Min-cost and Max-flow Channel) which is obtained using a Labeled Tree Probing (LTP) method. The computing capacity is denoted as the Idle Factor (IF) which is obtained from the semantic overlay. The higher- and lower-level characteristics are combined into an Integrated Impacting Factor (IIF) using a Double Linear Inserting (DLI) function. Based on IIF, optimal topology matching can be achieved in the LB process. Extensive experiments and simulations have been performed and will be discussed. The results show that $ M^{2} $ON achieves more accurate topology matching with a minimum increment in the overall locating time yet achieving higher system performance as a whole. grid computing (dpeaa)DE-He213 load balancing (LB) (dpeaa)DE-He213 min-cost and max-flow channel (M (dpeaa)DE-He213 C) (dpeaa)DE-He213 topology mismatching (dpeaa)DE-He213 labeled tree probing (LTP) (dpeaa)DE-He213 double linear inserting (DLI) (dpeaa)DE-He213 Baumgarten, Matthias verfasserin aut Zhou, Yanhong verfasserin aut Jin, Hai verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 3(2009), 4 vom: 22. Okt. (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:3 year:2009 number:4 day:22 month:10 https://dx.doi.org/10.1007/s11704-009-0036-0 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_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_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_266 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.00 ASE AR 3 2009 4 22 10 |
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10.1007/s11704-009-0036-0 doi (DE-627)SPR021934452 (SPR)s11704-009-0036-0-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Jiang, Wenchao verfasserin aut A bipartite model for load balancing in grid computing environments 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper, a bipartite model for load balancing (LB) in grid computing environments, called Transverse viewpoint-based Bi-Tier model (TBT), is proposed. TBT can efficiently eliminate topology mismatching between overlay- and physical-networks during the load transfer process. As an implementation of TBT, a novel LB policy called $ M^{2} $ON (Min-cost and Max-flow Channel based Overlay Network) is presented. In $ M^{2} $ON, the communication capability is denoted as $ M^{2} $C (Min-cost and Max-flow Channel) which is obtained using a Labeled Tree Probing (LTP) method. The computing capacity is denoted as the Idle Factor (IF) which is obtained from the semantic overlay. The higher- and lower-level characteristics are combined into an Integrated Impacting Factor (IIF) using a Double Linear Inserting (DLI) function. Based on IIF, optimal topology matching can be achieved in the LB process. Extensive experiments and simulations have been performed and will be discussed. The results show that $ M^{2} $ON achieves more accurate topology matching with a minimum increment in the overall locating time yet achieving higher system performance as a whole. grid computing (dpeaa)DE-He213 load balancing (LB) (dpeaa)DE-He213 min-cost and max-flow channel (M (dpeaa)DE-He213 C) (dpeaa)DE-He213 topology mismatching (dpeaa)DE-He213 labeled tree probing (LTP) (dpeaa)DE-He213 double linear inserting (DLI) (dpeaa)DE-He213 Baumgarten, Matthias verfasserin aut Zhou, Yanhong verfasserin aut Jin, Hai verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 3(2009), 4 vom: 22. Okt. (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:3 year:2009 number:4 day:22 month:10 https://dx.doi.org/10.1007/s11704-009-0036-0 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_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_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_266 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.00 ASE AR 3 2009 4 22 10 |
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10.1007/s11704-009-0036-0 doi (DE-627)SPR021934452 (SPR)s11704-009-0036-0-e DE-627 ger DE-627 rakwb eng 004 ASE 54.00 bkl Jiang, Wenchao verfasserin aut A bipartite model for load balancing in grid computing environments 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper, a bipartite model for load balancing (LB) in grid computing environments, called Transverse viewpoint-based Bi-Tier model (TBT), is proposed. TBT can efficiently eliminate topology mismatching between overlay- and physical-networks during the load transfer process. As an implementation of TBT, a novel LB policy called $ M^{2} $ON (Min-cost and Max-flow Channel based Overlay Network) is presented. In $ M^{2} $ON, the communication capability is denoted as $ M^{2} $C (Min-cost and Max-flow Channel) which is obtained using a Labeled Tree Probing (LTP) method. The computing capacity is denoted as the Idle Factor (IF) which is obtained from the semantic overlay. The higher- and lower-level characteristics are combined into an Integrated Impacting Factor (IIF) using a Double Linear Inserting (DLI) function. Based on IIF, optimal topology matching can be achieved in the LB process. Extensive experiments and simulations have been performed and will be discussed. The results show that $ M^{2} $ON achieves more accurate topology matching with a minimum increment in the overall locating time yet achieving higher system performance as a whole. grid computing (dpeaa)DE-He213 load balancing (LB) (dpeaa)DE-He213 min-cost and max-flow channel (M (dpeaa)DE-He213 C) (dpeaa)DE-He213 topology mismatching (dpeaa)DE-He213 labeled tree probing (LTP) (dpeaa)DE-He213 double linear inserting (DLI) (dpeaa)DE-He213 Baumgarten, Matthias verfasserin aut Zhou, Yanhong verfasserin aut Jin, Hai verfasserin aut Enthalten in Frontiers of computer science in China Beijing : Higher Education Press, 2007 3(2009), 4 vom: 22. Okt. (DE-627)545787726 (DE-600)2388878-7 1673-7466 nnns volume:3 year:2009 number:4 day:22 month:10 https://dx.doi.org/10.1007/s11704-009-0036-0 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_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_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_266 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 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_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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.00 ASE AR 3 2009 4 22 10 |
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Enthalten in Frontiers of computer science in China 3(2009), 4 vom: 22. Okt. volume:3 year:2009 number:4 day:22 month:10 |
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Jiang, Wenchao @@aut@@ Baumgarten, Matthias @@aut@@ Zhou, Yanhong @@aut@@ Jin, Hai @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR021934452</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220111090258.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201006s2009 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11704-009-0036-0</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR021934452</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11704-009-0036-0-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">54.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Jiang, Wenchao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A bipartite model for load balancing in grid computing environments</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2009</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract In this paper, a bipartite model for load balancing (LB) in grid computing environments, called Transverse viewpoint-based Bi-Tier model (TBT), is proposed. TBT can efficiently eliminate topology mismatching between overlay- and physical-networks during the load transfer process. As an implementation of TBT, a novel LB policy called $ M^{2} $ON (Min-cost and Max-flow Channel based Overlay Network) is presented. In $ M^{2} $ON, the communication capability is denoted as $ M^{2} $C (Min-cost and Max-flow Channel) which is obtained using a Labeled Tree Probing (LTP) method. The computing capacity is denoted as the Idle Factor (IF) which is obtained from the semantic overlay. The higher- and lower-level characteristics are combined into an Integrated Impacting Factor (IIF) using a Double Linear Inserting (DLI) function. Based on IIF, optimal topology matching can be achieved in the LB process. Extensive experiments and simulations have been performed and will be discussed. 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Jiang, Wenchao ddc 004 bkl 54.00 misc grid computing misc load balancing (LB) misc min-cost and max-flow channel (M misc C) misc topology mismatching misc labeled tree probing (LTP) misc double linear inserting (DLI) A bipartite model for load balancing in grid computing environments |
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004 ASE 54.00 bkl A bipartite model for load balancing in grid computing environments grid computing (dpeaa)DE-He213 load balancing (LB) (dpeaa)DE-He213 min-cost and max-flow channel (M (dpeaa)DE-He213 C) (dpeaa)DE-He213 topology mismatching (dpeaa)DE-He213 labeled tree probing (LTP) (dpeaa)DE-He213 double linear inserting (DLI) (dpeaa)DE-He213 |
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bipartite model for load balancing in grid computing environments |
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A bipartite model for load balancing in grid computing environments |
| abstract |
Abstract In this paper, a bipartite model for load balancing (LB) in grid computing environments, called Transverse viewpoint-based Bi-Tier model (TBT), is proposed. TBT can efficiently eliminate topology mismatching between overlay- and physical-networks during the load transfer process. As an implementation of TBT, a novel LB policy called $ M^{2} $ON (Min-cost and Max-flow Channel based Overlay Network) is presented. In $ M^{2} $ON, the communication capability is denoted as $ M^{2} $C (Min-cost and Max-flow Channel) which is obtained using a Labeled Tree Probing (LTP) method. The computing capacity is denoted as the Idle Factor (IF) which is obtained from the semantic overlay. The higher- and lower-level characteristics are combined into an Integrated Impacting Factor (IIF) using a Double Linear Inserting (DLI) function. Based on IIF, optimal topology matching can be achieved in the LB process. Extensive experiments and simulations have been performed and will be discussed. The results show that $ M^{2} $ON achieves more accurate topology matching with a minimum increment in the overall locating time yet achieving higher system performance as a whole. |
| abstractGer |
Abstract In this paper, a bipartite model for load balancing (LB) in grid computing environments, called Transverse viewpoint-based Bi-Tier model (TBT), is proposed. TBT can efficiently eliminate topology mismatching between overlay- and physical-networks during the load transfer process. As an implementation of TBT, a novel LB policy called $ M^{2} $ON (Min-cost and Max-flow Channel based Overlay Network) is presented. In $ M^{2} $ON, the communication capability is denoted as $ M^{2} $C (Min-cost and Max-flow Channel) which is obtained using a Labeled Tree Probing (LTP) method. The computing capacity is denoted as the Idle Factor (IF) which is obtained from the semantic overlay. The higher- and lower-level characteristics are combined into an Integrated Impacting Factor (IIF) using a Double Linear Inserting (DLI) function. Based on IIF, optimal topology matching can be achieved in the LB process. Extensive experiments and simulations have been performed and will be discussed. The results show that $ M^{2} $ON achieves more accurate topology matching with a minimum increment in the overall locating time yet achieving higher system performance as a whole. |
| abstract_unstemmed |
Abstract In this paper, a bipartite model for load balancing (LB) in grid computing environments, called Transverse viewpoint-based Bi-Tier model (TBT), is proposed. TBT can efficiently eliminate topology mismatching between overlay- and physical-networks during the load transfer process. As an implementation of TBT, a novel LB policy called $ M^{2} $ON (Min-cost and Max-flow Channel based Overlay Network) is presented. In $ M^{2} $ON, the communication capability is denoted as $ M^{2} $C (Min-cost and Max-flow Channel) which is obtained using a Labeled Tree Probing (LTP) method. The computing capacity is denoted as the Idle Factor (IF) which is obtained from the semantic overlay. The higher- and lower-level characteristics are combined into an Integrated Impacting Factor (IIF) using a Double Linear Inserting (DLI) function. Based on IIF, optimal topology matching can be achieved in the LB process. Extensive experiments and simulations have been performed and will be discussed. The results show that $ M^{2} $ON achieves more accurate topology matching with a minimum increment in the overall locating time yet achieving higher system performance as a whole. |
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| title_short |
A bipartite model for load balancing in grid computing environments |
| url |
https://dx.doi.org/10.1007/s11704-009-0036-0 |
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true |
| author2 |
Baumgarten, Matthias Zhou, Yanhong Jin, Hai |
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Baumgarten, Matthias Zhou, Yanhong Jin, Hai |
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| doi_str |
10.1007/s11704-009-0036-0 |
| up_date |
2024-07-04T01:05:24.306Z |
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| score |
7.3964148 |