ALVEC: Auto-scaling by Lotka Volterra elastic cloud: A QoS aware non linear dynamical allocation model
Measurement of the dynamic elasticity of resource allocation in cloud computing continues to be a relevant problem in the related literature. Yet, there is scant evidence on determining the dynamic scaling quotient in such operations. Elasticity is defined as the ability to adapt to the changing wor...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Goswami(Mukherjee), Bidisha [verfasserIn] Sarkar, Jyotirmoy [verfasserIn] Saha, Snehanshu [verfasserIn] Kar, Saibal [verfasserIn] Sarkar, Poulami [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Simulation modelling practice and theory - Amsterdam [u.a.] : Elsevier Science, 2002, 93, Seite 262-292 |
|---|---|
| Übergeordnetes Werk: |
volume:93 ; pages:262-292 |
| DOI / URN: |
10.1016/j.simpat.2018.08.003 |
|---|
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ELV001951718 |
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| 520 | |a Measurement of the dynamic elasticity of resource allocation in cloud computing continues to be a relevant problem in the related literature. Yet, there is scant evidence on determining the dynamic scaling quotient in such operations. Elasticity is defined as the ability to adapt to the changing workloads by provisioning and de-provisioning of Cloud resources and scaling is essential for maintaining elasticity in resource allocation. We propose ALVEC, as a model of resource allocation in Cloud data centers (Sarkar et al. , 2016) , to address dynamic allocation by auto-tuning the model parameters. The proposed model, governed by a coupled differential equation known as Lotka Volterra (LV), fares better for management of Service Level Agreement (SLA) and Quality of Services (QoS). We show evidence of true elasticity both in theoretical and numerical applications. Additionally, we show that ALVEC as an example of unsupervised resource allocation, is able to predict the future load and allocate virtual machines efficiently. | ||
| 650 | 4 | |a Resource allocation | |
| 650 | 4 | |a Elasticity | |
| 650 | 4 | |a Lotka Volterra (LV) | |
| 650 | 4 | |a Auto scaling | |
| 650 | 4 | |a Cloud systems modeling | |
| 650 | 4 | |a Simulation. | |
| 700 | 1 | |a Sarkar, Jyotirmoy |e verfasserin |4 aut | |
| 700 | 1 | |a Saha, Snehanshu |e verfasserin |0 (orcid)0000-0002-8458-604X |4 aut | |
| 700 | 1 | |a Kar, Saibal |e verfasserin |4 aut | |
| 700 | 1 | |a Sarkar, Poulami |e verfasserin |4 aut | |
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10.1016/j.simpat.2018.08.003 doi (DE-627)ELV001951718 (ELSEVIER)S1569-190X(18)30110-2 DE-627 ger DE-627 rda eng 530 510 DE-600 50.03 bkl 30.03 bkl 54.76 bkl Goswami(Mukherjee), Bidisha verfasserin aut ALVEC: Auto-scaling by Lotka Volterra elastic cloud: A QoS aware non linear dynamical allocation model 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Measurement of the dynamic elasticity of resource allocation in cloud computing continues to be a relevant problem in the related literature. Yet, there is scant evidence on determining the dynamic scaling quotient in such operations. Elasticity is defined as the ability to adapt to the changing workloads by provisioning and de-provisioning of Cloud resources and scaling is essential for maintaining elasticity in resource allocation. We propose ALVEC, as a model of resource allocation in Cloud data centers (Sarkar et al. , 2016) , to address dynamic allocation by auto-tuning the model parameters. The proposed model, governed by a coupled differential equation known as Lotka Volterra (LV), fares better for management of Service Level Agreement (SLA) and Quality of Services (QoS). We show evidence of true elasticity both in theoretical and numerical applications. Additionally, we show that ALVEC as an example of unsupervised resource allocation, is able to predict the future load and allocate virtual machines efficiently. Resource allocation Elasticity Lotka Volterra (LV) Auto scaling Cloud systems modeling Simulation. Sarkar, Jyotirmoy verfasserin aut Saha, Snehanshu verfasserin (orcid)0000-0002-8458-604X aut Kar, Saibal verfasserin aut Sarkar, Poulami verfasserin aut Enthalten in Simulation modelling practice and theory Amsterdam [u.a.] : Elsevier Science, 2002 93, Seite 262-292 Online-Ressource (DE-627)357869052 (DE-600)2095751-8 (DE-576)253019486 nnns volume:93 pages:262-292 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 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_4338 GBV_ILN_4393 50.03 Methoden und Techniken der Ingenieurwissenschaften 30.03 Methoden und Techniken in den Naturwissenschaften 54.76 Computersimulation AR 93 262-292 |
| spelling |
10.1016/j.simpat.2018.08.003 doi (DE-627)ELV001951718 (ELSEVIER)S1569-190X(18)30110-2 DE-627 ger DE-627 rda eng 530 510 DE-600 50.03 bkl 30.03 bkl 54.76 bkl Goswami(Mukherjee), Bidisha verfasserin aut ALVEC: Auto-scaling by Lotka Volterra elastic cloud: A QoS aware non linear dynamical allocation model 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Measurement of the dynamic elasticity of resource allocation in cloud computing continues to be a relevant problem in the related literature. Yet, there is scant evidence on determining the dynamic scaling quotient in such operations. Elasticity is defined as the ability to adapt to the changing workloads by provisioning and de-provisioning of Cloud resources and scaling is essential for maintaining elasticity in resource allocation. We propose ALVEC, as a model of resource allocation in Cloud data centers (Sarkar et al. , 2016) , to address dynamic allocation by auto-tuning the model parameters. The proposed model, governed by a coupled differential equation known as Lotka Volterra (LV), fares better for management of Service Level Agreement (SLA) and Quality of Services (QoS). We show evidence of true elasticity both in theoretical and numerical applications. Additionally, we show that ALVEC as an example of unsupervised resource allocation, is able to predict the future load and allocate virtual machines efficiently. Resource allocation Elasticity Lotka Volterra (LV) Auto scaling Cloud systems modeling Simulation. Sarkar, Jyotirmoy verfasserin aut Saha, Snehanshu verfasserin (orcid)0000-0002-8458-604X aut Kar, Saibal verfasserin aut Sarkar, Poulami verfasserin aut Enthalten in Simulation modelling practice and theory Amsterdam [u.a.] : Elsevier Science, 2002 93, Seite 262-292 Online-Ressource (DE-627)357869052 (DE-600)2095751-8 (DE-576)253019486 nnns volume:93 pages:262-292 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 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_4338 GBV_ILN_4393 50.03 Methoden und Techniken der Ingenieurwissenschaften 30.03 Methoden und Techniken in den Naturwissenschaften 54.76 Computersimulation AR 93 262-292 |
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10.1016/j.simpat.2018.08.003 doi (DE-627)ELV001951718 (ELSEVIER)S1569-190X(18)30110-2 DE-627 ger DE-627 rda eng 530 510 DE-600 50.03 bkl 30.03 bkl 54.76 bkl Goswami(Mukherjee), Bidisha verfasserin aut ALVEC: Auto-scaling by Lotka Volterra elastic cloud: A QoS aware non linear dynamical allocation model 2018 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Measurement of the dynamic elasticity of resource allocation in cloud computing continues to be a relevant problem in the related literature. Yet, there is scant evidence on determining the dynamic scaling quotient in such operations. Elasticity is defined as the ability to adapt to the changing workloads by provisioning and de-provisioning of Cloud resources and scaling is essential for maintaining elasticity in resource allocation. We propose ALVEC, as a model of resource allocation in Cloud data centers (Sarkar et al. , 2016) , to address dynamic allocation by auto-tuning the model parameters. The proposed model, governed by a coupled differential equation known as Lotka Volterra (LV), fares better for management of Service Level Agreement (SLA) and Quality of Services (QoS). We show evidence of true elasticity both in theoretical and numerical applications. Additionally, we show that ALVEC as an example of unsupervised resource allocation, is able to predict the future load and allocate virtual machines efficiently. Resource allocation Elasticity Lotka Volterra (LV) Auto scaling Cloud systems modeling Simulation. Sarkar, Jyotirmoy verfasserin aut Saha, Snehanshu verfasserin (orcid)0000-0002-8458-604X aut Kar, Saibal verfasserin aut Sarkar, Poulami verfasserin aut Enthalten in Simulation modelling practice and theory Amsterdam [u.a.] : Elsevier Science, 2002 93, Seite 262-292 Online-Ressource (DE-627)357869052 (DE-600)2095751-8 (DE-576)253019486 nnns volume:93 pages:262-292 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 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_4338 GBV_ILN_4393 50.03 Methoden und Techniken der Ingenieurwissenschaften 30.03 Methoden und Techniken in den Naturwissenschaften 54.76 Computersimulation AR 93 262-292 |
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Goswami(Mukherjee), Bidisha @@aut@@ Sarkar, Jyotirmoy @@aut@@ Saha, Snehanshu @@aut@@ Kar, Saibal @@aut@@ Sarkar, Poulami @@aut@@ |
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alvec: auto-scaling by lotka volterra elastic cloud: a qos aware non linear dynamical allocation model |
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ALVEC: Auto-scaling by Lotka Volterra elastic cloud: A QoS aware non linear dynamical allocation model |
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Measurement of the dynamic elasticity of resource allocation in cloud computing continues to be a relevant problem in the related literature. Yet, there is scant evidence on determining the dynamic scaling quotient in such operations. Elasticity is defined as the ability to adapt to the changing workloads by provisioning and de-provisioning of Cloud resources and scaling is essential for maintaining elasticity in resource allocation. We propose ALVEC, as a model of resource allocation in Cloud data centers (Sarkar et al. , 2016) , to address dynamic allocation by auto-tuning the model parameters. The proposed model, governed by a coupled differential equation known as Lotka Volterra (LV), fares better for management of Service Level Agreement (SLA) and Quality of Services (QoS). We show evidence of true elasticity both in theoretical and numerical applications. Additionally, we show that ALVEC as an example of unsupervised resource allocation, is able to predict the future load and allocate virtual machines efficiently. |
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Measurement of the dynamic elasticity of resource allocation in cloud computing continues to be a relevant problem in the related literature. Yet, there is scant evidence on determining the dynamic scaling quotient in such operations. Elasticity is defined as the ability to adapt to the changing workloads by provisioning and de-provisioning of Cloud resources and scaling is essential for maintaining elasticity in resource allocation. We propose ALVEC, as a model of resource allocation in Cloud data centers (Sarkar et al. , 2016) , to address dynamic allocation by auto-tuning the model parameters. The proposed model, governed by a coupled differential equation known as Lotka Volterra (LV), fares better for management of Service Level Agreement (SLA) and Quality of Services (QoS). We show evidence of true elasticity both in theoretical and numerical applications. Additionally, we show that ALVEC as an example of unsupervised resource allocation, is able to predict the future load and allocate virtual machines efficiently. |
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Measurement of the dynamic elasticity of resource allocation in cloud computing continues to be a relevant problem in the related literature. Yet, there is scant evidence on determining the dynamic scaling quotient in such operations. Elasticity is defined as the ability to adapt to the changing workloads by provisioning and de-provisioning of Cloud resources and scaling is essential for maintaining elasticity in resource allocation. We propose ALVEC, as a model of resource allocation in Cloud data centers (Sarkar et al. , 2016) , to address dynamic allocation by auto-tuning the model parameters. The proposed model, governed by a coupled differential equation known as Lotka Volterra (LV), fares better for management of Service Level Agreement (SLA) and Quality of Services (QoS). We show evidence of true elasticity both in theoretical and numerical applications. Additionally, we show that ALVEC as an example of unsupervised resource allocation, is able to predict the future load and allocate virtual machines efficiently. |
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| score |
7.4003763 |