CHOPPER: an intelligent QoS-aware autonomic resource management approach for cloud computing
Abstract Cloud computing is the future generation of computational services delivered over the Internet. As cloud infrastructure expands, resource management in such a large heterogeneous and distributed environment is a challenging task. In a cloud environment, uncertainty and dispersion of resourc...
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Gespeichert in:
| Autor*in: |
Gill, Sukhpal Singh [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC 2017 |
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| Übergeordnetes Werk: |
Enthalten in: Cluster computing - Springer US, 1998, 21(2017), 2 vom: 01. Aug., Seite 1203-1241 |
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| Übergeordnetes Werk: |
volume:21 ; year:2017 ; number:2 ; day:01 ; month:08 ; pages:1203-1241 |
| Links: |
|---|
| DOI / URN: |
10.1007/s10586-017-1040-z |
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| Katalog-ID: |
OLC2066390712 |
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| 520 | |a Abstract Cloud computing is the future generation of computational services delivered over the Internet. As cloud infrastructure expands, resource management in such a large heterogeneous and distributed environment is a challenging task. In a cloud environment, uncertainty and dispersion of resources encounters problems of allocation of resources. Unfortunately, existing resource management techniques, frameworks and mechanisms are insufficient to handle these environments, applications and resource behaviors. To provide an efficient performance and to execute workloads, there is a need of quality of service (QoS) based autonomic resource management approach which manages resources automatically and provides reliable, secure and cost efficient cloud services. In this paper, we present an intelligent QoS-aware autonomic resource management approach named as CHOPPER (Configuring, Healing, Optimizing and Protecting Policy for Efficient Resource management). CHOPPER offers self-configuration of applications and resources, self-healing by handling sudden failures, self-protection against security attacks and self-optimization for maximum resource utilization. We have evaluated the performance of the proposed approach in a real cloud environment and the experimental results show that the proposed approach performs better in terms of cost, execution time, SLA violation, resource contention and also provides security against attacks. | ||
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| 650 | 4 | |a Resource provisioning and scheduling | |
| 650 | 4 | |a Self-healing | |
| 650 | 4 | |a Self-configuring | |
| 650 | 4 | |a Self-optimizing | |
| 650 | 4 | |a Self-protecting | |
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| 700 | 1 | |a Singh, Maninder |4 aut | |
| 700 | 1 | |a Buyya, Rajkumar |4 aut | |
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10.1007/s10586-017-1040-z doi (DE-627)OLC2066390712 (DE-He213)s10586-017-1040-z-p DE-627 ger DE-627 rakwb eng 004 VZ 54.50$jProgrammierung: Allgemeines bkl 54.32$jRechnerkommunikation bkl 54.25$jParallele Datenverarbeitung bkl Gill, Sukhpal Singh verfasserin aut CHOPPER: an intelligent QoS-aware autonomic resource management approach for cloud computing 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2017 Abstract Cloud computing is the future generation of computational services delivered over the Internet. As cloud infrastructure expands, resource management in such a large heterogeneous and distributed environment is a challenging task. In a cloud environment, uncertainty and dispersion of resources encounters problems of allocation of resources. Unfortunately, existing resource management techniques, frameworks and mechanisms are insufficient to handle these environments, applications and resource behaviors. To provide an efficient performance and to execute workloads, there is a need of quality of service (QoS) based autonomic resource management approach which manages resources automatically and provides reliable, secure and cost efficient cloud services. In this paper, we present an intelligent QoS-aware autonomic resource management approach named as CHOPPER (Configuring, Healing, Optimizing and Protecting Policy for Efficient Resource management). CHOPPER offers self-configuration of applications and resources, self-healing by handling sudden failures, self-protection against security attacks and self-optimization for maximum resource utilization. We have evaluated the performance of the proposed approach in a real cloud environment and the experimental results show that the proposed approach performs better in terms of cost, execution time, SLA violation, resource contention and also provides security against attacks. Autonomic cloud computing Resource provisioning and scheduling Self-healing Self-configuring Self-optimizing Self-protecting Chana, Inderveer aut Singh, Maninder aut Buyya, Rajkumar aut Enthalten in Cluster computing Springer US, 1998 21(2017), 2 vom: 01. Aug., Seite 1203-1241 (DE-627)265187907 (DE-600)1465290-0 (DE-576)9265187905 1386-7857 nnns volume:21 year:2017 number:2 day:01 month:08 pages:1203-1241 https://doi.org/10.1007/s10586-017-1040-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.50$jProgrammierung: Allgemeines VZ 181569876 (DE-625)181569876 54.32$jRechnerkommunikation VZ 10640623X (DE-625)10640623X 54.25$jParallele Datenverarbeitung VZ 181569892 (DE-625)181569892 AR 21 2017 2 01 08 1203-1241 |
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10.1007/s10586-017-1040-z doi (DE-627)OLC2066390712 (DE-He213)s10586-017-1040-z-p DE-627 ger DE-627 rakwb eng 004 VZ 54.50$jProgrammierung: Allgemeines bkl 54.32$jRechnerkommunikation bkl 54.25$jParallele Datenverarbeitung bkl Gill, Sukhpal Singh verfasserin aut CHOPPER: an intelligent QoS-aware autonomic resource management approach for cloud computing 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2017 Abstract Cloud computing is the future generation of computational services delivered over the Internet. As cloud infrastructure expands, resource management in such a large heterogeneous and distributed environment is a challenging task. In a cloud environment, uncertainty and dispersion of resources encounters problems of allocation of resources. Unfortunately, existing resource management techniques, frameworks and mechanisms are insufficient to handle these environments, applications and resource behaviors. To provide an efficient performance and to execute workloads, there is a need of quality of service (QoS) based autonomic resource management approach which manages resources automatically and provides reliable, secure and cost efficient cloud services. In this paper, we present an intelligent QoS-aware autonomic resource management approach named as CHOPPER (Configuring, Healing, Optimizing and Protecting Policy for Efficient Resource management). CHOPPER offers self-configuration of applications and resources, self-healing by handling sudden failures, self-protection against security attacks and self-optimization for maximum resource utilization. We have evaluated the performance of the proposed approach in a real cloud environment and the experimental results show that the proposed approach performs better in terms of cost, execution time, SLA violation, resource contention and also provides security against attacks. Autonomic cloud computing Resource provisioning and scheduling Self-healing Self-configuring Self-optimizing Self-protecting Chana, Inderveer aut Singh, Maninder aut Buyya, Rajkumar aut Enthalten in Cluster computing Springer US, 1998 21(2017), 2 vom: 01. Aug., Seite 1203-1241 (DE-627)265187907 (DE-600)1465290-0 (DE-576)9265187905 1386-7857 nnns volume:21 year:2017 number:2 day:01 month:08 pages:1203-1241 https://doi.org/10.1007/s10586-017-1040-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.50$jProgrammierung: Allgemeines VZ 181569876 (DE-625)181569876 54.32$jRechnerkommunikation VZ 10640623X (DE-625)10640623X 54.25$jParallele Datenverarbeitung VZ 181569892 (DE-625)181569892 AR 21 2017 2 01 08 1203-1241 |
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10.1007/s10586-017-1040-z doi (DE-627)OLC2066390712 (DE-He213)s10586-017-1040-z-p DE-627 ger DE-627 rakwb eng 004 VZ 54.50$jProgrammierung: Allgemeines bkl 54.32$jRechnerkommunikation bkl 54.25$jParallele Datenverarbeitung bkl Gill, Sukhpal Singh verfasserin aut CHOPPER: an intelligent QoS-aware autonomic resource management approach for cloud computing 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2017 Abstract Cloud computing is the future generation of computational services delivered over the Internet. As cloud infrastructure expands, resource management in such a large heterogeneous and distributed environment is a challenging task. In a cloud environment, uncertainty and dispersion of resources encounters problems of allocation of resources. Unfortunately, existing resource management techniques, frameworks and mechanisms are insufficient to handle these environments, applications and resource behaviors. To provide an efficient performance and to execute workloads, there is a need of quality of service (QoS) based autonomic resource management approach which manages resources automatically and provides reliable, secure and cost efficient cloud services. In this paper, we present an intelligent QoS-aware autonomic resource management approach named as CHOPPER (Configuring, Healing, Optimizing and Protecting Policy for Efficient Resource management). CHOPPER offers self-configuration of applications and resources, self-healing by handling sudden failures, self-protection against security attacks and self-optimization for maximum resource utilization. We have evaluated the performance of the proposed approach in a real cloud environment and the experimental results show that the proposed approach performs better in terms of cost, execution time, SLA violation, resource contention and also provides security against attacks. Autonomic cloud computing Resource provisioning and scheduling Self-healing Self-configuring Self-optimizing Self-protecting Chana, Inderveer aut Singh, Maninder aut Buyya, Rajkumar aut Enthalten in Cluster computing Springer US, 1998 21(2017), 2 vom: 01. Aug., Seite 1203-1241 (DE-627)265187907 (DE-600)1465290-0 (DE-576)9265187905 1386-7857 nnns volume:21 year:2017 number:2 day:01 month:08 pages:1203-1241 https://doi.org/10.1007/s10586-017-1040-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.50$jProgrammierung: Allgemeines VZ 181569876 (DE-625)181569876 54.32$jRechnerkommunikation VZ 10640623X (DE-625)10640623X 54.25$jParallele Datenverarbeitung VZ 181569892 (DE-625)181569892 AR 21 2017 2 01 08 1203-1241 |
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| author |
Gill, Sukhpal Singh |
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chopper: an intelligent qos-aware autonomic resource management approach for cloud computing |
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CHOPPER: an intelligent QoS-aware autonomic resource management approach for cloud computing |
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Abstract Cloud computing is the future generation of computational services delivered over the Internet. As cloud infrastructure expands, resource management in such a large heterogeneous and distributed environment is a challenging task. In a cloud environment, uncertainty and dispersion of resources encounters problems of allocation of resources. Unfortunately, existing resource management techniques, frameworks and mechanisms are insufficient to handle these environments, applications and resource behaviors. To provide an efficient performance and to execute workloads, there is a need of quality of service (QoS) based autonomic resource management approach which manages resources automatically and provides reliable, secure and cost efficient cloud services. In this paper, we present an intelligent QoS-aware autonomic resource management approach named as CHOPPER (Configuring, Healing, Optimizing and Protecting Policy for Efficient Resource management). CHOPPER offers self-configuration of applications and resources, self-healing by handling sudden failures, self-protection against security attacks and self-optimization for maximum resource utilization. We have evaluated the performance of the proposed approach in a real cloud environment and the experimental results show that the proposed approach performs better in terms of cost, execution time, SLA violation, resource contention and also provides security against attacks. © Springer Science+Business Media, LLC 2017 |
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Abstract Cloud computing is the future generation of computational services delivered over the Internet. As cloud infrastructure expands, resource management in such a large heterogeneous and distributed environment is a challenging task. In a cloud environment, uncertainty and dispersion of resources encounters problems of allocation of resources. Unfortunately, existing resource management techniques, frameworks and mechanisms are insufficient to handle these environments, applications and resource behaviors. To provide an efficient performance and to execute workloads, there is a need of quality of service (QoS) based autonomic resource management approach which manages resources automatically and provides reliable, secure and cost efficient cloud services. In this paper, we present an intelligent QoS-aware autonomic resource management approach named as CHOPPER (Configuring, Healing, Optimizing and Protecting Policy for Efficient Resource management). CHOPPER offers self-configuration of applications and resources, self-healing by handling sudden failures, self-protection against security attacks and self-optimization for maximum resource utilization. We have evaluated the performance of the proposed approach in a real cloud environment and the experimental results show that the proposed approach performs better in terms of cost, execution time, SLA violation, resource contention and also provides security against attacks. © Springer Science+Business Media, LLC 2017 |
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Abstract Cloud computing is the future generation of computational services delivered over the Internet. As cloud infrastructure expands, resource management in such a large heterogeneous and distributed environment is a challenging task. In a cloud environment, uncertainty and dispersion of resources encounters problems of allocation of resources. Unfortunately, existing resource management techniques, frameworks and mechanisms are insufficient to handle these environments, applications and resource behaviors. To provide an efficient performance and to execute workloads, there is a need of quality of service (QoS) based autonomic resource management approach which manages resources automatically and provides reliable, secure and cost efficient cloud services. In this paper, we present an intelligent QoS-aware autonomic resource management approach named as CHOPPER (Configuring, Healing, Optimizing and Protecting Policy for Efficient Resource management). CHOPPER offers self-configuration of applications and resources, self-healing by handling sudden failures, self-protection against security attacks and self-optimization for maximum resource utilization. We have evaluated the performance of the proposed approach in a real cloud environment and the experimental results show that the proposed approach performs better in terms of cost, execution time, SLA violation, resource contention and also provides security against attacks. © Springer Science+Business Media, LLC 2017 |
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