ATAC4Cloud: a framework for modeling and simulating autonomic cloud
Abstract Optimizing resources usage costs represents a key issue in order to efficiently manage Cloud infrastructure. By using such infrastructure, the ability to infer the needed number and type of resources determines the final budget. A lot of work and budget is required to set up a testbed of ad...
Ausführliche Beschreibung
Autor*in: |
Chainbi, Walid [verfasserIn] Chihi, Hanen [verfasserIn] Azaiez, Meriem [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2016 |
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Übergeordnetes Werk: |
Enthalten in: Soft Computing - Springer-Verlag, 2003, 21(2016), 16 vom: 26. Nov., Seite 4571-4582 |
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Übergeordnetes Werk: |
volume:21 ; year:2016 ; number:16 ; day:26 ; month:11 ; pages:4571-4582 |
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DOI / URN: |
10.1007/s00500-016-2451-0 |
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SPR006493165 |
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10.1007/s00500-016-2451-0 doi (DE-627)SPR006493165 (SPR)s00500-016-2451-0-e DE-627 ger DE-627 rakwb eng Chainbi, Walid verfasserin aut ATAC4Cloud: a framework for modeling and simulating autonomic cloud 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Optimizing resources usage costs represents a key issue in order to efficiently manage Cloud infrastructure. By using such infrastructure, the ability to infer the needed number and type of resources determines the final budget. A lot of work and budget is required to set up a testbed of adequate size, including different resources from different Cloud providers, in order to develop new proposals aimed at Cloud resources adaptation. Several Cloud computing simulators including MDCSim, GreenCloud, iCanCloud and CloudSim have been proposed, but their main problems are that they don’t take into account Cloud self-adaptation needs. For these reasons, we propose in this paper ATAC4Cloud, a Cloud simulator supporting autonomic behaviors and integrating a workload generator that builds benchmarks to test the Cloud infrastructure. The underpinning of this work is the synergy existing between agent technology and autonomic computing to develop self-adaptive Cloud systems. ATAC4Cloud is developed as an extension of CloudSim. Cloud Computing (dpeaa)DE-He213 Virtual Machine (dpeaa)DE-He213 Agent Technology (dpeaa)DE-He213 Cloud Resource (dpeaa)DE-He213 Cloud Infrastructure (dpeaa)DE-He213 Chihi, Hanen verfasserin aut Azaiez, Meriem verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 21(2016), 16 vom: 26. Nov., Seite 4571-4582 (DE-627)SPR006469531 nnns volume:21 year:2016 number:16 day:26 month:11 pages:4571-4582 https://dx.doi.org/10.1007/s00500-016-2451-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 21 2016 16 26 11 4571-4582 |
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10.1007/s00500-016-2451-0 doi (DE-627)SPR006493165 (SPR)s00500-016-2451-0-e DE-627 ger DE-627 rakwb eng Chainbi, Walid verfasserin aut ATAC4Cloud: a framework for modeling and simulating autonomic cloud 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Optimizing resources usage costs represents a key issue in order to efficiently manage Cloud infrastructure. By using such infrastructure, the ability to infer the needed number and type of resources determines the final budget. A lot of work and budget is required to set up a testbed of adequate size, including different resources from different Cloud providers, in order to develop new proposals aimed at Cloud resources adaptation. Several Cloud computing simulators including MDCSim, GreenCloud, iCanCloud and CloudSim have been proposed, but their main problems are that they don’t take into account Cloud self-adaptation needs. For these reasons, we propose in this paper ATAC4Cloud, a Cloud simulator supporting autonomic behaviors and integrating a workload generator that builds benchmarks to test the Cloud infrastructure. The underpinning of this work is the synergy existing between agent technology and autonomic computing to develop self-adaptive Cloud systems. ATAC4Cloud is developed as an extension of CloudSim. Cloud Computing (dpeaa)DE-He213 Virtual Machine (dpeaa)DE-He213 Agent Technology (dpeaa)DE-He213 Cloud Resource (dpeaa)DE-He213 Cloud Infrastructure (dpeaa)DE-He213 Chihi, Hanen verfasserin aut Azaiez, Meriem verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 21(2016), 16 vom: 26. Nov., Seite 4571-4582 (DE-627)SPR006469531 nnns volume:21 year:2016 number:16 day:26 month:11 pages:4571-4582 https://dx.doi.org/10.1007/s00500-016-2451-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 21 2016 16 26 11 4571-4582 |
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10.1007/s00500-016-2451-0 doi (DE-627)SPR006493165 (SPR)s00500-016-2451-0-e DE-627 ger DE-627 rakwb eng Chainbi, Walid verfasserin aut ATAC4Cloud: a framework for modeling and simulating autonomic cloud 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Optimizing resources usage costs represents a key issue in order to efficiently manage Cloud infrastructure. By using such infrastructure, the ability to infer the needed number and type of resources determines the final budget. A lot of work and budget is required to set up a testbed of adequate size, including different resources from different Cloud providers, in order to develop new proposals aimed at Cloud resources adaptation. Several Cloud computing simulators including MDCSim, GreenCloud, iCanCloud and CloudSim have been proposed, but their main problems are that they don’t take into account Cloud self-adaptation needs. For these reasons, we propose in this paper ATAC4Cloud, a Cloud simulator supporting autonomic behaviors and integrating a workload generator that builds benchmarks to test the Cloud infrastructure. The underpinning of this work is the synergy existing between agent technology and autonomic computing to develop self-adaptive Cloud systems. ATAC4Cloud is developed as an extension of CloudSim. Cloud Computing (dpeaa)DE-He213 Virtual Machine (dpeaa)DE-He213 Agent Technology (dpeaa)DE-He213 Cloud Resource (dpeaa)DE-He213 Cloud Infrastructure (dpeaa)DE-He213 Chihi, Hanen verfasserin aut Azaiez, Meriem verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 21(2016), 16 vom: 26. Nov., Seite 4571-4582 (DE-627)SPR006469531 nnns volume:21 year:2016 number:16 day:26 month:11 pages:4571-4582 https://dx.doi.org/10.1007/s00500-016-2451-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 21 2016 16 26 11 4571-4582 |
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10.1007/s00500-016-2451-0 doi (DE-627)SPR006493165 (SPR)s00500-016-2451-0-e DE-627 ger DE-627 rakwb eng Chainbi, Walid verfasserin aut ATAC4Cloud: a framework for modeling and simulating autonomic cloud 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Optimizing resources usage costs represents a key issue in order to efficiently manage Cloud infrastructure. By using such infrastructure, the ability to infer the needed number and type of resources determines the final budget. A lot of work and budget is required to set up a testbed of adequate size, including different resources from different Cloud providers, in order to develop new proposals aimed at Cloud resources adaptation. Several Cloud computing simulators including MDCSim, GreenCloud, iCanCloud and CloudSim have been proposed, but their main problems are that they don’t take into account Cloud self-adaptation needs. For these reasons, we propose in this paper ATAC4Cloud, a Cloud simulator supporting autonomic behaviors and integrating a workload generator that builds benchmarks to test the Cloud infrastructure. The underpinning of this work is the synergy existing between agent technology and autonomic computing to develop self-adaptive Cloud systems. ATAC4Cloud is developed as an extension of CloudSim. Cloud Computing (dpeaa)DE-He213 Virtual Machine (dpeaa)DE-He213 Agent Technology (dpeaa)DE-He213 Cloud Resource (dpeaa)DE-He213 Cloud Infrastructure (dpeaa)DE-He213 Chihi, Hanen verfasserin aut Azaiez, Meriem verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 21(2016), 16 vom: 26. Nov., Seite 4571-4582 (DE-627)SPR006469531 nnns volume:21 year:2016 number:16 day:26 month:11 pages:4571-4582 https://dx.doi.org/10.1007/s00500-016-2451-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 21 2016 16 26 11 4571-4582 |
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10.1007/s00500-016-2451-0 doi (DE-627)SPR006493165 (SPR)s00500-016-2451-0-e DE-627 ger DE-627 rakwb eng Chainbi, Walid verfasserin aut ATAC4Cloud: a framework for modeling and simulating autonomic cloud 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Optimizing resources usage costs represents a key issue in order to efficiently manage Cloud infrastructure. By using such infrastructure, the ability to infer the needed number and type of resources determines the final budget. A lot of work and budget is required to set up a testbed of adequate size, including different resources from different Cloud providers, in order to develop new proposals aimed at Cloud resources adaptation. Several Cloud computing simulators including MDCSim, GreenCloud, iCanCloud and CloudSim have been proposed, but their main problems are that they don’t take into account Cloud self-adaptation needs. For these reasons, we propose in this paper ATAC4Cloud, a Cloud simulator supporting autonomic behaviors and integrating a workload generator that builds benchmarks to test the Cloud infrastructure. The underpinning of this work is the synergy existing between agent technology and autonomic computing to develop self-adaptive Cloud systems. ATAC4Cloud is developed as an extension of CloudSim. Cloud Computing (dpeaa)DE-He213 Virtual Machine (dpeaa)DE-He213 Agent Technology (dpeaa)DE-He213 Cloud Resource (dpeaa)DE-He213 Cloud Infrastructure (dpeaa)DE-He213 Chihi, Hanen verfasserin aut Azaiez, Meriem verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 21(2016), 16 vom: 26. Nov., Seite 4571-4582 (DE-627)SPR006469531 nnns volume:21 year:2016 number:16 day:26 month:11 pages:4571-4582 https://dx.doi.org/10.1007/s00500-016-2451-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 21 2016 16 26 11 4571-4582 |
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Abstract Optimizing resources usage costs represents a key issue in order to efficiently manage Cloud infrastructure. By using such infrastructure, the ability to infer the needed number and type of resources determines the final budget. A lot of work and budget is required to set up a testbed of adequate size, including different resources from different Cloud providers, in order to develop new proposals aimed at Cloud resources adaptation. Several Cloud computing simulators including MDCSim, GreenCloud, iCanCloud and CloudSim have been proposed, but their main problems are that they don’t take into account Cloud self-adaptation needs. For these reasons, we propose in this paper ATAC4Cloud, a Cloud simulator supporting autonomic behaviors and integrating a workload generator that builds benchmarks to test the Cloud infrastructure. The underpinning of this work is the synergy existing between agent technology and autonomic computing to develop self-adaptive Cloud systems. ATAC4Cloud is developed as an extension of CloudSim. |
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Abstract Optimizing resources usage costs represents a key issue in order to efficiently manage Cloud infrastructure. By using such infrastructure, the ability to infer the needed number and type of resources determines the final budget. A lot of work and budget is required to set up a testbed of adequate size, including different resources from different Cloud providers, in order to develop new proposals aimed at Cloud resources adaptation. Several Cloud computing simulators including MDCSim, GreenCloud, iCanCloud and CloudSim have been proposed, but their main problems are that they don’t take into account Cloud self-adaptation needs. For these reasons, we propose in this paper ATAC4Cloud, a Cloud simulator supporting autonomic behaviors and integrating a workload generator that builds benchmarks to test the Cloud infrastructure. The underpinning of this work is the synergy existing between agent technology and autonomic computing to develop self-adaptive Cloud systems. ATAC4Cloud is developed as an extension of CloudSim. |
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Abstract Optimizing resources usage costs represents a key issue in order to efficiently manage Cloud infrastructure. By using such infrastructure, the ability to infer the needed number and type of resources determines the final budget. A lot of work and budget is required to set up a testbed of adequate size, including different resources from different Cloud providers, in order to develop new proposals aimed at Cloud resources adaptation. Several Cloud computing simulators including MDCSim, GreenCloud, iCanCloud and CloudSim have been proposed, but their main problems are that they don’t take into account Cloud self-adaptation needs. For these reasons, we propose in this paper ATAC4Cloud, a Cloud simulator supporting autonomic behaviors and integrating a workload generator that builds benchmarks to test the Cloud infrastructure. The underpinning of this work is the synergy existing between agent technology and autonomic computing to develop self-adaptive Cloud systems. ATAC4Cloud is developed as an extension of CloudSim. |
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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">SPR006493165</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20201124002828.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201005s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00500-016-2451-0</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR006493165</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00500-016-2451-0-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="100" ind1="1" ind2=" "><subfield code="a">Chainbi, Walid</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">ATAC4Cloud: a framework for modeling and simulating autonomic cloud</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</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 Optimizing resources usage costs represents a key issue in order to efficiently manage Cloud infrastructure. By using such infrastructure, the ability to infer the needed number and type of resources determines the final budget. A lot of work and budget is required to set up a testbed of adequate size, including different resources from different Cloud providers, in order to develop new proposals aimed at Cloud resources adaptation. Several Cloud computing simulators including MDCSim, GreenCloud, iCanCloud and CloudSim have been proposed, but their main problems are that they don’t take into account Cloud self-adaptation needs. For these reasons, we propose in this paper ATAC4Cloud, a Cloud simulator supporting autonomic behaviors and integrating a workload generator that builds benchmarks to test the Cloud infrastructure. The underpinning of this work is the synergy existing between agent technology and autonomic computing to develop self-adaptive Cloud systems. 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