The Experts below are selected from a list of 39 Experts worldwide ranked by ideXlab platform
Ludmila Cherkasova - One of the best experts on this subject based on the ideXlab platform.
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Run-time Performance Optimization and Job Management in a Data Protection Solution
2015Co-Authors: Ludmila Cherkasova, Roger Lau, Harald Burose, Subramaniam Venkata KalamburAbstract:data Protector, Backup management, job scheduling, performance evaluation, automated parameter tuning The amount of stored data in enterprise Data Centers quadruples every 18 months. This trend presents a serious challenge for Backup management: one either needs to continuously scale the Backup infrastructure or to significantly improve the performance and efficiency of existing Backup tools. In this work, we discuss potential performance shortcomings of the traditional Backup solutions. We analyze historic data on Backup processing from eight Backup servers in HP Labs, and introduce two additional metrics associated with each Backup job, called job duration and job throughput. Our goal is to design a Backup Schedule that minimizes the overall completion time for a given set of Backup jobs. This problem can be formulated as a resource constrained scheduling problem which is known to be NP-complete. As an efficient heuristic for the classic optimization problem, we propose a novel job scheduling algorithm, called FlexLBF. The Scheduler utilizes extracted information from historic data and provides a significant reduction in the Backup time (up to 50%), improved quality of service, and reduced resource usage (up to 2-3 times). Moreover, the proposed framework automates parameter tuning to avoid manual configuration by syste
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DP+IP = Design of Efficient Backup Scheduling
2015Co-Authors: Ludmila Cherkasova, Alex ZhangAbstract:Data Protector, Backup management, job scheduling, integer programming, performance evaluation, automated parameter tuning Many industries experience an explosion in digital content. This explosion of electronic documents, along with new regulations and document retention rules, sets new requirements for performance efficiency of traditional data protection and archival tools. During a Backup session a predefined set of objects (client filesystems) should be backed up. Traditionally, no information on the expected duration and throughput requirements of different Backup jobs is provided. This may lead to a suboptimal job Schedule that results in the increased Backup session time. In this work, we characterize each Backup job via two metrics, called job duration and job throughput. These metrics are derived from collected historic information about Backup jobs during previous Backup sessions. Our goal is to automate the design of a Backup Schedule that minimizes the overall completion time for a given set of Backup jobs. This problem can be formulated as a resource constrained scheduling problem where a set of n jobs should be Scheduled on m machines with given capacities. We provide an integer programming (IP) formulation of this problem and use available IP-solvers for finding an optimized Schedule, called binpacking Schedule. Performance benefits of the new bin-packing Schedule are evaluated via a broad variety of realistic experiments using Backup processin
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SustainIT - Optimizing QoS, performance, and power efficiency of Backup services
2015 Sustainable Internet and ICT for Sustainability (SustainIT), 2015Co-Authors: Ludmila Cherkasova, Alex ZhangAbstract:For most businesses, Backup is a daily operation that needs to reliably protect diverse digital assets distributed across the enterprise. Efficiently processing ever increasing amounts of data residing on multiple desktops, servers, laptops, etc., and providing dynamic recovery capabilities becomes a high priority task for many IT departments. Driven by the advances in cloud computing and Software as a Service (SaaS) delivery model, IT departments are transitioning from providing highly customized services to offering on demand services which can be requested and canceled instantly. Backup service providers must be able to react efficiently to on-demand requests and cannot afford labor intensive resource planning and manual adjustments of Schedules. Our goal is to automate the design of a Backup Schedule that minimizes the overall completion time for a given set of Backup jobs. This problem can be formulated as a resource constrained scheduling problem where a set of n jobs should be Scheduled on ���� machines with given capacities. In this work, we compare the outcome of the integer programming formulation with a heuristic-based job scheduling algorithm, called FlexLBF. The FlexLBF Schedule produces close to optimal results (reducing Backup time 20%-60%) while carrying no additional computing overhead and scaling well to efficiently process large datasets compared to the IP-based solution. Moreover, FlexLBF can be easily analyzed in a simulation environment to further tune a Backup server configuration for achieving given performance objectives while saving power (up to additional 50% in our experiments). It helps to avoid guess-based configuration efforts by system administrators and significantly increase the quality and reliability of implemented solutions.
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DP+IP = Design of Efficient Backup Scheduling
2013Co-Authors: Ludmila Cherkasova, Alex ZhangAbstract:Abstract—Many industries experience an explosion in digital content. This explosion of electronic documents, along with new regulations and document retention rules, sets new requirements for performance efficiency of traditional data protection and archival tools. During a Backup session a predefined set of objects (client filesystems) should be backed up. Traditionally, no information on the expected duration and throughput requirements of different Backup jobs is provided. This may lead to a suboptimal job Schedule that results in the increased Backup session time. In thiswork,wecharacterizeeachBackupjobviatwometrics,called job duration and job throughput. These metrics are derived from collected historic information about Backup jobs during previous Backup sessions. Our goal is to automate the design of a Backup Schedule that minimizes the overall completion time for a given set of Backup jobs. This problem can be formulated as a resource constrained scheduling problem where a set of n jobs should be Scheduled on m machines with given capacities. We provide an integer programming (IP) formulation of this problem and use available IP-solvers for finding an optimized Schedule, called binpacking Schedule. Performance benefits of the new bin-packing Scheduleareevaluatedviaabroadvarietyofrealisticexperiments using Backup processing data from six Backup servers in HP Labs. The new bin-packing job Schedule significantly optimizes the Backup session time (20%-60 % of Backup time reduction). HP Data Protector (DP) is HP’s enterprise Backup offering and it can directly benefit from the designed technique. Moreover, significantlyreducedBackupsessiontimesguaranteeanimproved resource/power usage of the overall Backup solution. I
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Run-time Performance Optimization and Job Management in a Data Protection Solution
2011Co-Authors: Ludmila Cherkasova, Roger Lau, Harald Burose, Subramaniam Venkata Kalambur, Kuttiraja VeerananAbstract:Abstract — The amount of stored data in enterprise Data Centers quadruples every 18 months. This trend presents a serious challenge for Backup management and sets new requirements for performance efficiency of traditional Backup and archival tools. In this work, we discuss potential performance shortcomings of the existing Backup solutions. During a Backup session a predefined set of objects (client filesystems) should be backed up. Traditionally, no information on the expected duration and throughput requirements of different Backup jobs is provided. This may lead to an inefficient job Schedule and the increased Backup session time. We analyze historic data on Backup processing from eight Backup servers in HP Labs, and introduce two additional metrics associated with each Backup job, called job duration and job throughput. Our goal is to use this additional information for automated design of a Backup Schedule that minimizes the overall completion time for a given set of Backup jobs. This problem can be formulated as a resource constrained scheduling problem which is known to be NP-complete. Instead, we propose an efficient heuristics for building an optimized job Schedule, called FlexLBF. The new job Schedule provides a significant reduction in the Backup time (up to 50%) and reduced resource usage (up to 2-3 times). Moreover, we design a simulation-based tool that aims to automate parameter tuning for avoiding manual configuration by system administrators while helping them to achieve nearly optimal performance. I
Alex Zhang - One of the best experts on this subject based on the ideXlab platform.
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DP+IP = Design of Efficient Backup Scheduling
2015Co-Authors: Ludmila Cherkasova, Alex ZhangAbstract:Data Protector, Backup management, job scheduling, integer programming, performance evaluation, automated parameter tuning Many industries experience an explosion in digital content. This explosion of electronic documents, along with new regulations and document retention rules, sets new requirements for performance efficiency of traditional data protection and archival tools. During a Backup session a predefined set of objects (client filesystems) should be backed up. Traditionally, no information on the expected duration and throughput requirements of different Backup jobs is provided. This may lead to a suboptimal job Schedule that results in the increased Backup session time. In this work, we characterize each Backup job via two metrics, called job duration and job throughput. These metrics are derived from collected historic information about Backup jobs during previous Backup sessions. Our goal is to automate the design of a Backup Schedule that minimizes the overall completion time for a given set of Backup jobs. This problem can be formulated as a resource constrained scheduling problem where a set of n jobs should be Scheduled on m machines with given capacities. We provide an integer programming (IP) formulation of this problem and use available IP-solvers for finding an optimized Schedule, called binpacking Schedule. Performance benefits of the new bin-packing Schedule are evaluated via a broad variety of realistic experiments using Backup processin
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SustainIT - Optimizing QoS, performance, and power efficiency of Backup services
2015 Sustainable Internet and ICT for Sustainability (SustainIT), 2015Co-Authors: Ludmila Cherkasova, Alex ZhangAbstract:For most businesses, Backup is a daily operation that needs to reliably protect diverse digital assets distributed across the enterprise. Efficiently processing ever increasing amounts of data residing on multiple desktops, servers, laptops, etc., and providing dynamic recovery capabilities becomes a high priority task for many IT departments. Driven by the advances in cloud computing and Software as a Service (SaaS) delivery model, IT departments are transitioning from providing highly customized services to offering on demand services which can be requested and canceled instantly. Backup service providers must be able to react efficiently to on-demand requests and cannot afford labor intensive resource planning and manual adjustments of Schedules. Our goal is to automate the design of a Backup Schedule that minimizes the overall completion time for a given set of Backup jobs. This problem can be formulated as a resource constrained scheduling problem where a set of n jobs should be Scheduled on ���� machines with given capacities. In this work, we compare the outcome of the integer programming formulation with a heuristic-based job scheduling algorithm, called FlexLBF. The FlexLBF Schedule produces close to optimal results (reducing Backup time 20%-60%) while carrying no additional computing overhead and scaling well to efficiently process large datasets compared to the IP-based solution. Moreover, FlexLBF can be easily analyzed in a simulation environment to further tune a Backup server configuration for achieving given performance objectives while saving power (up to additional 50% in our experiments). It helps to avoid guess-based configuration efforts by system administrators and significantly increase the quality and reliability of implemented solutions.
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DP+IP = Design of Efficient Backup Scheduling
2013Co-Authors: Ludmila Cherkasova, Alex ZhangAbstract:Abstract—Many industries experience an explosion in digital content. This explosion of electronic documents, along with new regulations and document retention rules, sets new requirements for performance efficiency of traditional data protection and archival tools. During a Backup session a predefined set of objects (client filesystems) should be backed up. Traditionally, no information on the expected duration and throughput requirements of different Backup jobs is provided. This may lead to a suboptimal job Schedule that results in the increased Backup session time. In thiswork,wecharacterizeeachBackupjobviatwometrics,called job duration and job throughput. These metrics are derived from collected historic information about Backup jobs during previous Backup sessions. Our goal is to automate the design of a Backup Schedule that minimizes the overall completion time for a given set of Backup jobs. This problem can be formulated as a resource constrained scheduling problem where a set of n jobs should be Scheduled on m machines with given capacities. We provide an integer programming (IP) formulation of this problem and use available IP-solvers for finding an optimized Schedule, called binpacking Schedule. Performance benefits of the new bin-packing Scheduleareevaluatedviaabroadvarietyofrealisticexperiments using Backup processing data from six Backup servers in HP Labs. The new bin-packing job Schedule significantly optimizes the Backup session time (20%-60 % of Backup time reduction). HP Data Protector (DP) is HP’s enterprise Backup offering and it can directly benefit from the designed technique. Moreover, significantlyreducedBackupsessiontimesguaranteeanimproved resource/power usage of the overall Backup solution. I
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CNSM - DP+IP = design of efficient Backup scheduling
2010 International Conference on Network and Service Management, 2010Co-Authors: Ludmila Cherkasova, Alex ZhangAbstract:Many industries experience an explosion in digital content. This explosion of electronic documents, along with new regulations and document retention rules, sets new requirements for performance efficiency of traditional data protection and archival tools. During a Backup session a predefined set of objects (client filesystems) should be backed up. Traditionally, no information on the expected duration and throughput requirements of different Backup jobs is provided. This may lead to a suboptimal job Schedule that results in the increased Backup session time. In this work, we characterize each Backup job via two metrics, called job duration and job throughput. These metrics are derived from collected historic information about Backup jobs during previous Backup sessions. Our goal is to automate the design of a Backup Schedule that minimizes the overall completion time for a given set of Backup jobs. This problem can be formulated as a resource constrained scheduling problem where a set of n jobs should be Scheduled on m machines with given capacities. We provide an integer programming (IP) formulation of this problem and use available IP-solvers for finding an optimized Schedule, called binpacking Schedule. Performance benefits of the new bin-packing Schedule are evaluated via a broad variety of realistic experiments using Backup processing data from six Backup servers in HP Labs. The new bin-packing job Schedule significantly optimizes the Backup session time (20%–60% of Backup time reduction). HP Data Protector (DP) is HP's enterprise Backup offering and it can directly benefit from the designed technique. Moreover, significantly reduced Backup session times guarantee an improved resource/power usage of the overall Backup solution.
James Da Silva - One of the best experts on this subject based on the ideXlab platform.
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The amanda network Backup manager
1993Co-Authors: James Da Silva, Olafur Guthmundsson, Ólafur GuðmundssonAbstract:We present Amanda, a freely redistributable network Backup manager written at the University of Maryland. Amanda is designed to make backing up large networks of data-full workstations to gigabyte tape drives automatic and efficient. Amanda runs on top of standard Unix Backup tools such as dump and tar. It takes care of balancing the Backup Schedule and handling any problems that arise. Amanda runs Backups in parallel to insure a reasonable run time for the nightly Backups, even in the presence of slow computers on the network. Tape labeling insures that the wrong tape is not overwritten. A report detailing any problems is mailed to the system administrator in the morning. In our department, we use Amanda to back up about 35 gigabytes of data in 336 filesystems on more than 130 workstations, using a single 5 gigabyte 8mm tape drive. Nightly runs typically complete in three to four hours. Amanda is currently in daily use at sites around the world
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The Amanda Network Backup Manager
1993Co-Authors: James Da Silva, Olafur GudmundssonAbstract:We present Amanda, a freely redistributable network Backup manager written at the University of Maryland. Amanda is designed to make backing up large networks of data-full workstations to gigabyte tape drives automatic and efficient. Amanda runs on top of standard Unix Backup tools such as dump and gnu tar. It takes care of balancing the Backup Schedule and handling any problems that arise. Amanda runs Backups in parallel to insure a reasonable run time for the nightly Backups, even in the presence of slow computers on the network. Tape labeling insures that the wrong tape is not overwritten. A report detailing any problems is mailed to the system administrator in the morning. In our department, we use Amanda to back up about 35 gigabytes of data in 336 filesystems on more than 130 workstations, using a single 5 gigabyte 8mm tape drive. Nightly runs typically complete in three to four hours. Amanda is currently in daily use at sites around the world. Categories and Subject D..
Ólafur Guðmundsson - One of the best experts on this subject based on the ideXlab platform.
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The amanda network Backup manager
1993Co-Authors: James Da Silva, Olafur Guthmundsson, Ólafur GuðmundssonAbstract:We present Amanda, a freely redistributable network Backup manager written at the University of Maryland. Amanda is designed to make backing up large networks of data-full workstations to gigabyte tape drives automatic and efficient. Amanda runs on top of standard Unix Backup tools such as dump and tar. It takes care of balancing the Backup Schedule and handling any problems that arise. Amanda runs Backups in parallel to insure a reasonable run time for the nightly Backups, even in the presence of slow computers on the network. Tape labeling insures that the wrong tape is not overwritten. A report detailing any problems is mailed to the system administrator in the morning. In our department, we use Amanda to back up about 35 gigabytes of data in 336 filesystems on more than 130 workstations, using a single 5 gigabyte 8mm tape drive. Nightly runs typically complete in three to four hours. Amanda is currently in daily use at sites around the world
Olafur Gudmundsson - One of the best experts on this subject based on the ideXlab platform.
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The Amanda Network Backup Manager
1993Co-Authors: James Da Silva, Olafur GudmundssonAbstract:We present Amanda, a freely redistributable network Backup manager written at the University of Maryland. Amanda is designed to make backing up large networks of data-full workstations to gigabyte tape drives automatic and efficient. Amanda runs on top of standard Unix Backup tools such as dump and gnu tar. It takes care of balancing the Backup Schedule and handling any problems that arise. Amanda runs Backups in parallel to insure a reasonable run time for the nightly Backups, even in the presence of slow computers on the network. Tape labeling insures that the wrong tape is not overwritten. A report detailing any problems is mailed to the system administrator in the morning. In our department, we use Amanda to back up about 35 gigabytes of data in 336 filesystems on more than 130 workstations, using a single 5 gigabyte 8mm tape drive. Nightly runs typically complete in three to four hours. Amanda is currently in daily use at sites around the world. Categories and Subject D..
