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cesar diaz

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See detailENERGY-EFFICIENT SCHEDULING IN GRID COMPUTING AND RESOURCE ALLOCATION IN OPPORTUNISTIC CLOUD COMPUTING: MODELS AND ALGORITHMS
Diaz, Cesar Orlando UL

Doctoral thesis (2014)

Resource allocation among Heterogenous Computing Systems (HCS) components, such as cluster, grid, or cloud computing can be considered as a service. These systems manage millions of computational ... [more ▼]

Resource allocation among Heterogenous Computing Systems (HCS) components, such as cluster, grid, or cloud computing can be considered as a service. These systems manage millions of computational resources to solve several difficult com- putational problems. Resource allocation and scheduling among these systems are still a hot topic for research purposes. A goal of this research is to find an effi- cient use of these resources proposing a resource allocation and efficient scheduling techniques. Firstly, the relevance of energy consumption in processing elements as well as techniques and policies to support it are presented. It emphasizes in resource allocation algorithms in opportunistic environments and low complexity scheduling heuristics in grid computing environment. In particular, a series of low complexity, scalable, and energy-efficient algorithms for scheduling in grid computing and a resource allocation technique for opportunistic environment are presented. The latest aforementioned technique was evaluated in an opportunistic cloud environment. Three fast and energy-efficient batch mode scheduling novel heuristics were designed, developed, and evaluated to produce fast tasks mapping in HCS. To fully understand their capabilities and limitations, these aforemen- tioned heuristics were studied and compared with a variety of system parameters for their performance and scalability. [less ▲]

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See detailEnergy Savings on a Cloud-based Opportunistic Infrastructure
Pecero, Johnatan UL; Diaz, Cesar UL; Castro, Harold et al

in Service Oriented Computing ICSOC 2013 Workshops (2014)

In this paper, we address energy savings on a Cloud-based opportunistic infrastructure. The infrastructure implements opportunis- tic design concepts to provide basic services, such as virtual CPUs, RAM ... [more ▼]

In this paper, we address energy savings on a Cloud-based opportunistic infrastructure. The infrastructure implements opportunis- tic design concepts to provide basic services, such as virtual CPUs, RAM and Disk while profiting from unused capabilities of desktop computer laboratories in a non-intrusive way. We consider the problem of virtual machines consolidation on the oppor- tunistic cloud computing resources. We investigate four workload packing algorithms that place a set of virtual machines on the least number of physical machines to increase resource utilization and to transition parts of the unused resources into a lower power states or switching off. We em- pirically evaluate these heuristics on real workload traces collected from our experimental opportunistic cloud, called UnaCloud. The final aim is to implement the best strategy on UnaCoud. The results show that a consolidation algorithm implementing a policy taking into account fea- tures and constraints of the opportunistic cloud saves energy more than 40% than related consolidation heuristics, over the percentage earned by the opportunistic environment. [less ▲]

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See detailPerformance Evaluation of an IaaS Opportunistic Cloud Computing
Diaz, Cesar UL; Pecero, Johnatan UL; Bouvry, Pascal UL et al

Poster (2014)

This poster shows the performance evaluation of UnaCloud Opportunistic Computing IaaS. We analyze from an HPC perspective, two virtualization frameworks Virtual Box and VMware ESXi and compare them over ... [more ▼]

This poster shows the performance evaluation of UnaCloud Opportunistic Computing IaaS. We analyze from an HPC perspective, two virtualization frameworks Virtual Box and VMware ESXi and compare them over this particular opportunistic cloud environment. The benchmarks consist of two set of tests, High Performance Linpack and IOzone, that examine the performance and the Input/Output response. The purpose of the experiments is to evaluate the behavior of the different virtual environments over an opportunistic cloud environment and investigate how these are affected by different percentage of end-users. The results show a better performance for Virtual Box than VMware and the other way around for I/O response. Nevertheless, the experiments shows that VBox have more robustness than VMware. [less ▲]

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See detailScalable, Low complexity, and fast greedy scheduling heuristics for highly heterogeneous distributed computing systems
Diaz, Cesar UL; Pecero, Johnatan UL; Bouvry, Pascal UL

in Journal of Supercomputing (2013)

Forheterogeneousdistributedcomputingsystems,importantdesignissues are scalability and system optimization. Given such systems, it is crucial to develop low computational complexity algorithms to schedule ... [more ▼]

Forheterogeneousdistributedcomputingsystems,importantdesignissues are scalability and system optimization. Given such systems, it is crucial to develop low computational complexity algorithms to schedule tasks in a manner that exploits the heterogeneity of the resources and applications. In this paper, we report and evalu- ate three scalable, and fast scheduling heuristics for highly heterogeneous distributed computing systems. We conduct a comprehensive performance evaluation study us- ing simulation. The benchmarking outlines the performance of the schedulers, rep- resenting scalability, makespan, flowtime, computational complexity, and memory utilization. The set of experimental results shows that our heuristics perform as good as the traditional approaches, for makespan and flowtime, while featuring lower com- plexity, lower running time, and lower used memory. The experimental results also detail the various scenarios under which certain algorithms excel and fail. [less ▲]

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See detailGFOG: Green and Flexible Opportunistic Grids.
Castro, Harold; Villamizar, Mario; Sotelo, German et al

in Khan, Samee; Zomaya, Albert; Lizhe, Wang (Eds.) Scalable Computing and Communications. Theory and Practice (2013)

Energy efficiency and high performance computing are the basic design consider- ations across modern-day computing solutions due to different concerns, such as system functioning, operational cost, and ... [more ▼]

Energy efficiency and high performance computing are the basic design consider- ations across modern-day computing solutions due to different concerns, such as system functioning, operational cost, and environmental issues. Opportunistic grid infrastructures offer computational power at low cost focused on harvesting idle computing cycles of existing commodity computing resources. Other than allow- ing the customization of execution environments, virtualization is considered as one key technique to reduce energy consumption in large-scale systems and contributes to the scalability of the system. This work presented an energy efficient approach for opportunistic grids based on virtualization. The experimental results showed that depending on the strategy used to deploy virtual machines on desktop machines, virtu- alization significantly improves the energy efficiency of opportunistic grids compared with dedicated computing systems, without disturbing the owner-user. [less ▲]

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See detailEnergy-aware VM allocation on An Opportunistic Cloud Infrastructure
Diaz, Cesar UL; Castro, Harold; Villamizar, Mario et al

in Proceedings of the 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (2013)

UnaCloud is an opportunistic based cloud infras- tructure (IaaS) that allows to access on-demand computing capabilities using commodity desktops. Although UnaCloud maximizes the use of idle resources to ... [more ▼]

UnaCloud is an opportunistic based cloud infras- tructure (IaaS) that allows to access on-demand computing capabilities using commodity desktops. Although UnaCloud maximizes the use of idle resources to deploy virtual machines, it does not use energy-efficient resource allocation algorithms. In this paper, we design and develop different energy-aware algorithms to operate in an energy-efficient way and at the same time to guarantee the performance of the UnaCloud users. Performance tests with different algorithms and scenarios using real trace workloads from UnaCloud, show how different policies can change the energy consumption patterns and reduce the energy consumption in the opportunistic cloud infrastructure. The results show that some algorithms can reduce the energy-consumption power up to 30% over the percentage earned by the opportunistic environment [less ▲]

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See detailBulding Platform as a Service for High Performance Computing over an Opportunistic Cloud Computing
Sotelo, German; Diaz, Cesar UL; Villamizar, Mario et al

in Algorithms and Architectures for Parallel Processing (2013)

PlatformasaServiceprovidersdeliverdevelopmentandrun- time environments for applications that are hosted on the Cloud. In this paper, we present a Platform as a Service model constructed over a desktop ... [more ▼]

PlatformasaServiceprovidersdeliverdevelopmentandrun- time environments for applications that are hosted on the Cloud. In this paper, we present a Platform as a Service model constructed over a desktop-based Cloud infrastructure for developing high performance computing applications taking advantage of unused resources opportunis- tically. We highlight the key concepts and features of the platform, as well as its innovation on an opportunistic computing and we present the results of several tests showing the performance of the proposed model. [less ▲]

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See detailGreen Flexible Opportunistic Computing with task consolidation and virtualization
Castro, Harold; Villamizar, Mario; Sotelo, German et al

in Cluster Computing (2012)

Energy efficiency and high computing power are basic design considerations across modern-day computing solutions due to different concerns such as system perfor- mance, operational cost, and environmental ... [more ▼]

Energy efficiency and high computing power are basic design considerations across modern-day computing solutions due to different concerns such as system perfor- mance, operational cost, and environmental issues. Desktop Grid and Volunteer Computing System (DGVCS) so called opportunistic infrastructures offer computational power at low cost focused on harvesting idle computing cycles of ex- isting commodity computing resources. Other than allow- ing to customize the end user offer, virtualization is consid- ered as one key techniques to reduce energy consumption in large-scale systems and contributes to the scalability of the system. This paper presents an energy efficient approach for opportunistic infrastructures based on task consolidation and customization of virtual machines. The experimental re- sults with single desktops and complete computer rooms show that virtualization significantly improves the energy-efficiency of opportunistic grids compared with dedicated computing systems without disturbing the end-user. [less ▲]

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See detailImpact of Voltage Levels Number for Energy-aware Bi-objective DAG Scheduling for Multi-processors Systems
Guzek, Mateusz UL; Diaz, Cesar UL; Pecero, Johnatan UL et al

in Advances in Information Technology: 5th International Conference, IAIT 2012, Bangkok, Thailand, December 6-7, 2012, Proceedings (2012)

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See detailGreen Flexible Opportunistic Computing with Virtualization
Castro, Harold; Sotelo, German; Diaz, Cesar UL et al

in Proceedings of the 2011 IEEE 11th International Conference on Computer and Information Technology, CIT'11 (2011)

Energy efficiency and High computing power are basic design considerations across modern-day computing solutions due to different concerns such as system performance, operational cost, and environmental ... [more ▼]

Energy efficiency and High computing power are basic design considerations across modern-day computing solutions due to different concerns such as system performance, operational cost, and environmental issues. Opportunistic grid infrastructures offer computational power at low cost focused on harvesting idle computing cycles of existing commodity computing resources. Other than allowing to customize the end user offer, virtualization is considered as one key tech- niques to reduce energy consumption in large-scale systems and contributes to the scalability of the system. This paper presents an energy efficient approach for opportunistic grids based on virtualization. The experimental results show that virtualization significantly improves the energy efficiency of opportunistic grids compared with dedicated computing sys- tems without disturbing the end-user. [less ▲]

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See detailEnergy-Aware Fast Scheduling Heuristics in Heterogeneous Computing Systems
Diaz, Cesar UL; Guzek, Mateusz UL; Pecero, Johnatan UL et al

in High Performance Computing and Simulation (HPCS), 2011 International Conference on (2011)

In heterogeneous computing systems it is crucial to sched- ule tasks in a manner that exploits the heterogeneity of the resources and applications to optimize systems perfor- mance. Moreover, the energy ... [more ▼]

In heterogeneous computing systems it is crucial to sched- ule tasks in a manner that exploits the heterogeneity of the resources and applications to optimize systems perfor- mance. Moreover, the energy efficiency in these systems is of a great interest due to different concerns such as opera- tional costs and environmental issues associated to carbon emissions. In this paper, we present a series of original low complexity energy efficient algorithms for scheduling. The main idea is to map a task to the machine that executes it fastest while the energy consumption is minimum. On the practical side, the set of experimental results showed that the proposed heuristics perform as efficiently as related ap- proaches, demonstrating their applicability for the consid- ered problem and its good scalability. [less ▲]

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See detailScalable and Energy-Efficient Scheduling Techniques for Large-Scale Systems
Diaz, Cesar UL; Guzek, Mateusz UL; Pecero, Johnatan UL et al

in Computer and Information Technology (CIT), 2011 IEEE 11th International Conference on (2011)

The scalability of a computing system can be identified by at least three components: (a) size, (b) geograph- ical distribution, and (c) administrative constraints. Newer paradigms, such as clouds, grids ... [more ▼]

The scalability of a computing system can be identified by at least three components: (a) size, (b) geograph- ical distribution, and (c) administrative constraints. Newer paradigms, such as clouds, grids, and clusters bring in more parameters to the aforementioned list, namely heterogeneity, energy consumption, and transparency. To optimize the per- formance of a computing system, it is manner that exploits heterogeneity and is scalable. Moreover, newer systems also demand energy efficiency as an integral part of schedulers. In this paper, we evaluate the behavior of low complexity energy- efficient algorithms for scheduling. The set of experimental results showed that the evaluated heuristics perform as effi- ciently as related approaches; demonstrating their applicability and scalability for the considered problem. [less ▲]

Detailed reference viewed: 53 (1 UL)