References of "Pecero, Johnatan 40020872"
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See detailExact and heuristic approaches to solve the Internet shopping optimization problem with delivery costs
Lopez Loces, Mario; Musial, Jedrzej; Pecero, Johnatan UL et al

in International Journal of Applied Mathematics and Computer Science (2016), 26

Internet shopping has been one of the most common online activities, carried out by millions of users every day. As the number of available offers grows, the difficulty in getting the best one among all ... [more ▼]

Internet shopping has been one of the most common online activities, carried out by millions of users every day. As the number of available offers grows, the difficulty in getting the best one among all the shops increases as well. In this paper we propose an integer linear programming (ILP) model and two heuristic solutions, the MinMin algorithm and the cellular processing algorithm, to tackle the Internet shopping optimization problem with delivery costs. The obtained results improve those achieved by the state-of-the-art heuristics, and for small real case scenarios ILP delivers exact solutions in a reasonable amount of time. [less ▲]

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See detailMulti-objective evolutionary algorithms for energy-aware scheduling on distributed computing systems
Guzek, Mateusz UL; Pecero, Johnatan UL; Dorronsoro, Bernabé UL et al

in Applied Soft Computing (2014), 24

The ongoing increase of energy consumption by IT infrastructures forces data center managers to find innovative ways to improve energy efficiency. The latter is also a focal point for different branches ... [more ▼]

The ongoing increase of energy consumption by IT infrastructures forces data center managers to find innovative ways to improve energy efficiency. The latter is also a focal point for different branches of computer science due to its financial, ecological, political, and technical consequences. One of the answers is given by scheduling combined with dynamic voltage scaling technique to optimize the energy consumption. The way of reasoning is based on the link between current semiconductor technologies and energy state management of processors, where sacrificing the performance can save energy. This paper is devoted to investigate and solve the multi-objective precedence constrained application scheduling problem on a distributed computing system, and it has two main aims: the creation of general algorithms to solve the problem and the examination of the problem by means of the thorough analysis of the results returned by the algorithms. The first aim was achieved in two steps: adaptation of state-of-the-art multi-objective evolutionary algorithms by designing new operators and their validation in terms of performance and energy. The second aim was accomplished by performing an extensive number of algorithms executions on a large and diverse benchmark and the further analysis of performance among the proposed algorithms. Finally, the study proves the validity of the proposed method, points out the best-compared multi-objective algorithm schema, and the most important factors for the algorithms performance. [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 detailA Holistic Model of the Performance and the Energy-Efficiency of Hypervisors in an HPC Environment
Guzek, Mateusz UL; Varrette, Sébastien UL; Plugaru, Valentin UL et al

in Concurrency & Computation : Practice & Experience (2014)

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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 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 detailA Holistic Model of the Performance and the Energy-Efficiency of Hypervisors in an HPC Environment
Guzek, Mateusz UL; Varrette, Sébastien UL; Plugaru, Valentin UL et al

in Energy Efficiency in Large Scale Distributed Systems (2013)

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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 detailEnergy-Aware Scheduling on Multicore Heterogeneous Grid Computing Systems
Nesmachnow, sergio; Dorronsoro, bernabe; Pecero, Johnatan UL et al

in Journal of Grid Computing (2013), 11

We address a multicriteria nonpreemptive energy-aware scheduling problem for computationalGrid systems. This work introduces a new formulation of the scheduling problem for multicore heterogeneous ... [more ▼]

We address a multicriteria nonpreemptive energy-aware scheduling problem for computationalGrid systems. This work introduces a new formulation of the scheduling problem for multicore heterogeneous computational Grid systems in which the minimization of the energy consumption, along with the makespan metric, is considered. We adopt a two-level model, in which a meta-broker agent (level 1) receives all user tasks and schedules them on the available resources, belonging to different local providers (level 2). The computing capacity and energy consumption of resources are taken from real multi-core processors from the main current vendors. Twenty novel list scheduling methods for the problem are proposed, and a comparative analysis of all of them over a large set of problem instances is presented. Additionally, a scalability study is performed in order to analyze the contribution of the best new bi-objective list scheduling heuristics when the problem dimension grows. We conclude after the experimental analysis that accurate trade-off schedules are computed by using the new proposed methods. [less ▲]

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See detailA survey on resource allocation in high performance distributed computing systems
Hussain, Hameed; Malik, Saif Ur Rehman; Hameed, Abdul et al

in Parallel Computing (2013), 39(11), 709-736

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and ... [more ▼]

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature. [less ▲]

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See detailCA-DAG: Communication-Aware Directed Acyclic Graphs for Modeling Cloud Computing Applications
Kliazovich, Dzmitry UL; Pecero, Johnatan UL; Tchernykh, Andrei et al

in Proceedings of the 2013 IEEE Sixth International Conference on Cloud Computing (2013)

The review of the requirements of different cloud applications identified the need to consider communication processes explicitly and equally to the computing tasks. Following this observation, we propose ... [more ▼]

The review of the requirements of different cloud applications identified the need to consider communication processes explicitly and equally to the computing tasks. Following this observation, we propose a new communication-aware model for cloud computing applications, called CA-DAG. This model is based on Directed Acyclic Graphs (DAGs) that in addition to computing vertices include separate vertices to represent communications. Such a representation allows making separate resource allocation decisions, assigning processors to handle computing jobs and network resources for information transmissions, such as application database requests. [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 detailEnergy Efficiency of Knowledge-Free Scheduling in Peer-to-Peer Desktop Grids
Barrondo, Aritz; Tchernykh, Andrei; Shaeffer, Elisa UL et al

in 2012 International Conference on High Performance Computing and Simulation (HPCS) (2012, July 02)

We address knowledge-free Bag-of-Tasks non-preemptive scheduling problem on heterogeneous grids, where scheduling decisions are free from information of resources and application characteristics. We ... [more ▼]

We address knowledge-free Bag-of-Tasks non-preemptive scheduling problem on heterogeneous grids, where scheduling decisions are free from information of resources and application characteristics. We consider a scheduling with task replications to overcome possible random bad resource allocation and ensure good performance. We analyze energy consumption of job allocation strategies based on variations of the replication threshold. In order to provide QoS and minimize energy consumption, we perform a joint analysis of two metrics. A case study is given and corresponding results indicate that proposed strategies reduce energy consumption without significant degradation in performance. [less ▲]

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See detailOn the Energy Optimization for Precedence Constrained Applications using Local Search Algorithms
Pecero, Johnatan UL; Fraire Huacuja, Hector Joaquin; Bouvry, Pascal UL et al

in International Conference on High Performance Computing and Simulation (HPCS), 2012 (2012, July 02)

We investigate the problem of scheduling precedence constrained applications on a distributed heterogeneous computing system with the aim of minimizing schedule length and reducing energy consumption. We ... [more ▼]

We investigate the problem of scheduling precedence constrained applications on a distributed heterogeneous computing system with the aim of minimizing schedule length and reducing energy consumption. We present a scheduling algorithm based on the best-effort idea that promotes local search algorithms and dynamic voltage scaling to reduce energy consumption. The final goal is to maintain a given performance while minimizing energy use. The proposed approach first uses a list-based scheduling algorithm to find near-optimal solutions for schedule length, then local search algorithms with dynamic voltage scaling are applied to reduce energy consumption. However the algorithm it's not allowed to deteriorate the schedule length computed by the best-effort algorithm. We discuss simulation results obtained with sets of real-world applications that emphasize the interest of the approach. [less ▲]

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See detailMemetic Algorithms for Energy-Aware Computation and Communications Optimization in Computing Clusters
Pecero, Johnatan UL; Dorronsoro, Bernabé UL; Guzek, Mateusz UL et al

in Ahmad, Ishfaq; Ranka, Sanjay (Eds.) Handbook energy-aware and green computing (2012)

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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 detailDesigning a Self-organized Approach for Scheduling Bag-of-Tasks
Jimenez Laredo, Juan Luis UL; Dorronsoro, Bernabé UL; Pecero, Johnatan UL et al

in Designing a Self-organized Approach for Scheduling Bag-of-Tasks (2012)

This paper proposes a decentralized and self-organized agent system for dynamically load-balancing tasks arriving in the form of Bags-of-Tasks (BoTs) in large-scale decentralized systems. The approach is ... [more ▼]

This paper proposes a decentralized and self-organized agent system for dynamically load-balancing tasks arriving in the form of Bags-of-Tasks (BoTs) in large-scale decentralized systems. The approach is inspired by the emergent behavior of the sandpile model; a cellular automaton behaving at the edge of chaos. Depending on the state of the cellular automaton, rather different responses may occur when a new task is assigned to a resource. It may change nothing or generate avalanches that reconfigure the state of the system. The proportion between the abundance of avalanches and their sizes shows a power-law relation, a scale-invariant behavior that does not need to be tuned. That means that large –catastrophic– avalanches are very rare but small ones occur very often. Such a smart and emergent behavior fits well with the idea of non-clairvoyant scheduling, where tasks are load balanced into computing resources trying to maximize the performance but without assuming any knowledge on the tasks features. In order to study the viability of the approach, we have conducted an empirical experimentation which shows that the sandpile is able to find near-optimal schedules by reacting differently to different conditions of workloads and architectures. [less ▲]

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