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Bernabe Dorronsoro

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See detailVoIP Service Model for Multi-objective Scheduling in Cloud Infrastructure
Cortés-Mendoza, Jorge M.; Tchernykh; Simionovici, Ana-Maria UL et al

in International Journal of Metaheuristics (2015), 4(2), 185-203

Voice over IP (VoIP) is very fast growing technology for the delivery of voice communications and multimedia data over internet with lower cost. Early technical solutions mirrored the architecture of the ... [more ▼]

Voice over IP (VoIP) is very fast growing technology for the delivery of voice communications and multimedia data over internet with lower cost. Early technical solutions mirrored the architecture of the legacy telephone network. Now, they have adopted the concept of distributed cloud VoIP. These solutions typically allow dynamic interconnection between users on any domains. However, providers face challenges to use infrastructure in the best efficient and cost-effective ways. Hence, efficient scheduling and load balancing algorithms are a fundamental part of this approach, especially in presence of the uncertainty of a very dynamic and unpredictable environment. In this paper, we formulate the problem of dynamic scheduling of VoIP services in distributed cloud environments and propose a model for bi-objective optimisation. We consider it as the special case of the bin packing problem, and discuss solutions for provider cost optimisation while ensuring quality of service. [less ▲]

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See detailThe sandpile scheduler: How self-organized criticality may lead to dynamic load-balancing
Jimenez Laredo, Juan Luis UL; Bouvry, Pascal UL; Guinand, Frederic et al

in Cluster Computing (2014)

This paper studies a self-organized criticality model called sandpile for dynamically load-balancing tasks arriving in the form of Bag-of-Tasks in large-scale decentralized system. The sandpile is ... [more ▼]

This paper studies a self-organized criticality model called sandpile for dynamically load-balancing tasks arriving in the form of Bag-of-Tasks in large-scale decentralized system. The sandpile is designed as a decentralized agent system characterizing a cellular automaton, which works in a critical state at the edge of chaos. Depending on the state of the cellular automaton, 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 abundance of such avalanches is in power-law relation with their sizes, a scale-invariant behavior that emerges without requiring tuning or control parameters. That means that large—catastrophic—avalanches are very rare but small ones occur very often. Such emergent pattern can be efficiently adapted for non-clairvoyant scheduling, where tasks are load balanced in computing resources trying to maximize the performance but without assuming any knowledge on the tasks features. The algorithm design is experimentally validated showing 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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See detailComputational Intelligence for Cloud Management Current Trends and Opportunities
Tantar, Alexandru-Adrian UL; Nguyen, Anh Quan UL; Bouvry, Pascal UL et al

Scientific Conference (2013, June 21)

The development of large scale data center and cloud computing optimization models led to a wide range of complex issues like scaling, operation cost and energy efficiency. Different approaches were ... [more ▼]

The development of large scale data center and cloud computing optimization models led to a wide range of complex issues like scaling, operation cost and energy efficiency. Different approaches were proposed to this end, including classical resource allocation heuristics, machine learning or stochastic optimization. No consensus exists but a trend towards using many-objective stochastic models became apparent over the past years. This work reviews in brief some of the more recent studies on cloud computing modeling and optimization, and points at notions on stability, convergence, definitions or results that could serve to analyze, respectively build accurate cloud computing models. A very brief discussion of simulation frameworks that include support for energy-aware components is also given. [less ▲]

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See detailCellular genetic algorithms without additional parameters
Dorronsoro, Bernabe; Bouvry, Pascal UL

in Journal of Supercomputing (2013), 63(3), 816-835

Cellular genetic algorithms (cGAs) are a kind of genetic algorithms (GAs) with decentralized population in which interactions among individuals are restricted to close ones. The use of decentralized ... [more ▼]

Cellular genetic algorithms (cGAs) are a kind of genetic algorithms (GAs) with decentralized population in which interactions among individuals are restricted to close ones. The use of decentralized populations in GAs allows to keep the population diversity for longer, usually resulting in a better exploration of the search space and, therefore, in a better performance of the algorithm. However, it supposes the need of several new parameters that have a major impact on the behavior of the algorithm. In the case of cGAs, these parameters are the population and neighborhood shapes. We propose in this work two innovative cGAs with new adaptive techniques that allow removing the neighborhood and population shape from the algorithm’s configuration. As a result, the new adaptive cGAs are highly competitive (statistically) with all the compared cGAs in terms of the average solutions found in the continuous and combinatorial domains, while finding, in general, the best solutions for the considered problems, and with less computational effort. [less ▲]

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See detailEvolutionary algorithms based on game theory and cellular automata with coalitions
Dorronsoro, Bernabe; Burguillo, J.C.; Peleteiro, A. et al

in Zelinka, I.; Snasel, V.; Abraham, A. (Eds.) Handbook of Optimization (2013)

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See detailA Parallel Multi-objective Local Search for AEDB Protocol Tuning
Iturriaga, Santiago; Ruiz, Patricia UL; Nesmachnow, Sergio et al

in IEEE International Parallel and Distributed Processing Simposium (2013)

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See detailEnergy Efficient Scheduling in Heterogeneous Systems with a Parallel Multiobjective Local Search
Iturriaga, Santiago; Nesmachnow, Sergio; Dorronsoro, Bernabe et al

in Computing and Informatics Journal (2013), 32(2), 273-294

This article introduces ME-MLS, an e cient multithreading local search algorithm for solving the multiobjective scheduling problem in heterogeneous com- puting systems. We consider the minimization of ... [more ▼]

This article introduces ME-MLS, an e cient multithreading local search algorithm for solving the multiobjective scheduling problem in heterogeneous com- puting systems. We consider the minimization of both the makespan and energy consumption objectives. The proposed method follows a fully multiobjective ap- proach, applying a Pareto-based dominance search that is executed in parallel by using several threads. The experimental analysis demonstrates that the new multi- threading algorithm outperforms a set of fast and accurate two-phases deterministic heuristics based on the traditional MinMin. The new ME-MLS method is able to achieve signi cant improvements in both makespan and energy consumption objec- tives in reduced execution times for a large set of testbed instances, while exhibiting a near linear speedup behavior when using up to 24 threads. [less ▲]

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See detailList scheduling heuristics for virtual machine mapping in cloud systems
nesmachnow, sergio; iturriaga, santiago; dorronsoro, bernabe et al

in VI Latin American Symposium on High Performance Computing (HPCLatam) (2013)

This article introduces the formulation of the VirtualMachine Planning Problem in cloud computing systems. It deals with the efficient allocation of a set of virtual machine requests from customers into ... [more ▼]

This article introduces the formulation of the VirtualMachine Planning Problem in cloud computing systems. It deals with the efficient allocation of a set of virtual machine requests from customers into the available pre-booked resources the broker has in a number of cloud providers, maximizing the broker profit. Eight list scheduling heuristics are proposed to solve the problem, by taking into account different criteria for mapping request to available virtual machines. The experimental evaluation analyzes the profit, makespan, and flowtime results of the proposed methods over a set of 400 problem instances that account for realistic workloads and scenarios using real data from cloud providers. [less ▲]

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See detailOversized Populations and Cooperative Selection: Dealing with Massive Resources in Parallel Infrastructures
Jimenez Laredo, Juan Luis UL; Dorronsoro, Bernabe; Fernandes, Carlos et al

in Nicosia, G.; Pardalos, P. (Eds.) Learning and Intelligent Optimization (2013)

This paper proposes a new selection scheme for Evolutionary Algorithms (EAs) based on altruistic cooperation between individuals. Cooperation takes place every time an individual undergoes selection: the ... [more ▼]

This paper proposes a new selection scheme for Evolutionary Algorithms (EAs) based on altruistic cooperation between individuals. Cooperation takes place every time an individual undergoes selection: the individual decreases its own fitness in order to improve the mating chances of worse individuals. On the one hand, the selection scheme guarantees that the genetic material of fitter individuals passes to subsequent generations as to decrease their fitnesses individuals have to be firstly selected. On the other hand, the scheme restricts the number of times an individual can be selected not to take over the entire population. We conduct an empirical study for a parallel EA version where cooperative selection scheme is shown to outperform binary tournament: both selection schemes yield the same qualities of solutions but cooperative selection always improves the times to solutions. [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 parallel hybrid evolutionary algorithm for the optimization of broker virtual machines subletting in cloud systems
iturriaga, Santiago; Nesmachnow, Sergio; Dorronsoro, Bernabe et al

in International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (2013)

This article presents a new parallel hybrid evolutionary algorithm to solve the problem of virtual machines subletting in cloud systems. The problem deals with the efficient allocation of a set of virtual ... [more ▼]

This article presents a new parallel hybrid evolutionary algorithm to solve the problem of virtual machines subletting in cloud systems. The problem deals with the efficient allocation of a set of virtual machine requests from customers into available pre-booked resources from a cloud broker, in order to maximize the broker profit. The proposed parallel algorithm uses a distributed subpopulations model, and a Simulated Annealing operator. The experimental evaluation analyzes the profit and makespan results of the proposed methods over a set of problem instances that account for realistic workloads and scenarios using real data from cloud providers. A comparison with greedy heuristics indicates that the proposed method is able to compute solutions with up to 133.8% improvement in the profit values, while accounting for accurate makespan results. [less ▲]

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See detailFinding Scalable Configurations for AEDB Broadcasting Protocol using Multi-objective Evolutionary
Ruiz, Patricia UL; Dorronsoro, Bernabe; Bouvry, Pascal UL

in Cluster Computing (2012), 16

Detailed reference viewed: 43 (2 UL)