References of "Bouvry, Pascal 50001021"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailUAV Fleet Mobility Model with Multiple Pheromones for Tracking Moving Observation Targets
Atten, Christophe UL; Chanouf, Loubna; Danoy, Grégoire UL et al

in 19th European Conference on Applications of Evolutionary Computation (EvoApplications) (2016)

Detailed reference viewed: 213 (31 UL)
Full Text
Peer Reviewed
See detailVoIP Traffic Modelling using Gaussian Mixture Models, Gaussian Processes and Interactive Particle Algorithms
Simionovici, Ana-Maria UL; Tantar, Alexandru; Bouvry, Pascal UL et al

Scientific Conference (2015, December 05)

The paper deals with an important problem in the Voice over IP (VoIP) domain, namely being able to understand and predict the structure of traffic over some given period of time. VoIP traffic has a time ... [more ▼]

The paper deals with an important problem in the Voice over IP (VoIP) domain, namely being able to understand and predict the structure of traffic over some given period of time. VoIP traffic has a time variant structure, e.g. due to sudden peaks, daily or weekly moving patterns of activities, which in turn makes prediction difficult. Obtaining insights about the structure and trends of traffic has important implications when dealing with the nowadays cloud-deployed VoIP services. Prediction techniques are applied to anticipate the incoming traffic, for an efficient distribution of the traffic in the system and allocation of resources. The article looks in a critical manner at a series of machine learning techniques. We namely compare and review (using real VoIP data) the results obtained when using a Gaussian Mixture Model (GMM), Gaussian Processes (GP), and an evolutionary like Interacting Particle Systems based (sampling) algorithm. The experiments consider different setups as to verify the time variant traffic assumption. [less ▲]

Detailed reference viewed: 151 (9 UL)
Full Text
Peer Reviewed
See detailEnergy-Efficient Computation Offloading for Wearable Devices and Smartphones in Mobile Cloud Computing
Ragona, Claudio; Fiandrino, Claudio UL; Kliazovich, Dzmitry UL et al

in IEEE Global Communications Conference (GLOBECOM), San Diego, CA, USA, 2015 (2015, December)

Wearable devices are becoming increasingly popu- lar and are expected to become essential in our everyday life. De- spite continuous improvement of hardware, the lifetime of mobile devices and their ... [more ▼]

Wearable devices are becoming increasingly popu- lar and are expected to become essential in our everyday life. De- spite continuous improvement of hardware, the lifetime of mobile devices and their capabilities still remain a concern. Small size of batteries of smart watches, glasses, helmets and gloves limits the amount of computing, storage and communication resources. Mobile cloud computing can augment the capabilities of wearable devices by helping to execute some of the computing tasks in the cloud. Such computational offloading helps to preserve battery power at the cost of more intensive communications with the cloud. In this paper, we present a model and comprehensive analysis for computational offloading between wearable devices and clouds in realistic setups. [less ▲]

Detailed reference viewed: 403 (21 UL)
Full Text
Peer Reviewed
See detailAn Evaluation Model for Selecting Cloud Services from Commercially Available Cloud Providers
Wagle, Shyam Sharan UL; Guzek, Mateusz UL; Bouvry, Pascal UL et al

in 2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom) (2015, December)

Detailed reference viewed: 172 (16 UL)
Full Text
Peer Reviewed
See detailMetaheuristics for the Virtual Machine Mapping Problem in Clouds
Nesmachnow, Sergio; Dorronsoro, Bernabé UL; Talbi, El-Ghazali et al

in Informatica, Lith. Acad. Sci. (2015), 26(1), 111-134

This article presents sequential and parallel metaheuristics to solve the virtual machines subletting problem in cloud systems, which deals with allocating virtual machine requests into prebooked ... [more ▼]

This article presents sequential and parallel metaheuristics to solve the virtual machines subletting problem in cloud systems, which deals with allocating virtual machine requests into prebooked resources from a cloud broker, maximizing the broker profit. Three metaheuristic are studied: Simulated Annealing, Genetic Algorithm, and hybrid Evolutionary Algorithm. The experimental evaluation over instances accounting for workloads and scenarios using real data from cloud providers, indicates that the parallel hybrid Evolutionary Algorithm is the best method to solve the problem, computing solutions with up to 368.9% profit improvement over greedy heuristics results while accounting for accurate makespan and flowtime values. [less ▲]

Detailed reference viewed: 114 (2 UL)
Full Text
Peer Reviewed
See detailAn LLVM-based Approach to Generate Energy Aware Code by means of MOEAs
Varrette, Sébastien UL; Dorronsorro, Bernabe; Bouvry, Pascal UL

in Proc. of the 7th European Symposium on Computational Intelligence and Mathematics.(ESCIM 2015) (2015, October)

Moderating the energy consumption and building eco-friendly computing infrastructure is of major concerns in the implementation of High Performance Computing (HPC) system, especially when a world- wide ... [more ▼]

Moderating the energy consumption and building eco-friendly computing infrastructure is of major concerns in the implementation of High Performance Computing (HPC) system, especially when a world- wide effort target the production of an Exaflop machine by 2020 within a power envelop of 20 MW. Tracking energy savings can be done at var- ious levels and in this paper, we investigate the automatic generation of energy aware software with the ambition to keep the same level of efficiency, testability, scalability and security. To this end, the Evo-LLVM framework is proposed. Based on the mod- ular LLVM Compiler Infrastructure and exploiting various evolutionary heuristics, our scheme is designed to optimize for a given input source code (written in C) the sequence of LLVM transformations that should be applied to the source code to improve its energy efficiency without degrading its other performance attributes (execution time, parallel or distributed scalability). Measuring this capacity is based on the combi- nation of several metrics optimized simultaneously with Multi-Objective Evolutionary Algorithms (MOEAs). In this position paper, the NSGA- II algorithm is implemented within the Evo-LLVM yet the analysis of more advanced heuristics is in progress. In all cases, the experimental validation of the framework over a pedagogical code sample reveal a drastic improvement of the energy consumed during the execution while maintaining (or even improving) the average execution time. [less ▲]

Detailed reference viewed: 151 (15 UL)
Full Text
Peer Reviewed
See detailMitigating flash crowd effect using connected vehicle technology
Grzybek, Agata UL; Danoy, Grégoire UL; Bouvry, Pascal UL et al

in Vehicular Communications (2015), 2(4),

A Flash Crowd Effect (FCE) occurs when in the case of non-recurring congestion a large portion of drivers follows similar re-routing advice. Consequently, congestion is transferred from one road to ... [more ▼]

A Flash Crowd Effect (FCE) occurs when in the case of non-recurring congestion a large portion of drivers follows similar re-routing advice. Consequently, congestion is transferred from one road to another. Coping with the FCE is challenging, especially if the congestion results from a temporary loss of capacity (e.g. due to a traffic incident). The existing route guidance systems do not address FCE, as they either do not consider the effects of guidance on the rest of the road network, or predict link travel times based on the number of vehicles travelling on the link, which in the case of the loss of capacity is unreliable. We demonstrate that the FCE can be addressed in a distributed way with Vehicle-to-Vehicle (V2V) communication provided by Connected Vehicle (CV) technology. The proposed in-vehicle TrafficEQ system provides vehicles with mixed route guidance strategy—i.e. a route is autonomously chosen by the vehicle with a probability that is inversely proportional to the latest reported travel time on the route. Real-time travel time information is crowd-sourced by TrafficEQ users. Using realistic simulations of incident-related capacity drops on a classic two-route highway example and a realistic urban road network, we demonstrate that TrafficEQ can address the FCE by reducing travel time oscillations among the alternative routes. The system's drawbacks—in particular the occasional necessity of providing incentives to follow the guidance—are discussed. [less ▲]

Detailed reference viewed: 175 (19 UL)
Full Text
Peer Reviewed
See detailPreference-Based Genetic Algorithm for Solving the Bio-Inspired NK Landscape Benchmark
Ferreira Torres, Christof UL; Nielsen, Sune Steinbjorn UL; Danoy, Grégoire UL et al

in 7th European Symposium on Computational Intelligence and Mathematics (ESCIM) (2015, October)

Detailed reference viewed: 112 (25 UL)
Full Text
Peer Reviewed
See detailCloud Service Providers Ranking Based on Service Delivery and Consumer Experience
Wagle, Shyam Sharan UL; Guzek, Mateusz UL; Bouvry, Pascal UL

in 2015 IEEE 4th International Conference on Cloud Networking (CloudNet) (2015, October)

Detailed reference viewed: 139 (7 UL)
Full Text
Peer Reviewed
See detailSurvey on Broadcast Algorithms for Mobile Ad Hoc Networks
Ruiz, Patricia UL; Bouvry, Pascal UL

in ACM Computing Surveys (2015), 48(1),

Networking at any time and any place paves the way for a large number of possible applications in ad hoc networks, from disaster relief in remote areas to network extension. Thus, for the past decades ... [more ▼]

Networking at any time and any place paves the way for a large number of possible applications in ad hoc networks, from disaster relief in remote areas to network extension. Thus, for the past decades, many works have been proposed trying to make ad hoc networks a reality. The importance of broadcasting in networking and the broadcast nature of the wireless medium have encouraged researchers to join their efforts on designing efficient dissemination algorithms for Mobile Ad Hoc Networks (MANETs). The many different challenges that MANETs face, such as limited network resources, network partitions, or energy restrictions, gave rise to many different approaches to overcome one or more of those problems. Therefore, literature reveals a huge variety of techniques that have been proposed for efficient message dissemination. In this article, we make an in-depth review of the existing state-of-the-art techniques, as well as propose a new taxonomy that provides a global overview of the most relevant existing algorithms. [less ▲]

Detailed reference viewed: 137 (5 UL)
Full Text
Peer Reviewed
See detailDistributed Adaptive VoIP Load Balancing in Hybrid Clouds
Cortés-Mendoza, Jorge Mario; Tchernykh, Andrei; Drozdov, Alexander et al

Scientific Conference (2015, September)

Cloud computing as a powerful economic stimulus widely being adopted by many companies. However, the management of cloud infrastructure is a challenging task. Reliability, security, quality of service ... [more ▼]

Cloud computing as a powerful economic stimulus widely being adopted by many companies. However, the management of cloud infrastructure is a challenging task. Reliability, security, quality of service, and cost-efficiency are important issues in these systems. They require resource optimization at multiple layers of the infrastructure and applications. The complexity of cloud computing systems makes infeasible the optimal resource allocation, especially in presence of uncertainty of very dynamic and unpredictable environment. Hence, load balancing algorithms are a fundamental part of the research in cloud computing. We formulate the problem of load balancing in distributed computer environments and review several algorithms. The goal is to understand the main characteristics of dynamic load balancing algorithms and how they can be adapted for the domain of VoIP computations on hybrid clouds. We conclude by showing how none of these works directly addresses the problem space of the considered problem, but do provide a valuable basis for our work. [less ▲]

Detailed reference viewed: 196 (34 UL)
Full Text
Peer Reviewed
See detailPerformance Metrics for Data Center Communication Systems
Fiandrino, Claudio UL; Kliazovich, Dzmitry UL; Bouvry, Pascal UL et al

in 8th IEEE International Conference on Cloud Computing, New York, USA, 2015 (2015, June)

Cloud computing has become a de facto approach for service provisioning over the Internet. It operates relying on a pool of shared computing resources available on demand and usually hosted in data ... [more ▼]

Cloud computing has become a de facto approach for service provisioning over the Internet. It operates relying on a pool of shared computing resources available on demand and usually hosted in data centers. Assessing performance and energy efficiency of data centers becomes fundamental. Industries use a number of metrics to assess efficiency and energy consumption of cloud computing systems, focusing mainly on the efficiency of IT equipment, cooling and power distribution systems. However, none of the existing metrics is precise enough to distinguish and analyze the performance of data center communication systems from IT equipment. This paper proposes a framework of new metrics able to assess performance and energy efficiency of cloud computing communication systems, processes and protocols. The proposed metrics have been evaluated for the most common data center architectures including fat-tree three-tier, BCube and DCell. [less ▲]

Detailed reference viewed: 259 (16 UL)
Full Text
Peer Reviewed
See detailA Survey of Evolutionary Computation for Resource Management of Processing in Cloud Computing
Guzek, Mateusz UL; Bouvry, Pascal UL; Talbi, El-Ghazali

in IEEE Computational Intelligence Magazine (2015), 10(2), 53-67

Cloud computing is significantly reshaping the computing industry. Individuals and small organizations can benefit from using state-of-the-art services and infrastructure, while large companies are ... [more ▼]

Cloud computing is significantly reshaping the computing industry. Individuals and small organizations can benefit from using state-of-the-art services and infrastructure, while large companies are attracted by the flexibility and the speed with which they can obtain the services. Service providers compete to offer the most attractive conditions at the lowest prices. However, the environmental impact and legal aspects of cloud solutions pose additional challenges. Indeed, the new cloud-related techniques for resource virtualization and sharing and the corresponding service level agreements call for new optimization models and solutions. It is important for computational intelligence researchers to understand the novelties introduced by cloud computing. The current survey highlights and classifies key research questions, the current state of the art, and open problems. [less ▲]

Detailed reference viewed: 147 (9 UL)
Full Text
Peer Reviewed
See detailEvalix: Classification and Prediction of Job Resource Consumption on HPC Platforms
Emeras, Joseph UL; Varrette, Sébastien UL; Guzek, Mateusz UL et al

in Proc. of the 19th Intl. Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP'15), part of the 29th IEEE/ACM Intl. Parallel and Distributed Processing Symposium (IPDPS 2015) (2015, May)

At the advent of a wished (or forced) convergence between High Performance Computing (HPC) platforms, stand-alone accelerators and virtualized resources from Cloud Computing (CC) systems, this ar- ticle ... [more ▼]

At the advent of a wished (or forced) convergence between High Performance Computing (HPC) platforms, stand-alone accelerators and virtualized resources from Cloud Computing (CC) systems, this ar- ticle unveils the job prediction component of the Evalix project. This framework aims at an improved efficiency of the underlying Resource and Job Management System (RJMS) within heterogeneous HPC facil- ities by the automatic evaluation and characterization of the submitted workload. The objective is not only to better adapt the scheduled jobs to the available resource capabilities, but also to reduce the energy costs. For that purpose, we collected the resource consumption of all the jobs executed on a production cluster for a period of three months. Based on the analysis then on the classification of the jobs, we computed a resource consumption model. The objective is to train a set of predictors based on the aforementioned model, that will give the estimated CPU, mem- ory and IO used by the jobs. The analysis of the resource consumption highlighted that different classes of jobs have different kinds of resource needs and the classification of the jobs enabled to characterize several application patterns of the users. We also discovered that several users whose resource usage on the cluster is considered as too low, are respon- sible for a loss of CPU time on the order of five years over the considered three month period. The predictors, trained from a supervised learning algorithm, were able to correctly classify a large set of data. We evalu- ated them with three performance indicators that gave an information retrieval rate of 71% to 89% and a probability of accurate prediction be- tween 0.7 and 0.8. The results of this work will be particularly helpful for designing an optimal partitioning of the considered heterogeneous plat- form, taking into consideration the real application needs and thus lead- ing to energy savings and performance improvements. Moreover, apart from the novelty of the contribution, the accurate classification scheme offers new insights of users behavior of interest for the design of future HPC platforms. [less ▲]

Detailed reference viewed: 219 (17 UL)
Full Text
Peer Reviewed
See detailDistributed Cellular Evolutionary Algorithms in a Byzantine Environment
Muszynski, Jakub UL; Varrette, Sébastien UL; Dorronsorro, Bernabé et al

in Proc. of the 18th Intl. Workshop on Nature Inspired Distributed Computing (NIDISC 2015), part of the 29th IEEE/ACM Intl. Parallel and Distributed Processing Symposium (IPDPS 2015) (2015, May)

Distributed parallel computing platforms contribute for a large part to some of the most powerful computers. Such architec- tures are typically based on accelerators (General Purpose com- puting on ... [more ▼]

Distributed parallel computing platforms contribute for a large part to some of the most powerful computers. Such architec- tures are typically based on accelerators (General Purpose com- puting on Graphics Processing Units, Many Integrated Cores e.g Xeon Phi co-processors) and/or a large number of interconnected computing nodes. Obviously, they raise new challenges, typically in terms of scalability, robustness, adaptability and security. At the advent of the quest for Ultrascale Computing Systems, this paper addresses the issue of fault tolerance toward Byzantine failures overs such platforms. Indeed, the inherent unpredictable nature of these errors render their detection, not speaking of their correction, hard or even impossible to perform at large-scale. At this level, Algorithm-Based Fault Tolerance (ABFT) techniques where the fault tolerance scheme is tailored to the algorithm performed, seems the most promising approaches to deal with such failures. In this context, Evolutionary Algorithms (EAs), especially panmictic global parallel EAs, exhibit a remarkable resilience against byzantine failures modeled as cheating faults as demonstrated either empirically or theoretically in previous studies [1], [2]. In this paper, we extend this analysis to the case of distributed EAs based on the cellular model leading to distributed Cellular Evolutionary Algorithms (dCEAs). Our empirical study over a set or reference optimization problem confirm the ABFT nature of dCEAs. To our knowledge, this is the first study of dCEAs under the perspective of cheating issues and crash faults in a domain of distributed computations, thus opening new insights and perspectives for the design of competitive ultra-scale system based on evolutionary programming models. [less ▲]

Detailed reference viewed: 116 (2 UL)
Full Text
Peer Reviewed
See detailFinding a robust configuration for the AEDB information dissemination protocol for mobile ad hoc networks
Ruiz, Patricia; Dorronsoro, Bernabé UL; Talbi, El-Ghazali et al

in Applied Soft Computing (2015), 32

The Adaptive Enhanced Distance Based Broadcasting Protocol, AEDB hereinafter, is an advanced adaptive protocol for information dissemination in mobile ad hoc networks (MANETs). It is based on the Distance ... [more ▼]

The Adaptive Enhanced Distance Based Broadcasting Protocol, AEDB hereinafter, is an advanced adaptive protocol for information dissemination in mobile ad hoc networks (MANETs). It is based on the Distance Based broadcasting protocol, and it acts differently according to local information to minimize the energy and network use, while maximizing the coverage of the broadcasting process. As most of the existing communication protocols, AEDB relies on different thresholds for adapting its behavior to the environment. We propose in this work to look for configurations that induce a stable performance of the protocol in different networks by automatically fine tuning these thresholds thanks to the use of cooperative coevolutionary multi-objective evolutionary algorithms. Finding robust solutions for this problem is important because MANETs have a highly unpredictable and dynamic topology, features that have a strong influence on the performance of the protocol. Consequently, robust solutions that show a good performance under any circumstances are required. In this work, we define different fitness functions that measure robustness of solutions for better guiding the algorithm towards more robust solutions. They are: median, constrained, worst coverage, and worst hypervolume. Results show, that the two worst-case approaches perform better, not only in case of robustness but also in terms of accuracy of the reported AEDB configurations on a large set of networks. [less ▲]

Detailed reference viewed: 101 (1 UL)
Full Text
Peer Reviewed
See detailEnergy efficiency of TCP: An analytical model and its application to reduce energy consumption of the most diffused transport protocol
Usman, Muhammad; Kliazovich, Dzmitry UL; Granelli, Fabrizio et al

in International Journal of Communication Systems (2015)

Energy efficient communications become a challenge for both industries and researchers. Incorporating energy efficiency into the design of network protocols and architectures represents a relevant issue ... [more ▼]

Energy efficient communications become a challenge for both industries and researchers. Incorporating energy efficiency into the design of network protocols and architectures represents a relevant issue in networking research. Currently, very few works address energy efficiency as a fundamental feature of network protocols. This paper benchmarks energy efficiency of TCP to understand the parameters and operational mechanics that determine and contribute to energy consumption. We propose an analytical model with energy consumption to protocol operation cycles and novel optimization techniques for reducing energy consumption of TCP. The evaluation results, obtained from NS2 simulations, demonstrate that even minor modifications of the protocol behavior can bring significant savings of energy. [less ▲]

Detailed reference viewed: 145 (2 UL)
Full Text
Peer Reviewed
See detailCloud Brokering: Current Practices and Upcoming Challenges
Guzek, Mateusz UL; Gniewek, Alicja UL; Bouvry, Pascal UL et al

in IEEE Cloud Computing (2015), 2(2),

Detailed reference viewed: 229 (25 UL)
Full Text
Peer Reviewed
See detailOptimizing communication satellites payload configuration with exact approaches
Stathakis, Apostolos UL; Danoy, Grégoire UL; Bouvry, Pascal UL et al

in Engineering Optimization (2015), 0(0), 1-26

Detailed reference viewed: 162 (28 UL)