References of "Bouvry, Pascal 50001021"
     in
Bookmark and Share    
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: 151 (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: 207 (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: 270 (16 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: 126 (2 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: 150 (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: 231 (17 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: 111 (1 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: 248 (29 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: 181 (2 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: 179 (31 UL)
Full Text
Peer Reviewed
See detailPerformance Evaluation of the XDEM framework on the OpenStack Cloud Computing Middleware
Besseron, Xavier UL; Plugaru, Valentin UL; Mahmoudi, Amir Houshang UL et al

in Proceedings of the Fourth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering (2015, February)

As Cloud Computing services become ever more prominent, it appears necessary to assess the efficiency of these solutions. This paper presents a performance evaluation of the OpenStack Cloud Computing ... [more ▼]

As Cloud Computing services become ever more prominent, it appears necessary to assess the efficiency of these solutions. This paper presents a performance evaluation of the OpenStack Cloud Computing middleware using our XDEM application simulating the pyrolysis of biomass as a benchmark. We propose a systematic study based on a fully automated benchmarking framework to evaluate 3 different configurations: Native (i.e. no virtualization), OpenStack with KVM and XEN hypervisors. Our approach features the following advantages: real user application, the fair comparison using the same hardware, the large scale distributed execution, while fully automated and reproducible. Experiments has been run on two different clusters, using up to 432 cores. Results show a moderate overhead for sequential execution and a significant penalty for distributed execution under the Cloud middleware. The overhead on multiple nodes is between 10% and 30% for OpenStack/KVM and 30% and 60% for OpenStack/XEN. [less ▲]

Detailed reference viewed: 370 (51 UL)
Peer Reviewed
See detailEnergy efficiency in HPC Data Centers: Latest Advances to Build the Path to Exascale
Varrette, Sébastien UL; Bouvry, Pascal UL; Jarus, M. et al

in Handbook on Data Centers (2015)

Detailed reference viewed: 139 (3 UL)
Peer Reviewed
See detailEnergy Efficiency and High-Performance Computing
Bouvry, Pascal UL; Chetsa, G. L. T.; Costa, G. Da et al

in Pierson, J.-M. (Ed.) Large-scale Distributed Systems and Energy Efficiency: A Holistic View (2015)

Detailed reference viewed: 149 (5 UL)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 158 (17 UL)
Full Text
Peer Reviewed
See detailEnergy-efficient Data Replication in Cloud Computing Datacenters
Boru, Dejene; Kliazovich, Dzmitry UL; Granelli, Fabrizio et al

in Cluster Computing (2015), 18(1), 385-402

Cloud computing is an emerging paradigm that provides computing, communication and storage resources as a service over a network. Communication resources often become a bottleneck in service provisioning ... [more ▼]

Cloud computing is an emerging paradigm that provides computing, communication and storage resources as a service over a network. Communication resources often become a bottleneck in service provisioning for many cloud applications. Therefore, data replication which brings data (e.g., databases) closer to data consumers (e.g., cloud applications) is seen as a promising solution. It allows minimizing network delays and bandwidth usage. In this paper we study data replication in cloud computing data centers. Unlike other approaches available in the literature, we consider both energy efficiency and bandwidth consumption of the system. This is in addition to the improved quality of service QoS obtained as a result of the reduced communication delays. The evaluation results, obtained from both mathematical model and extensive simulations, help to unveil performance and energy efficiency tradeoffs as well as guide the design of future data replication solutions. [less ▲]

Detailed reference viewed: 205 (8 UL)
Full Text
Peer Reviewed
See detailHEROS: Energy-Efficient Load Balancing for Heterogeneous Data Centers
Guzek, Mateusz UL; Kliazovich, Dzmitry UL; Bouvry, Pascal UL

in 8th IEEE International Conference on Cloud Computing IEEE CLOUD 2015 (2015)

Detailed reference viewed: 204 (7 UL)
Full Text
Peer Reviewed
See detailModels for Efficient Data Replication in Cloud Computing Datacenters
Boru, Dejene; Kliazovich, Dzmitry UL; Granelli, Fabrizio et al

in IEEE International Conference on Communications (ICC), London, UK, 2015 (2015)

Cloud computing is a computing model where users access ICT services and resources without regard to where the services are hosted. Communication resources often become a bottleneck in service ... [more ▼]

Cloud computing is a computing model where users access ICT services and resources without regard to where the services are hosted. Communication resources often become a bottleneck in service provisioning for many cloud applications. Therefore, data replication which brings data (e.g., databases) closer to data consumers (e.g., cloud applications) is seen as a promising solution. In this paper we present models for energy consumption and bandwidth demand of database access in cloud computing datacenter. In addition we propose an energy efficient replication strategy based on the proposed models which results in improved Quality of Service (QoS) with reduced communication delays. The evaluation results obtained with extensive simulations help to unveil performance and energy efficiency tradeoffs as well as guide the design of future data replication solutions. [less ▲]

Detailed reference viewed: 262 (5 UL)
Full Text
Peer Reviewed
See detailPerformance and Energy Efficiency Metrics for Communication Systems of Cloud Computing Data Centers
Fiandrino, Claudio UL; Kliazovich, Dzmitry UL; Bouvry, Pascal UL et al

in IEEE Transactions on Cloud Computing (2015)

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, DCell and Hypercube. [less ▲]

Detailed reference viewed: 254 (31 UL)
Full Text
Peer Reviewed
See detailNetwork-Assisted Offloading for Mobile Cloud Applications
Fiandrino, Claudio UL; Kliazovich, Dzmitry UL; Bouvry, Pascal UL et al

in IEEE International Conference on Communications (ICC), London, UK, 2015 (2015)

Data traffic from mobile devices experiences unprecedented growth that current cellular network capacities cannot sustain. Traffic offloading to other type of networks such as WiFi emerged as a valid ... [more ▼]

Data traffic from mobile devices experiences unprecedented growth that current cellular network capacities cannot sustain. Traffic offloading to other type of networks such as WiFi emerged as a valid solution to relieve the load in cellular networks. In this paper, we propose novel solution, which unlike other existing methodologies uses information provided by the cellular network to optimize traffic offloading. The provided information includes channel usage statistics, user mobility patterns, information about available resources and other parameters. The offloading decisions aim at optimizing the balance between user and application requirements with availability of network resources. We validated the effectiveness of the proposed solution through simulations with NS-3 network simulator. The results show the capability of the solution in relieving cellular load while guaranteeing user QoS. [less ▲]

Detailed reference viewed: 283 (27 UL)