References of "Bouvry, Pascal 50001021"
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See detailA Scalable Parallel Cooperative Coevolutionary PSO Algorithm for Multi-objective Optimization
Atashpendar, Arash UL; Dorronsoro, Bernabé; Danoy, Grégoire UL et al

in Journal of Parallel & Distributed Computing (2017)

We present a parallel multi-objective cooperative coevolutionary variant of the Speed-constrained Multi-objective Particle Swarm Optimization (SMPSO) algorithm. The algorithm, called CCSMPSO, is the first ... [more ▼]

We present a parallel multi-objective cooperative coevolutionary variant of the Speed-constrained Multi-objective Particle Swarm Optimization (SMPSO) algorithm. The algorithm, called CCSMPSO, is the first multi-objective cooperative coevolutionary algorithm based on PSO in the literature. SMPSO adopts a strategy for limiting the velocity of the particles that prevents them from having erratic movements. This characteristic provides the algorithm with a high degree of reliability. In order to demonstrate the effectiveness of CCSMPSO, we compare our work with the original SMPSO and three different state-of-the-art multi-objective CC metaheuristics, namely CCNSGA-II, CCSPEA2 and CCMOCell, along with their original sequential counterparts. Our experiments indicate that our proposed solution, CCSMPSO, offers significant computational speedups, a higher convergence speed and better or comparable results in terms of solution quality, when evaluated against three other CC algorithms and four state-of-the-art optimizers (namely SMPSO, NSGA-II, SPEA2, and MOCell), respectively. We then provide a scalability analysis, which consists of two studies. First, we analyze how the algorithms scale when varying the problem size, i.e., the number of variables. Second, we analyze their scalability in terms of parallelization, i.e., the impact of using more computational cores on the quality of solutions and on the execution time of the algorithms. Three different criteria are used for making the comparisons, namely the quality of the resulting approximation sets, average computational time and the convergence speed to the Pareto front. [less ▲]

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See detailReal-Time Virtual Network Function (VNF) Migration toward Low Network Latency in Cloud Environments
Cho, Daewoong; Taheri, Javid; Zomaya, Albert Y. et al

in IEEE 10th International Conference on Cloud Computing (CLOUD), 2017 (2017, June)

Network Function Virtualization (NFV) is an emerging network architecture to increase flexibility and agility within operator's networks by placing virtualized services on demand in Cloud data centers ... [more ▼]

Network Function Virtualization (NFV) is an emerging network architecture to increase flexibility and agility within operator's networks by placing virtualized services on demand in Cloud data centers (CDCs). One of the main challenges for the NFV environment is how to minimize network latency in the rapidly changing network environments. Although many researchers have already studied in the field of Virtual Machine (VM) migration and Virtual Network Function (VNF) placement for efficient resource management in CDCs, VNF migration problem for low network latency among VNFs has not been studied yet to the best of our knowledge. To address this issue in this article, we i) formulate the VNF migration problem and ii) develop a novel VNF migration algorithm called VNF Real-time Migration (VNF-RM) for lower network latency in dynamically changing resource availability. As a result of experiments, the effectiveness of our algorithm is demonstrated by reducing network latency by up to 70.90% after latency-aware VNF migrations. [less ▲]

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See detailLoad-Aware Strategies for Cloud-Based VoIP Optimization with VM Startup Prediction
Cortes-Mendoza, Jorge M.; Tchernykh, Andrei; Feoktistov, Alexander et al

in IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2017 (2017, June)

In this paper, we address cloud VoIP scheduling strategies to provide appropriate levels of quality of service to users, and cost to VoIP service providers. This bi-objective focus is reasonable and ... [more ▼]

In this paper, we address cloud VoIP scheduling strategies to provide appropriate levels of quality of service to users, and cost to VoIP service providers. This bi-objective focus is reasonable and representative for real installations and applications. We conduct comprehensive simulation on real data of twenty three on-line non-clairvoyant scheduling strategies with fixed threshold of utilization to request VMs, and twenty strategies with dynamic prediction of the load. We show that our load-aware with predictions strategies outperform the known ones providing suitable quality of service and lower cost. The robustness of these strategies is also analyzed varying VM startup time delays to deal with realistic VoIP cloud environments. [less ▲]

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See detailCost analysis of Smart Lighting Solutions for Smart Cities
Cacciatore, Giuseppe; Fiandrino, Claudio UL; Kliazovich, Dzmitry UL et al

in IEEE International Conference on Communications (ICC), Paris, France, 2017 (2017, May)

Lighting is an essential community service, but current implementations are not energy efficient and impact on the energy budget of the municipalities for at least 40\%. In this paper, we propose ... [more ▼]

Lighting is an essential community service, but current implementations are not energy efficient and impact on the energy budget of the municipalities for at least 40\%. In this paper, we propose heuristics and devise a comparison methodology for new smart lighting solutions in next generation smart cities. The proposed smart lighting techniques make use of Internet of Things (IoT) augmented lamppost, which save energy by turning off or dimming the light according to the presence of citizens. Assessing costs and benefits in adopting the new smart lighting solutions is a pillar step for municipalities to foster real implementation. For evaluation purposes, we have developed a custom simulator which enables the deployment of lampposts in realistic urban environments. The citizens travel on foot along the streets and trigger activation of the lampposts according to the proposed heuristics. For the city of Luxembourg, the results highlight that replacing all existing lamps with LEDs and dimming light intensity according to the presence of users nearby the lampposts is convenient and provides an economical return already after the first year of deployment. [less ▲]

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See detailEnergy Efficient Data Collection in Opportunistic Mobile Crowdsensing Architectures for Smart Cities
Capponi, Andrea UL; Fiandrino, Claudio UL; Kliazovich, Dzmitry UL et al

in 3rd IEEE INFOCOM Workshop on Smart Cites and Urban Computing (2017, May)

Smart cities employ latest information and communication technologies to enhance services for citizens. Sensing is essential to monitor current status of infrastructures and the environment. In Mobile ... [more ▼]

Smart cities employ latest information and communication technologies to enhance services for citizens. Sensing is essential to monitor current status of infrastructures and the environment. In Mobile Crowdsensing (MCS), citizens participate in the sensing process contributing data with their mobile devices such as smartphones, tablets and wearables. To be effective, MCS systems require a large number of users to contribute data. While several studies focus on developing efficient incentive mechanisms to foster user participation, data collection policies still require investigation. In this paper, we propose a novel distributed and energy-efficient framework for data collection in opportunistic MCS architectures. Opportunistic sensing systems require minimal intervention from the user side as sensing decisions are application- or device-driven. The proposed framework minimizes the cost of both sensing and reporting, while maximizing the utility of data collection and, as a result, the quality of contributed information. We evaluate performance of the framework with simulations, performed in a real urban environment and with a large number of participants. The simulation results verify cost-effectiveness of the framework and assess efficiency of the data generation process. [less ▲]

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See detailImpact du mécanisme chaotique sur l’optimisation d’un modèle de mobilité pour un essaim de drones devant réaliser une couverture de zone
Rosalie, Martin UL; Danoy, Grégoire UL; Chaumette, Serge et al

in Falcon, Eric; Lefranc, Marc; Pétrélis, François (Eds.) et al Comptes-rendus de la 20e Rencontre du Non Linéaire (2017, March)

Solution of differential equations system can be chaotic attractors with various chaotic mechanisms. In this paper we highlight that the use of these chaotic mechanisms permits to enhance the ... [more ▼]

Solution of differential equations system can be chaotic attractors with various chaotic mechanisms. In this paper we highlight that the use of these chaotic mechanisms permits to enhance the diversification of metaheuristics. We applied our approach to the coverage problem using a swarm of UAVs where the diversification of an ant colony algorithm is enhanced by chaos coming from Ma system and Rössler system. [less ▲]

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See detailA Cost-Effective Distributed Framework for Data Collection in Cloud-based Mobile Crowd Sensing Architectures
Capponi, Andrea UL; Fiandrino, Claudio UL; Kliazovich, Dzmitry UL et al

in IEEE Transactions on Sustainable Computing (2017)

Mobile crowd sensing received significant attention in the recent years and has become a popular paradigm for sensing. It operates relying on the rich set of built-in sensors equipped in mobile devices ... [more ▼]

Mobile crowd sensing received significant attention in the recent years and has become a popular paradigm for sensing. It operates relying on the rich set of built-in sensors equipped in mobile devices, such as smartphones, tablets and wearable devices. To be effective, mobile crowd sensing systems require a large number of users to contribute data. While several studies focus on developing efficient incentive mechanisms to foster user participation, data collection policies still require investigation. In this paper, we propose a novel distributed and sustainable framework for gathering information in cloud-based mobile crowd sensing systems with opportunistic reporting. The proposed framework minimizes cost of both sensing and reporting, while maximizing the utility of data collection and, as a result, the quality of contributed information. Analytical and simulation results provide performance evaluation for the proposed framework by providing a fine-grained analysis of the energy consumed. The simulations, performed in a real urban environment and with a large number of participants, aim at verifying the performance and scalability of the proposed approach on a large scale under different user arrival patterns. [less ▲]

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See detailCrowdSenSim: a Simulation Platform for Mobile Crowdsensing in Realistic Urban Environments
Fiandrino, Claudio UL; Capponi, Andrea UL; Cacciatore, Giuseppe UL et al

in IEEE Access (2017)

Smart cities take advantage of recent ICT developments to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the ... [more ▼]

Smart cities take advantage of recent ICT developments to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the Internet more pervasive where objects equipped with computing, storage and sensing capabilities are interconnected with communication technologies. Because of the widespread diffusion of IoT devices, applying the IoT paradigm to smart cities is an excellent solution to build sustainable Information and Communication Technology (ICT) platforms. Having citizens involved in the process through mobile crowdsensing (MCS) techniques augments capabilities of these ICT platforms without additional costs. For proper operation, MCS systems require the contribution from a large number of participants. Simulations are therefore a candidate tool to assess the performance of MCS systems. In this paper, we illustrate the design of CrowdSenSim, a simulator for mobile crowdsensing. CrowdSenSim is designed specifically for realistic urban environments and smart cities services. We demonstrate the effectiveness of CrowdSenSim for the most popular MCS sensing paradigms (participatory and opportunistic) and we present its applicability using a smart public street lighting scenario. [less ▲]

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See detailLoad Balancing at the Edge of Chaos: How Can Self-Organized Criticality Lead to Energy-Efficient Computing
Laredo, Jean-Luis; Guinand, Frédéric; Damien, Olivier et al

in IEEE Transactions on Parallel & Distributed Systems (2017), 28

This paper investigates a self-organized critical approach for dynamically load-balancing computational workloads. The proposed model is based on the Bak-Tang-Wiesenfeld sandpile: a cellular automaton ... [more ▼]

This paper investigates a self-organized critical approach for dynamically load-balancing computational workloads. The proposed model is based on the Bak-Tang-Wiesenfeld sandpile: a cellular automaton that works in a critical regime at the edge of chaos. In analogy to grains of sand, tasks arrive, pile up and slip through the different processing elements or sites of the system. When a pile exceeds a certain threshold, it collapses and initiates an avalanche of migrating tasks, i.e. producing load-balancing. We show that the frequency of such avalanches is in power-law relation with their sizes, a scale-invariant fingerprint of self-organized criticality that emerges without any tuning of parameters. Such an emergent pattern has organic properties such as the self-organization of tasks into resources or the self-optimization of the computing performance. The conducted experimentation also reveals that the system is in balanced (i.e. not driving to overloaded or underutilized resources) as long as the arrival rate of tasks equals the processing power of the system. Taking advantage of this fact, we hypothesize that the processing elements can be turned on and off depending on the state of the workload as to maximize the utilization of resources. An interesting side-effect is that the overall energy consumption of the system is minimized without compromising the quality of service. [less ▲]

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See detailDefending Against Intrusion of Malicious UAVs with Networked UAV Defense Swarms
Brust, Matthias R. UL; Danoy, Grégoire UL; Bouvry, Pascal UL et al

in 42nd IEEE Conference on Local Computer Networks (2017)

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See detailTarget Tracking Optimization of UAV Swarms Based on Dual-Pheromone Clustering
Brust, Matthias R. UL; Zurad, Maciej UL; Hentges, Laurent Philippe UL et al

in CYBCONF 2017-12-13 09:39:53 +0000 2017-12-13 09:39:53 +0000 (2017)

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See detailBayesian Optimization Approach of General Bi-level Problems
Kieffer, Emmanuel UL; Danoy, Grégoire UL; Bouvry, Pascal UL et al

in Proceedings of the Genetic and Evolutionary Computation Conference Companion (2017)

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See detailA new modeling approach for the biobjective exact optimization of satellite payload configuration
Kieffer, Emmanuel UL; Danoy, Grégoire UL; Bouvry, Pascal UL et al

in International Transactions in Operational Research (2017)

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See detailSelf-Regulated Multi-criteria Decision Analysis: An Autonomous Brokerage-Based Approach for Service Provider Ranking in the Cloud
Wasim, Muhammad Umer UL; Ibrahim, Abdallah Ali Zainelabden Abdallah UL; Bouvry, Pascal UL et al

in 9th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2017), December 11-14, Hong Kong China. (2017)

The use of multi-criteria decision analysis (MCDA) by online broker to rank different service providers in the Cloud is based upon criteria provided by a customer. However, such ranking is prone to bias ... [more ▼]

The use of multi-criteria decision analysis (MCDA) by online broker to rank different service providers in the Cloud is based upon criteria provided by a customer. However, such ranking is prone to bias if the customer has insufficient domain knowledge. He/she may exclude relevant or include irrelevant criterion termed as ’misspecification of criterion’. This causes structural uncertainty within the MCDA leading to selection of suboptimal service provider by online broker. To cater such issue, we propose a self-regulated MCDA, which uses notion of factor analysis from the field of statistics. Two QoS based datasets were used for evaluation of proposed model. The prior dataset i.e., feedback from customers, was compiled using leading review websites such as Cloud Hosting Reviews, Best Cloud Computing Providers, and Cloud Storage Reviews and Ratings. The later dataset i.e., feedback from servers, was generated from Cloud brokerage architecture that was emulated using high performance computing (HPC) cluster at University of Luxembourg (HPC @ Uni.lu). The results show better performance of proposed model as compared to its counterparts in the field. The beneficiary of the research would be enterprises that view insufficient domain knowledge as a limiting factor for acquisition of Cloud services. [less ▲]

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See detailMin_c: Heterogeneous concentration policy for energy-aware scheduling of jobs with resource contention
Armenta-Cano, F.A.; Tchernykh, A.; Cortes-Mendoza, J.M. et al

in Programming & Computer Software (2017), 43(3), 204-215

In this paper, we address energy-aware online scheduling of jobs with resource contention. We propose an optimization model and present new approach to resource allocation with job concentration taking ... [more ▼]

In this paper, we address energy-aware online scheduling of jobs with resource contention. We propose an optimization model and present new approach to resource allocation with job concentration taking into account types of applications and heterogeneous workloads that could include CPU-intensive, diskintensive, I/O-intensive, memory-intensive, network-intensive, and other applications. When jobs of one type are allocated to the same resource, they may create a bottleneck and resource contention either in CPU, memory, disk or network. It may result in degradation of the system performance and increasing energy consumption. We focus on energy characteristics of applications, and show that an intelligent allocation strategy can further improve energy consumption compared with traditional approaches. We propose heterogeneous job consolidation algorithms and validate them by conducting a performance evaluation study using the Cloud Sim toolkit under different scenarios and real data. We analyze several scheduling algorithms depending on the type and amount of information they require. [less ▲]

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See detailLaw as a Service (LaaS): Enabling Legal Protection over a Blockchain Network
Wasim, Muhammad Umer UL; Ibrahim, Abdallah Ali Zainelabden Abdallah UL; Bouvry, Pascal UL et al

in 14th International Conference on Smart Cities: Improving Quality of Life using ICT & IoT (HONET-ICT 17), October 09-11, Irbid Jordan. (2017)

Breaches in online contracts (Service Level Agreements, SLAs) are usually compensated by gift vouchers at present, however as the online contracts emerge towards smart contracts, the breaches could ... [more ▼]

Breaches in online contracts (Service Level Agreements, SLAs) are usually compensated by gift vouchers at present, however as the online contracts emerge towards smart contracts, the breaches could potentially lead to court injunctions over blockchains. This research proposes Probability based Factor Model (PFM) that can be implemented over the blockchain to automatically identify breaches that can cause substantial damage and have high probability for recurrence. PFM can also issue court injunctions for the breaches. The underlying concept in PFM is built upon the notion of factor analysis and stochastic modeling from the discipline of Data Science. High performance computing (HPC) cluster at University of Luxembourg (HPC @ Uni.lu) and docker (a software container platform) were used to emulate contractual environment of three service providers: Redis, MongoDB, and Memcached Servers. The results showed that court injunction(s) was issued only for Redis and MongoDB Servers. Technically, this difference could be attributed to the fact that Memcached is simply used for caching and therefore, it is less prone to breach of contract. Whereas, Redis and MongoDB as databases and message brokers are performing more complex operations and are more likely to cause a breach. This research will benefit enterprises that view breach of contract as a limiting factor for implementation of smart contract in cyber physical system or internet of things. [less ▲]

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See detailUsing Virtual Desktop Infrastructure to Improve Power Efficiency in Grinfy System
Ibrahim, Abdallah Ali Zainelabden Abdallah UL; Kliazovich, Dzmitry UL; Bouvry, Pascal UL et al

in IEEE 8th International Conference on Cloud Computing Technology and Science(CloudCom), Luxembourg 2016 (2016, December 13)

Saving power becomes one of the main objectives in information technology industry and research. Companies consume a lot of money in the shape of power consuming. Virtual Desktop Infrastructure (VDI) is a ... [more ▼]

Saving power becomes one of the main objectives in information technology industry and research. Companies consume a lot of money in the shape of power consuming. Virtual Desktop Infrastructure (VDI) is a new shape of delivering operating systems remotely. Operating systems are executing in a cloud data center. Users desktops and applications can be accessed by using thin client devices. Thin client device is consisting of screen attached with small CPU. VDI has benefits in terms of cost reduction and energy saving. In this paper, we increase the power saved by Grinfy system. Without VDI, Grinfy can save at least 30% of energy consumption to its users companies. By integrating VDI in computing systems and using Grinfy, the power efficiency and saving can be improved and save more than 30%. The improving and increasing of energy saving features of VDI are also illustrated by experiment and will be integrated to Grinfy system to increase percentage of energy saved. [less ▲]

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See detailService Performance Pattern Analysis and Prediction of Commercially Available Cloud Providers
Wagle, Shyam Sharan UL; Guzek, Mateusz UL; Bouvry, Pascal UL

in Service Performance Pattern Analysis and Prediction of Commercially Available Cloud Providers (2016, December 12)

The knowledge of service performance of cloud providers is essential for cloud service users to choose the cloud services that meet their requirements. Instantaneous performance readings are accessible ... [more ▼]

The knowledge of service performance of cloud providers is essential for cloud service users to choose the cloud services that meet their requirements. Instantaneous performance readings are accessible, but prolonged observations provide more reliable information. However, due to technical complexities and costs of monitoring services, it may not be possible to access the service performance of cloud provider for longer time durations. The extended observation periods are also a necessity for prediction of future behavior of services. These predictions have very high value for decision making both for private and corporate cloud users, as the uncertainty about the future performance of purchased cloud services is an important risk factor. Predictions can be used by specialized entities, such as cloud service brokers (CSBs) to optimally recommend cloud services to the cloud users. In this paper, we address the challenge of prediction. To achieve this, the current service performance patterns of cloud providers are analyzed and future performance of cloud providers are predicted using to the observed service performance data. It is done using two automatic predicting approaches: ARIMA and ETS. Error measures of entire service performance prediction of cloud providers are evaluated against the actual performance of the cloud providers computed over a period of one month. Results obtained in the performance prediction show that the methodology is applicable for both short- term and long-term performance prediction. [less ▲]

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