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   Online Bi-Objective Scheduling for IaaS Clouds Ensuring Quality of Service; ; Bouvry, Pascal  in Simulation (2016), 92 In this paper, we propose a distributed algorithm based on a generalization of the Cellular Automata concept called Graph Cellular Automata (GCA) to solve the Maximum Lifetime Coverage Problem (MLCP) in ... [more ▼] In this paper, we propose a distributed algorithm based on a generalization of the Cellular Automata concept called Graph Cellular Automata (GCA) to solve the Maximum Lifetime Coverage Problem (MLCP) in wireless sensor networks (WSNs). In GCA, we adapt life-like state transition functions inspired by Conway’s Game of Life in order to solve the problem. The goal of this paper is to study the quality of state transition functions for an objective provided by the MLCP in WSNs. The proposed algorithm possesses all the advantages of a localized algorithm, i.e., using only some knowledge about neighbors, a WSN is able to self-organize in such a way as to prolong its lifetime, at the same time preserving the required coverage ratio of the target field. Our experimental results show that certain rules are better solvers of the given problem than others. The paper also presents the results of an experimental study of the proposed algorithm and comparison with a centralized Genetic Algorithm. [less ▲] Detailed reference viewed: 75 (2 UL)NIDISC Introduction and CommitteesBouvry, Pascal ; Danoy, Grégoire ; et alin Parallel and Distributed Processing Symposium Workshop (IPDPSW), 2015 IEEE International 2015-10-27 14:21:42 +0000 2015-10-27 14:21:42 +0000 (2015) Detailed reference viewed: 147 (2 UL)Cellular Automata Approach to Maximum Lifetime Coverage Problem in Wireless Sensor Networks; ; Bouvry, Pascal in Was, Jaroslaw; Sirakoulis, Georgios; Bandini, Stefania (Eds.) Cellular Automata: 11th International Conference on Cellular Automata for Research and Industry, ACRI 2014 Krakow, Poland, September 22–25, 2014, Proceedings (2014) In this paper, we propose a novel distributed algorithm based on Graph Cellular Automata (GCA) concept to solve Maximum Lifetime Coverage Problem (MLCP) in Wireless Sensor Networks (WSNs). The proposed ... [more ▼] In this paper, we propose a novel distributed algorithm based on Graph Cellular Automata (GCA) concept to solve Maximum Lifetime Coverage Problem (MLCP) in Wireless Sensor Networks (WSNs). The proposed algorithm possesses all advantages of localized algorithm, i.e. using only some knowledge about the neighbors, WSN is able to self-organize in such a way to prolong its lifetime preserving at the same time required coverage ratio of a target field. The paper presents results of experimental study of the proposed algorithm and comparison of them with a centralized genetic algorithm. [less ▲] Detailed reference viewed: 138 (0 UL)Convergence Analysis of Evolutionary Algorithms in the Presence of Crash-Faults and CheatersMuszynski, Jakub ; Varrette, Sébastien ; Bouvry, Pascal et alin Computers and Mathematics with Applications (2012), 64(12), 3805-3819 This paper analyzes the fault-tolerance nature of Evolutionary Algorithms (EAs) when executed in a distributed environment subjected to malicious acts. More precisely, the inherent resilience of EAs ... [more ▼] This paper analyzes the fault-tolerance nature of Evolutionary Algorithms (EAs) when executed in a distributed environment subjected to malicious acts. More precisely, the inherent resilience of EAs against two types of failures is considered: (1) crash faults, typically due to resource volatility which lead to data loss and part of the computation loss; (2) cheating faults, a far more complex kind of fault that can be modeled as the alteration of output values produced by some or all tasks of the program being executed. This last type of failure is due to the presence of cheaters on the computing platform. Most often in Global Computing (GC) systems such as BOINC, cheaters are attracted by the various incentives provided to stimulate the volunteers to share their computing resources: cheaters typically seek to obtain rewards with little or no contribution to the system. In this paper, the Algorithm-Based Fault Tolerance (ABFT) aspects of EAs against the above types of faults is characterized. Whereas the inherent resilience of EAs has been previously observed in the literature, for the first time, a formal analysis of the impact of the considered faults over the executed EA including a proof of convergence is proposed in this article. By the variety of problems addressed by EAs, this study will hopefully promote their usage in the future developments around distributed computing platform such as Desktop Grids and Volunteer Computing Systems or Cloud systems where the resources cannot be fully trusted. [less ▲] Detailed reference viewed: 150 (1 UL)Multiobjective Classification with moGEP: An Application in the Network Traffic DomainOstaszewski, Marek ; Bouvry, Pascal ; in GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009) The paper proposes a multiobjective approach to the problem of malicious network traffic classification, with specificity and sensitivity criteria as objective functions for the problem. The ... [more ▼] The paper proposes a multiobjective approach to the problem of malicious network traffic classification, with specificity and sensitivity criteria as objective functions for the problem. The multiobjective version of Gene Expression Programming (GEP) called moGEP is proposed and applied to find proper classifiers in the multiobjective search space. The purpose of the classifiers is to discriminate information about the network traffic obtained from Idiotypic Network-based Intrusion Detection System (INIDS), transformed into time series. The proposed approach is validated using the network traffic simulator ns2. Classifiers of high accuracy are obtained and their diversity offers interesting possibilities to the domain of network security. [less ▲] Detailed reference viewed: 142 (3 UL)An Approach to Intrusion Detection by Means of Idiotypic Networks ParadigmOstaszewski, Marek ; Bouvry, Pascal ; in IEEE World Congress on Computational Intelligence, WCCI 2008, Congress on Evolutionary Computation CEC 2008, Honk-Kong, June (2008) In this paper we present a novel intrusion detection architecture based on Idiotypic Network Theory (INIDS), that aims at dealing with large scale network attacks featuring variable properties, like ... [more ▼] In this paper we present a novel intrusion detection architecture based on Idiotypic Network Theory (INIDS), that aims at dealing with large scale network attacks featuring variable properties, like Denial of Service (DoS). The proposed architecture performs dynamic and adaptive clustering of the network traffic for taking fast and effective countermeasures against such high-volume attacks. INIDS is evaluated on the MITpsila99 dataset and outperforms previous approaches for DoS detection applied to this set. [less ▲] Detailed reference viewed: 139 (0 UL)Adaptive and Dynamic Intrusion Detection by Means of Idiotypic Networks ParadigmOstaszewski, Marek ; Bouvry, Pascal ; in The 21th IEEE International Parallel and Distributed Processing Symposium (IPDPS), NIDISC Workshop. (2008) In this paper we present a novel intrusion detection architecture based on Idiotypic Network Theory (INIDS), that aims at dealing with large scale network attacks featuring variable properties, like ... [more ▼] In this paper we present a novel intrusion detection architecture based on Idiotypic Network Theory (INIDS), that aims at dealing with large scale network attacks featuring variable properties, like Denial of Service (DoS). The proposed architecture performs dynamic and adaptive clustering of the network traffic for taking fast and effective countermeasures against such high-volume attacks. INIDS is evaluated on the MIT'99 dataset and outperforms previous approaches for DoS detection applied to this set. [less ▲] Detailed reference viewed: 157 (0 UL)Coevolutionary-based Mechanisms for Network Anomaly DetectionOstaszewski, Marek ; ; Bouvry, Pascal in Journal of Mathematical Modelling and Algorithms (2007), 6(3), 411-431 The paper presents an approach based on the principles of immune systems applied to the anomaly detection problem. Flexibility and efficiency of the anomaly detection system are achieved by building a ... [more ▼] The paper presents an approach based on the principles of immune systems applied to the anomaly detection problem. Flexibility and efficiency of the anomaly detection system are achieved by building a model of the network behavior based on the self-nonself space paradigm. Covering both self and nonself spaces by hyperrectangular structures is proposed. The structures corresponding to self-space are built using a training set from this space. The hyperrectangular detectors covering nonself space are created using a niching genetic algorithm. A coevolutionary algorithm is proposed to enhance this process. The results of experiments show a high quality of intrusion detection, which outperform the quality of the recently proposed approach based on a hypersphere representation of the self-space. [less ▲] Detailed reference viewed: 156 (2 UL)Evaluations of Strategies for Co-Evolutionary Genetic Algorithms: dLCGA Case StudyDanoy, Grégoire ; Bouvry, Pascal ; in ANNIE 2006: Proceedings of the 16th international conference on Artificial Neural Networks In Engineering (2006) Detailed reference viewed: 99 (6 UL)Agent-Based Optimization of Business Functions Using Coevolutionary AlgorithmsDanoy, Grégoire ; Bouvry, Pascal ; in Proceedings of the International Conference on Information and Knowledge Engineering (2004) Detailed reference viewed: 106 (3 UL) |
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