Michel Toulouse | Vietnamese-German University (original) (raw)

Papers by Michel Toulouse

Ars Combinatoria, 2006

A visual instruction system for the building and reworking of printed circuit boards. By superimp... more A visual instruction system for the building and reworking of printed circuit boards. By superimposing a printed circuit board and a one-to-one transparency illustrating component placement, cuts, jumpers, wiring information etc., the worker is constantly apprised of the work completed, and the work remaining to be done. The method is not compatible with more highly sophisticated and expensive production assembly systems, but is intended as a prototype tool for short runs.

Information Processing Letters, Feb 1, 2006

The maximum leaf spanning tree problem is known to be NP-complete. In [M.S. Rahman, M. Kaykobad, ... more The maximum leaf spanning tree problem is known to be NP-complete. In [M.S. Rahman, M. Kaykobad, Complexities of some interesting problems on spanning trees, Inform. Process. Lett. 94 (2005) 93–97], a variation on this problem was posed. This variation restricts the problem to bipartite graphs and asks, for a fixed integer K, whether or not the graph contains a spanning

International Conference on Computer Aided Design, Mar 12, 2001

In this paper, we present an adaptation for hypergraph partitioning of the multilevel cooperative... more In this paper, we present an adaptation for hypergraph partitioning of the multilevel cooperative search paradigm first introduce by Toulouse, Thulasiraman, and Glover [15]. We also introduce a new approach for coarsening hypergraphs, and describe a parallel implementation of this algorithm on the SGI O200 system. Experiments on ISPD98 benchmark suite of circuits show, for 4-way and 8-way partitioning, a reduction of 3% to 15% on hyperedge-cut compared to hMETIS. Bisections of hypergraphs based on our algorithm also outperforms hMETIS, although more modestly.

Lecture Notes in Computer Science, 2021

Public blockchains are decentralized networks where each participating node executes the same dec... more Public blockchains are decentralized networks where each participating node executes the same decision-making process. This form of decentralization does not scale well because the same data are stored on each network node, and because all nodes must validate each transaction prior to their confirmation. One solution approach decomposes the nodes of a blockchain network into subsets called "shards", each shard processing and storing disjoint sets of transactions in parallel. To fully benefit from the parallelism of sharded blockchains, the processing load of shards must be evenly distributed. However, the problem of computing balanced workloads is theoretically hard and further complicated in practice as transaction processing times are unknown prior to be assigned to shards. In this paper we introduce a dynamic workload-balancing algorithm where the allocation strategy of transactions to shards is periodically adapted based on the recent workload history of shards. Our algorithm is an adaptation to sharded blockchains of a consensus-based load-balancing algorithm. It is a fully distributed algorithm inline with network based applications such as blockchains. Some preliminary results are reported based on simulations that shard transactions of three well-known blockchain platforms.

This work concerns distributed consensus algorithms and application to a network intrusion detect... more This work concerns distributed consensus algorithms and application to a network intrusion detection system (NIDS) [21]. We consider the problem of defending the system against multiple data falsification attacks (Byzantine attacks), a vulnerability of distributed peer-to-peer consensus algorithms that has not been widely addressed in its practicality. We consider both naive (independent) and colluding attackers. We test three defense strategy implementations, two classified as outlier detection methods and one reputation-based method. We have narrowed our attention to outlier and reputation-based methods because they are relatively light computationally speaking. We have left out control theoretic methods which are likely the most effective methods, however their computational cost increase rapidly with the number of attackers. We compare the efficiency of these three implementations for their computational cost, detection performance, convergence behavior and possible impacts on the intrusion detection accuracy of the NIDS. Tests are performed based on simulations of distributed denial of service attacks using the KSL-KDD data set.

Network intrusion detection is the process of identifying malicious behaviors that target a netwo... more Network intrusion detection is the process of identifying malicious behaviors that target a network and its resources. Current systems implementing intrusion detection processes observe traffic at several data collecting points in the network but analysis is often centralized or partly centralized. These systems are not scalable and suffer from the single point of failure, i.e. attackers only need to target the central node to compromise the whole system. This paper proposes an anomaly-based fully distributed network intrusion detection system where analysis is run at each data collecting point using a naïve Bayes classifier. Probability values computed by each classifier are shared among nodes using an iterative average consensus protocol. The final analysis is performed redundantly and in parallel at the level of each data collecting point, thus avoiding the single point of failure issue. We run simulations focusing on DDoS attacks with several network configurations, comparing the accuracy of our fully distributed system with a hierarchical one. We also analyze communication costs and convergence speed during consensus phases.

International series in management science/operations research, 2010

Kluwer Academic Publishers eBooks, Feb 2, 2006

We present a state-of-the-art survey of parallel meta-heuristic developments and results, discuss... more We present a state-of-the-art survey of parallel meta-heuristic developments and results, discuss general design and implementation principles that apply to most meta-heuristic classes, instantiate these principles for the three meta-heuristic classes currently most extensively used—genetic methods, simulated annealing, and tabu search, and identify a number of trends and promising research directions.

The International Conference on Advanced COMPuting and Applications (ACOMP) is an annual, multitr... more The International Conference on Advanced COMPuting and Applications (ACOMP) is an annual, multitrack international forum for academics, engineers, practitioners and research students to exchange their ideas, techniques, methods, and state-of-the-art applications for advanced computing. Initially formed as a scientific venue for high-performance computing & advanced applications, the conference kept expanding and had a pedigree of attracting international and Vietnamese participants who both are interested in advanced topics of computer science & engineering. The first occurrence of ACOMP was dated back to as early as 2007.

Informatica (lithuanian Academy of Sciences), Jun 6, 2017

The purpose of a Network Intrusion Detection System (NIDS) is to monitor network traffic such to ... more The purpose of a Network Intrusion Detection System (NIDS) is to monitor network traffic such to detect malicious usages of network facilities. NIDSs can also be part of the affected network facilities and be the subject of attacks aiming at degrading their detection capabilities. The present paper investigates such vulnerabilities in a recent consensus-based NIDS proposal [1]. This system uses an average consensus algorithm to share information among the NIDS modules and to develop coordinated responses to network intrusions. It is known however that consensus algorithms are not resilient to compromised nodes sharing falsified information, i.e. they can be the target of Byzantine attacks. Our work proposes two different strategies aiming at identifying compromised NIDS modules sharing falsified information. Also, a simple approach is proposed to isolate compromised modules, returning the NIDS into a non-compromised state. Validations of the defense strategies are provided through several simulations of Distributed Denial of Service attacks using the NSL-KDD data set. The efficiency of the proposed methods at identifying compromised NIDS nodes and maintaining the accuracy of the NIDS is compared. The computational cost for protecting the consensus-based NIDS against Byzantine attacks is evaluated. Finally we analyze the behavior of the consensus-based NIDS once a compromised module has been isolated. Povzetek: Sistemi za odkrivanje napadov v omrežjih temeljijo na pojavih nenavadnega prometa, vendar so občutljivi na napade. Prispevek opisuje obrambo pred bizantinskimi napadi.

On-the-fly establishment of multihop wireless access networks (OEMAN) is a new wireless communica... more On-the-fly establishment of multihop wireless access networks (OEMAN) is a new wireless communication approach to quickly establish temporary Internet connectivity in a disaster region. OEMAN creates virtual access points on mobile devices of disaster victims to reach still-alive access points of the Internet so that rescuers can be informed about their status and position. The simple routing strategy in OEMAN is based on a tree like topology raising some traffic load balancing issues at nodes closed to the root. In this paper, we propose a linear program for overload-aware routing. Moreover, we consider wireless interference and integrate it into our routing optimization model. Our evaluations implemented in Matlab show that the overload-aware routing improves load balancing among available virtual access points in OEMAN. By avoiding nodes with heavy load in the network, our solution improves network throughput compared to overload-unaware routing.

Due to the expected scale of the Grid computing systems, we need to develop highly distributed an... more Due to the expected scale of the Grid computing systems, we need to develop highly distributed and extensible resource allocation frameworks for such systems. Microeconomic principles such as auctioning and commodity market are two approaches that are being pursued by several researchers for the Grid resource allocation problem. In this paper, we use a commodity market based approach to allocate resources, where resources are classified into different classes based on the hardware components, network connectivity, and operating system. In commodity market, the prices of the commodities ("resources") are fixed using individual supply and demand functions. In this paper we have developed an algorithm to determine the price of the resource. The simulation results show the performance of the pricing algorithm used in the commodity market.

Transportation Science, Nov 1, 2016

We first present a new service network design model for freight consolidation carriers, one that ... more We first present a new service network design model for freight consolidation carriers, one that both routes commodities and the resources needed to transport them while explicitly recognizing that there are limits on how many resources are available at each terminal. We next present a solution approach that combines column generation, meta-heuristic, and exact optimization techniques to produce high-quality solutions. We demonstrate the efficacy of the approach with an extensive computational study and benchmark its performance against a leading commercial solver.

SN computer science, Jul 1, 2020

Distributed function computation has a wide spectrum of major applications in distributed systems... more Distributed function computation has a wide spectrum of major applications in distributed systems. Distributed computation over a network-system proceeds in a sequence of time-steps in which vertices update and/or exchange their values based on the underlying algorithm constrained by the time-(in)variant network-topology. Distributed computing network-systems are modeled as directed/undirected graphs with vertices representing compute elements and adjacency-edges capturing their uni-or bi-directional communication. To quantify an intuitive tradeoff between two graph-parameters: minimum vertexdegree and diameter of the underlying graph, we formulate an extremal problem with the two parameters: for all positive integers n and d, the extremal value ∇(n, d) denotes the least minimum vertex-degree among all connected order-n graphs with diameters of at most d. We prove matching upper and lower bounds on the extremal values of ∇(n, d) for various combinations of n-and d-values.

Genetic Programming and Evolvable Machines, Mar 1, 2006

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Lecture Notes in Computer Science, 2019

Parallel and distributed computing network-systems are modeled as graphs with vertices representi... more Parallel and distributed computing network-systems are modeled as graphs with vertices representing compute elements and adjacency-edges capturing their uni- or bi-directional communication. Distributed function computation covers a wide spectrum of major applications, such as quantized consensus and collaborative hypothesis testing, in distributed systems. Distributed computation over a network-system proceeds in a sequence of time-steps in which vertices update and/or exchange their values based on the underlying algorithm constrained by the time-(in)variant network-topology. For finite convergence of distributed information dissemination and function computation in the model, we study lower bounds on the number of time-steps for vertices to receive (initial) vertex-values of all vertices regardless of underlying protocol or algorithmics in time-invariant networks via the notion of vertex-eccentricity in a graph-theoretic framework. We prove a lower bound on the maximum vertex-eccentricity in terms of graph-order and -size in a strongly connected directed graph, and demonstrate its optimality via an explicitly constructed family of strongly connected directed graphs.

ABSTRACT We propose a tabu search heuristic for the location/allocation problem with balancing re... more ABSTRACT We propose a tabu search heuristic for the location/allocation problem with balancing requirements. This problem typically arises in the context of the medium term management of a fleet of containers of multiple types, where container depots have to be selected, the assignment of customers to depots has to be established for each type of container, and the interdepot container traffic has to be planned to account for differences in supplies and demands in various zones of the geographical territory served by a container shipping company. It is modeled as a mixed integer program, which combines zero-one location variables and a multicommodity network flow structure. Extensive computational results on a set of benchmark problems and comparisons with an efficient dual ascent procedure are reported. These show that tabu search is a competitive approach for this class of problems.