DiffServ Aware MPLS Traffic Engineering for ISP Networks: State of the Art and New Trends, Journal of Telecommunications and Information Technology, 2009, nr 1

In the recent ten years, with the development of new applications through Internet such as multimedia or networked control applications, users need more and more quality of service (QoS). However, the requested QoS is not the same depending on the application. Most of the new models to manage internet traffic are based on specific QoS criteria which should be optimized. This paper presents main multiprotocol label switching (MPLS) approaches such as MPLS adaptive traffic engineering (MATE), load distribution in MPLS (LDM) and load balancing over widest disjoints paths (LBWDP) that are new models for traffic engineering. It also introduces periodic multi-step (PEMS) algorithm that adapts the offered quality depending on the class of the routed traffic

Formal Specification, Implementation, and Evaluation of the AdoBPRIM Approach

Modeling is one of the fundamental aspects of Risk-aware Business Process Management. The conceptualization of new modeling approaches needs to integrate all abstraction layers of risk and business process concepts and requires a highly specialized knowledge in conceptual modeling foundations and formal specification of meta-models. This paper introduces a risk-aware business process modeling approach based on the BPRIM method. In order to comprehensively and unambiguously specify the proposed approach, we revert to the FDMM formalism. Furthermore, a corresponding software prototype called AdoBPRIM has been implemented using the ADOxx meta-modeling platform to assess the technical feasibility of the approach. The usability of the tool has been empirically evaluated and a healthcare process-based example is presented as a proof-of-concept. We show that the AdoBPRIM approach enables Risk-aware Business Process Management with an excellent usability. In summary, this paper constitutes a best-practice for formally specifying, technically implementing, and empirically evaluating modeling method conceptualizations

DiffServ aware MPLS Traffic Engineering for ISP networks: State of Art and New Trends

International audienceIn the recent ten years, with the development of new applications through Internet such as multimedia or net-worked control applications, users need more and more qual-ity of service (QoS). However, the requested QoS is not the same depending on the application. Most of the new mod-els to manage internet traffic are based on specific QoS cri-teria which should be optimized. This paper presents main multiprotocol label switching (MPLS) approaches such as MPLS adaptive traffic engineering (MATE), load distribu-tion in MPLS (LDM) and load balancing over widest disjoints paths (LBWDP) that are new models for traffic engineering. It also introduces periodic multi-step (PEMS) algorithm that adapts the offered quality depending on the class of the routed traffic. Keywords-- differentiated service, multipath routing, QoS rout-ing, quality of service, traffic engineering

Binary Political Optimizer for Feature Selection Using Gene Expression Data

DNA Microarray technology is an emergent field, which offers the possibility of obtaining simultaneous estimates of the expression levels of several thousand genes in an organism in a single experiment. One of the most significant challenges in this research field is to select high relevant genes from gene expression data. To address this problem, feature selection is a well-known technique to eliminate unnecessary genes in order to ensure accurate classification results. This paper proposes a binary version of Political Optimizer (PO) to solve feature selection problem using gene expression data. Two transfer functions are used to design a binary PO. The first one is based on Sigmoid function and will be noted as BPO-S, while the second one is based on V-shaped function and will be noted as BPO-V. The proposed methods are evaluated using 9 biological datasets and compared with 8 binary well-known metaheuristics. The comparative results show the prevalent performance of the BPO methods especially BPO-V in comparison with other techniques

DiffServ aware MPLS Traffic Engineering for ISP networks: State of Art and New Trends

International audienceIn the recent ten years, with the development of new applications through Internet such as multimedia or net-worked control applications, users need more and more qual-ity of service (QoS). However, the requested QoS is not the same depending on the application. Most of the new mod-els to manage internet traffic are based on specific QoS cri-teria which should be optimized. This paper presents main multiprotocol label switching (MPLS) approaches such as MPLS adaptive traffic engineering (MATE), load distribu-tion in MPLS (LDM) and load balancing over widest disjoints paths (LBWDP) that are new models for traffic engineering. It also introduces periodic multi-step (PEMS) algorithm that adapts the offered quality depending on the class of the routed traffic. Keywords-- differentiated service, multipath routing, QoS rout-ing, quality of service, traffic engineering

On the use of text augmentation for stance and fake news detection

ABSTRACTData Augmentation (DA) aims at synthesizing new training instances by applying transformations to available ones. DA has several well-known benefits such as: (i) increasing generalization ability; (ii) preventing data scarcity; and (iii) helping resolve class imbalance issues. In this work, we investigate the use of DA for stance and fake news detection. In the first part of our work, we explore the effect of various DA techniques on the performance of common classification algorithms. Our study reveals that the motto ‘the more, the better’ is the wrong approach regarding text augmentation and that there is no one-size-fits-all text augmentation technique. The second part of our work leverages the results of our study to propose a novel augmentation-based, ensemble learning approach. The proposed approach leverages text augmentation to enhance base learners' diversity and accuracy, ergo the predictive performance of the ensemble. The third part of our work experimentally investigates the use of DA to cope with the class imbalance problem. Class imbalance is very common in stance and fake news detection and often results in biased models. In this work we show how and to what extent text augmentation can help resolving moderate and severe imbalance

Double Chaining Approach for Indirect Monitoring of FMS under Cyclic Scheduling

International audienceThe occurrence of failure in Flexible Manufacturing System can deeply modify its performances and its availability. In this context, the monitoring of FMS becomes an important issue, improving production time and minimizing unplanned costly breakdowns. We propose to develop an indirect monitoring by the analysis of product flows at the output of an FMS subjected to a 1-cyclic control. In order to determine the operating system failure that causes the decrease of process performance and the delay observed at the output of a system part, we propose a resolution mechanism based on fault tree analysis

On-line fault diagnosis of FMS based on flows analysis

International audienc