Tuning compilations by multi-objective optimization: Application to Apache web server

Modern compilers present a great and ever increasing number of options which can modify the features and behavior of a compiled program. Many of these options are often wasted due to the required comprehensive knowledge about both the underlying architecture and the internal processes of the compiler. In this context, it is usual, not having a single design goal but a more complex set of objectives. In addition, the dependencies between different goals are difficult to be a priori inferred. This paper proposes a strategy for tuning the compilation of any given application. This is accomplished by using an automatic variation of the compilation options by means of multi-objective optimization and evolutionary computation commanded by the NSGA-II algorithm. This allows finding compilation options that simultaneously optimize different objectives. The advantages of our proposal are illustrated by means of a case study based on the well-known Apache web server. Our strategy has demonstrated an ability to find improvements up to 7.5% and up to 27% in context switches and L2 cache misses, respectively, and also discovers the most important bottlenecks involved in the application performance.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

Robust solutions to multi-objective linear programs with uncertain data

In this paper we examine multi-objective linear programming problems in the face of data uncertainty both in the objective function and the constraints. First, we derive a formula for the radius of robust feasibility guaranteeing constraint feasibility for all possible scenarios within a specified uncertainty set under affine data parametrization. We then present numerically tractable optimality conditions for minmax robust weakly efficient solutions, i.e., the weakly efficient solutions of the robust counterpart. We also consider highly robust weakly efficient solutions, i.e., robust feasible solutions which are weakly efficient for any possible instance of the objective matrix within a specified uncertainty set, providing lower bounds for the radius of highly robust efficiency guaranteeing the existence of this type of solutions under affine and rank-1 objective data uncertainty. Finally, we provide numerically tractable optimality conditions for highly robust weakly efficient solutions.

Trouble du spectre de l’autisme : Une agentivité morale objective, rigoriste et émotionnelle

Article

Trudny "Sojusznik" Bialorus w polityce Rosji. Prace OSW 2008. = Difficult "ally." Belarus in Russia's foreign policy. OSW Study 28/2008

Belarus holds a special position in Russian policy due to its geopolitical, military and transit significance. Russia's influence and position in the entire Eastern European region largely depend on how strong Russian influence in Belarus is. The process of Russian-Belarusian integration began in 1994, when Alyaksandr Lukashenka came to power in Minsk. At the time, Russia's policy towards Belarus was based on twomain assumptions. Firstly, the Kremlin supported Lukashenka's authoritarian regime. This allowed Russia to keep Belarus within its orbit of political influence and prevent other states from getting involved, since an undemocratic Belarus could not count on closer contacts with the West. Secondly, Russia heavily subsidised Belarus with cheap energy resources (way below the market price) and allowed the duty-free access of Belarusian goods to its market. Thus Belarus became a kind of 'sponsored authoritarianism' with a specific economic model, owing its existence to Russia's economic and political support. At the same time, Moscow's key objective in its policy towards Belarus was to make Minsk accept the Russian conditions concerning integration, which would in fact lead to Belarus' incorporation by the Russian Federation. However, Belarus managed to maintain its sovereignty, while Alyaksandr Lukashenka bandied the term 'integration' about in order to maintain the preferential model of his state's relations with Russia. Russia's intention to alter the nature of these bilateral relations became evident when Vladimir Putin took power in 2000. However, Moscow faced Minsk's refusal to accept the Russian integration plan (which, among other measures, provided for the takeover of Belarusian economic assets by Russian companies). This forced Russia to use its main tool against Minsk: the supplies of cheap gas and oil that had been sustaining Belarus' archaic economy. The most serious crisis in Russian-Belarusian relations broke out at the beginning of 2007, following Moscow's decision to raise the energy resource prices. This decision marked the beginning of the application of market principles to settlements between Moscow and Minsk. The key question this study is meant to answer concerns the consequences of the aforementioned decision by Russia for future Russian-Belarusian relations. Are they at a turning point? What are Russia's policy objectives? What results can come from the process of moving mutual relations onto an economic footing? What policy will replace Russia's 'sponsoring of Belarusian authoritarianism', which it has been implementing since 1994? Finally, what further measures will Russia undertake towards Belarus? The current study consists of five chapters. The first chapter offers a brief presentation of Belarus' significance and position in Russian policy. The second analyses the development of Russian-Belarusian political relations, first of all the establishment of the Union State, Belarus' position in Russian domestic policy and Russia's influence on Belarusian policy. The third chapter presents bilateral economic relations, primarily energy issues. The fourth chapter describes the state and perspectives of military cooperation between the two states. The fifth chapter presents conclusions, where the author attempts to define the essence of the ongoing re-evaluation in Russian-Belarusian relations and to project their future model.