MineCap: super incremental learning for detecting and blocking cryptocurrency mining on software-defined networking

Annals of Telecommunications - Covert mining of cryptocurrency implies the use of valuable computing resources and high energy consumption. In this paper, we propose MineCap, a dynamic online...     

PEMPIs: A New Methodology for Modeling and Prediction of MPI Programs Performance

The evaluation and prediction of parallel programs performance are becoming more and more important, so that they require appropriate techniques to identify the factors which influence the application execution time and also the way they interact. In this paper, we present some contributions of our research in this area by describing PEMPIs, a new methodology applied to the performance analysis and prediction of MPI programs. A new task graph helps us both to understand details of the application and to increase the accuracy of the prediction models. The proposed techniques are detailed and tested through the modeling of a complete application. PEMPIs efficiency has been proved by the results of this application modeling—most tests executed in a cluster of computers showed errors up to 10.     

Grammar-based immune programming

This paper describes Grammar-based Immune Programming (GIP) for evolving programs in an arbitrary language by immunological inspiration. GIP is based on Grammatical Evolution (GE) in which a grammar is used to define a language and decode candidate solutions to a valid representation (program). However, by default, GE uses a Genetic Algorithm in the search process while GIP uses an artificial immune system. Some modifications are needed of an immune algorithm to use a grammar in order to efficiently decode antibodies into programs. Experiments are performed to analyze algorithm behavior over different aspects and compare it with GEVA, a well known GE implementation. The methods are applied to identify a causal model (an ordinary differential equation) from an observed data set, to symbolically regress an iterated function f(f(x)) = g(x), and to find a symbolic representation of a discontinuous function.     

A Hierarchical Segmentation of Articulated Bodies

This paper presents a novel segmentation method to assist the rigging of articulated bodies. The method computes a coarse‐to‐fine hierarchy of segments ordered by the level of detail. The results are invariant to deformations, and numerically robust to noise, irregular tessellations, and topological short‐circuits. The segmentation is based on two key ideas. First, it exploits the multiscale properties of the diffusion distance on surfaces, and then it introduces a new definition of medial structures, composing a bijection between medial structures and segments. Our method computes this bijection through a simple and fast iterative approach, and applies it to triangulated meshes.     

Restoration in wavelength-routed optical networks by means of ant colony optimization

Because of the distributed control of the network, the dynamic nature of the traffic and the unpredictability of a failure event, the flexibility and robustness of ant colony optimization (ACO) make it a suitable candidate for provisioning lightpaths in an optical network. In this work, we propose a fault-tolerant dynamic routing and wavelength assignment (RWA) algorithm based on the ACO framework, presenting its integration into the Generalized multi-protocol label switching (GMPLS) control plane. By simulating two different scenarios, we demonstrate the effectiveness of this algorithm when a single link or node failure occurs.

A number-theoretic framework for the mitigation of fragmentation loss in elastic optical links

This paper addresses the problem of minimizing total slot idle time in assigning spectrum to a 2-class traffic, considering both incremental and dynamic arrival and permanence rules. Deadlock avoidance under incremental traffic is first shown to be possible with the use of non-greedy spectrum assignment policies in some link states which are identified from knowledge of the connection request sizes, thus keeping total idleness finite and minimal. Then, the concept of deadlock avoidance is extended to dynamic traffic with the purpose of proposing an algorithm that mitigates fragmentation losses with appropriate greedy traffic-aware assignment policies. Since deadlock is not permanent under dynamic traffic, avoidance by assignment denial is not used. Instead, the proposed algorithm is only reluctant to assign dysfunctional, deadlock-prone voids in favour of functional voids if they are available. Other priorities may also apply if multiple searches are allowed.

     

Multidimensional Projections for Visual Analysis of Social Networks

Visual analysis of social networks is usually based on graph drawing algorithms and tools.However,social networks are a special kind of graph in the sense that interpretation of displayed relationships is heavily dependent on context.Context,in its turn,is given by attributes associated with graph elements,such as individual nodes,edges,and groups of edges,as well as by the nature of the connections between individuals.In most systems,attributes of individuals and communities are not taken into consideration during graph layout,except to derive weights for force-based placement strategies.This paper proposes a set of novel tools for displaying and exploring social networks based on attribute and connectivity mappings.These properties are employed to layout nodes on the plane via multidimensional projection techniques.For the attribute mapping,we show that node proximity in the layout corresponds to similarity in attribute,leading to easiness in locating similar groups of nodes.The projection based on connectivity yields an initial placement that forgoes force-based or graph analysis algorithm,reaching a meaningful layout in one pass.When a force algorithm is then applied to this initial mapping,the final layout presents better properties than conventional force-based approaches.Numerical evaluations show a number of advantages of pre-mapping points via projections.User evaluation demonstrates that these tools promote ease of manipulation as well as fast identification of concepts and associations which cannot be easily expressed by conventional graph visualization alone.In order to allow better space usage for complex networks,a graph mapping on the surface of a sphere is also implemented.     

钢框架结构优化设计的多集约束和自动构件分组

对于结构优化问题,如钢框架结构的用钢量最小化,设计尺寸取决于构件横截面面积。构件横截面面积可从一些可行性表格中查得,如美国钢结构协会(AISC)提供的表格。构件的横截面尺寸bf,tf,d和tw(可为分散的或连续的)能独立确定。讨论关于设计尺寸变量的框架结构优化问题,提出一种获得理想构件分组法则。此法则考虑了制作、检查、装配和焊接的优势,而这些因素在传统预算里并没有被考虑。运用先前提出的适应性损失法,增强结构优化中的机械约束。     

Combination of local feature detection methods for digital video stabilization

Technological advances in compact and portable cameras have enabled the generation of large volumes of video sequences. However, videos captured by amateurs are subject to unwanted vibrations due to camera shaking. To overcome such problem, video stabilization aims to remove undesired motion from videos to enhance visual quality, improving applications such as detection and tracking of objects. In this work, we develop and analyze a consensual method for combining a set of local feature techniques for camera motion estimation. Several video sequences are used to evaluate the proposed methodology. Experimental results demonstrate the effectiveness of the combination method over individual local feature approaches.