A SOCIOLOGICAL PERSPECTIVE ON THE REORDERING PROBLEM IN MULTIPATH ROUTING

The term multipath routing means using multiple paths concurrently to transport data over network. The main problem of this routing scheme is the difference among the delays of selected paths, which causes reordering of a single flow's packets. In this paper, this problem is analyzed through a sociological perspective. We show that reordering problem is not inherently related to multipath routing, rather caused by the dominant capitalist view of the problem. then, the problem is addressed through a Marxism perspective. We theoretically prove that by this perspective, there exists a routing scheme that minimizes latency and also the requirement of buffering at receiver.     

A Critical Study of the Compressible Lattice Boltzmann Methods for Riemann Problem

In this paper, the discrete velocity model proposed by Kataoka and Tsutahara (Phys. Rev. E 69(5):056702, 2004) for simulating inviscid flows is employed. Three approaches for improving the stability and the accuracy of this model, especially for high Mach numbers, are suggested and implemented in this research. First, the TVD scheme (Harten in J. Comput. Phys. 49:357?C393, 1983) is used for space discretization of the convective term in the Lattice Boltzmann equation. Next, the modified Lax-Wendroff with artificial viscosity is employed to increase the robustness of the method in supersonic flows. Finally, a combination of TVD and the 2nd order derivative of the distribution function is employed using a differentiable switch. It is found that the recent technique is a more suitable approach for a wide range of Mach numbers. Moreover, the WENO scheme for space discretization has been applied and compared with these newly applied methods.     

Negotiation strategies considering market, time and behavior functions for resource allocation in computational grid

Providing an efficient resource allocation mechanism is a challenge to computational grid due to large-scale resource sharing and the fact that Grid Resource Owners (GROs) and Grid Resource Consumers (GRCs) may have different goals, policies, and preferences. In a real world market, various economic models exist for setting the price of grid resources, based on supply-and-demand and their value to the consumers. In this paper, we discuss the use of multiagent-based negotiation model for interaction between GROs and GRCs. For realizing this approach, we designed the Market- and Behavior-driven Negotiation Agents (MBDNAs). Negotiation strategies that adopt MBDNAs take into account the following factors: Competition, Opportunity, Deadline and Negotiator’s Trading Partner’s Previous Concession Behavior. In our experiments, we compare MBDNAs with MDAs (Market-Driven Agent), NDF (Negotiation Decision Function) and Kasbah in terms of the following metrics: total tasks complementation and budget spent. The results show that by taking the proposed negotiation model into account, MBDNAs outperform MDAs, NDF and Kasbah.     

Robust stochastic moment control via genetic-pole placement in communication network parameter setting

In this paper, the problems of stochastic robust approximate covariance assignment and robust covariance feedback stabilization, which are applied to variable parameters of additive increase/multiplicative decrease (AIMD) networks, are considered. The main idea of the developed algorithm is to use the parameter settings of an AIMD network congestion control scheme, where parameters may assign the desired network’s window covariance, with respect to the current network conditions. The aim is to search for the optimal AIMD parameters of a feedback gain matrix such that the objective functions defined via appropriate robustness measures and covariance assignment constraints can be optimized using an adaptive genetic algorithm (AGA). It is shown that the results can be used to develop tools for analyzing the behavior of AIMD communication networks. Quality of service (QoS) and other performance measures of the network have been improved by using the proposed congestion control. The accuracy of the controller is demonstrated by using MATLAB and NS software programs.     

Cluster center initialization algorithm for K-modes clustering

Partitional clustering of categorical data is normally performed by using K-modes clustering algorithm, which works well for large datasets. Even though the design and implementation of K-modes algorithm is simple and efficient, it has the pitfall of randomly choosing the initial cluster centers for invoking every new execution that may lead to non-repeatable clustering results. This paper addresses the randomized center initialization problem of K-modes algorithm by proposing a cluster center initialization algorithm. The proposed algorithm performs multiple clustering of the data based on attribute values in different attributes and yields deterministic modes that are to be used as initial cluster centers. In the paper, we propose a new method for selecting the most relevant attributes, namely Prominent attributes, compare it with another existing method to find Significant attributes for unsupervised learning, and perform multiple clustering of data to find initial cluster centers. The proposed algorithm ensures fixed initial cluster centers and thus repeatable clustering results. The worst-case time complexity of the proposed algorithm is log-linear to the number of data objects. We evaluate the proposed algorithm on several categorical datasets and compared it against random initialization and two other initialization methods, and show that the proposed method performs better in terms of accuracy and time complexity. The initial cluster centers computed by the proposed approach are close to the actual cluster centers of the different data we tested, which leads to faster convergence of K-modes clustering algorithm in conjunction to better clustering results.     

Structural controllability of multi-agent networks: Robustness against simultaneous failures

In this paper, structural controllability of a leader–follower multi-agent system with multiple leaders is studied from a graph-theoretic point of view. The problem of preservation of structural controllability under simultaneous failures in both the communication links and the agents is investigated. The effects of the loss of agents and communication links on the controllability of an information flow graph are previously studied. In this work, the corresponding results are exploited to introduce some useful indices and importance measures that help characterize and quantify the role of individual links and agents in the controllability of the overall network. Existing results are then extended by considering the effects of losses in both links and agents at the same time. To this end, the concepts of joint (r,s)$(r,s)$-controllability and joint t$t$-controllability are introduced as quantitative measures of reliability for a multi-agent system, and their important properties are investigated. Lastly, the class of jointly critical digraphs is introduced, and it is stated that if a digraph is jointly critical, then joint t$t$-controllability is a necessary and sufficient condition for remaining controllable following the failure of any set of links and agents, with cardinality less than t$t$. Various examples are exploited throughout the paper to elaborate on the analytical findings.     

A survey of shaped-based registration and segmentation techniques for cardiac images

Heart disease is the leading cause of death in the modern world. Cardiac imaging is routinely applied for assessment and diagnosis of cardiac diseases. Computerized image analysis methods are now widely applied to cardiac segmentation and registration in order to extract the anatomy and contractile function of the heart. The vast number of recent papers on this topic point to the need for an up to date survey in order to summarize and classify the published literature. This paper presents a survey of shape modeling applications to cardiac image analysis from MRI, CT, echocardiography, PET, and SPECT and aims to (1) introduce new methodologies in this field, (2) classify major contributions in image-based cardiac modeling, (3) provide a tutorial to beginners to initiate their own studies, and (4) introduce the major challenges of registration and segmentation and provide practical examples. The techniques surveyed include statistical models, deformable models/level sets, biophysical models, and non-rigid registration using basis functions. About 130 journal articles are categorized based on methodology, output, imaging system, modality, and validations. The advantages and disadvantages of the registration and validation techniques are discussed as appropriate in each section.     

Improved Incompressible Smoothed Particle Hydrodynamics method for simulating flow around bluff bodies

In this article, we present numerical solutions for flow over an airfoil and a square obstacle using Incompressible Smoothed Particle Hydrodynamics (ISPH) method with an improved solid boundary treatment approach, referred to as the Multiple Boundary Tangents (MBT) method. It was shown that the MBT boundary treatment technique is very effective for tackling boundaries of complex shapes. Also, we have proposed the usage of the repulsive component of the Lennard-Jones Potential (LJP) in the advection equation to repair particle fractures occurring in the SPH method due to the tendency of SPH particles to follow the stream line trajectory. This approach is named as the artificial particle displacement method. Numerical results suggest that the improved ISPH method which is consisting of the MBT method, artificial particle displacement and the corrective SPH discretization scheme enables one to obtain very stable and robust SPH simulations. The square obstacle and NACA airfoil geometry with the angle of attacks between 0° and 15° were simulated in a laminar flow field with relatively high Reynolds numbers. We illustrated that the improved ISPH method is able to capture the complex physics of bluff-body flows naturally such as the flow separation, wake formation at the trailing edge, and the vortex shedding. The SPH results are validated with a mesh-dependent Finite Element Method (FEM) and excellent agreements among the results were observed.