Multitriangle: A Constant Node Degree Interconnection Network

1997 ◽  
Vol 08 (02) ◽  
pp. 187-209 ◽  
Author(s):  
Jie Wu ◽  
Haifeng Qian
Keyword(s):  
Network Topology ◽  
Interconnection Network ◽  
Average Distance ◽  
Node Degree ◽  
Formal Definition ◽  
Corner Cutting ◽  
Network Topologies ◽  
Salient Features ◽  
Definition Of ◽  
Node Routing

We propose a constant node degree network topology, multitriangle, which is hierarchical, recursive, and expansive. First we introduce a corner cutting approach that generates a set of new network topologies (including multitriangles), followed by a formal definition of the multitriangle network and discussion of its properties. The salient features of this network are that it is a constant node degree network and it can be viewed as a hierarchical ring, a popular topology which has been adopted in several commercial systems. Algorithms for node-to-node routing, hierarchical ring routing, optimal ring routing, and broadcasting are presented. The multitriangle network is analyzed in terms of diameter, degree, average distance, and message density, and results are compared with other relevant networks.

MODELING THE PERFORMANCE OF COMMUNICATION SCHEMES ON NETWORK TOPOLOGIES

2008 ◽  
Vol 18 (02) ◽  
pp. 205-220
Author(s):  
JAN LEMEIRE ◽  
ERIK DIRKX ◽  
WALTER COLITTI
Keyword(s):  
Network Topology ◽  
Structure Learning ◽  
Interconnection Network ◽  
Causal Structure ◽  
Quantitative Prediction ◽  
Communication Performance ◽  
Communication Time ◽  
Communication Scheme ◽  
Network Topologies ◽  
The Impact

This paper investigates the influence of the interconnection network topology of a parallel system on the delivery time of an ensemble of messages, called the communication scheme. More specifically, we focus on the impact on the performance of structure in network topology and communication scheme. We introduce causal structure learning algorithms for the modeling of the communication time. The experimental data, from which the models are learned automatically, is retrieved from simulations. The qualitative models provide insight about which and how variables influence the communication performance. Next, a generic property is defined which characterizes the performance of individual communication schemes and network topologies. The property allows the accurate quantitative prediction of the runtime of random communication on random topologies. However, when either communication scheme or network topology exhibit regularities the prediction can become very inaccurate. The causal models can also differ qualitatively and quantitatively. Each combination of communication scheme regularity type, e.g. a one-to-all broadcast, and network topology regularity type, e.g. torus, possibly results in a different model which is based on different characteristics.

scholarly journals Star varietal cube: A New Large Scale Parallel Interconnection Network

2011 ◽  
pp. 37-44
Author(s):  
Binod Nag ◽  
Debendra Pradhan ◽  
Nirmal Keshari Swain ◽  
Nibedita Adhikari
Keyword(s):  
Network Topology ◽  
Efficient Method ◽  
Large Scale ◽  
Interconnection Network ◽  
Average Distance ◽  
Building Blocks ◽  
Star Graph ◽  
Recursive Structure ◽  
Strong Connectivity ◽  
The Hierarchical Structure

This paper proposes a new interconnection network topology, called the Star varietalcube SVC(n,m), for large scale multicomputer systems. We take advantage of the hierarchical structure of the Star graph network and the Varietal hypercube to obtain an efficient method for constructing the new topology. The Star graph of dimension n and a Varietal hypercube of dimension m are used as building blocks. The resulting network has most of the desirable properties of the Star and Varietal hypercube including recursive structure, partionability, strong connectivity. The diameter of the Star varietal hypercube is about two third of the diameter of the Star-cube. The average distance of the proposed topology is also smaller than that of the Star-cube.

scholarly journals Optimal Coordination of Over-Current Relays in Microgrids Using Unsupervised Learning Techniques

2021 ◽  
Vol 11 (3) ◽  
pp. 1241
Author(s):  
Sergio D. Saldarriaga-Zuluaga ◽  
Jesús M. López-Lezama ◽  
Nicolás Muñoz-Galeano
Keyword(s):  
Unsupervised Learning ◽  
Distributed Generation ◽  
Network Topology ◽  
International Electrotechnical Commission ◽  
Number Of Clusters ◽  
Learning Techniques ◽  
Topology Changes ◽  
Network Topologies ◽  
Optimal Coordination ◽  
Operational Modes

Microgrids constitute complex systems that integrate distributed generation (DG) and feature different operational modes. The optimal coordination of directional over-current relays (DOCRs) in microgrids is a challenging task, especially if topology changes are taken into account. This paper proposes an adaptive protection approach that takes advantage of multiple setting groups that are available in commercial DOCRs to account for network topology changes in microgrids. Because the number of possible topologies is greater than the available setting groups, unsupervised learning techniques are explored to classify network topologies into a number of clusters that is equal to the number of setting groups. Subsequently, optimal settings are calculated for every topology cluster. Every setting is saved in the DOCRs as a different setting group that would be activated when a corresponding topology takes place. Several tests are performed on a benchmark IEC (International Electrotechnical Commission) microgrid, evidencing the applicability of the proposed approach.

scholarly journals Students’ Understanding on Formal Definition of Limit

2021 ◽  
Vol 1752 (1) ◽  
pp. 012082
Author(s):  
Nurdin ◽  
S F Assagaf ◽  
F Arwadi
Keyword(s):  
Formal Definition ◽  
Definition Of

scholarly journals Optimal Multiculture Network Design for Maximizing Resilience in the Face of Multiple Correlated Failures

2019 ◽  
Vol 9 (11) ◽  
pp. 2256
Author(s):  
Yasmany Prieto ◽  
Nicolás Boettcher ◽  
Silvia Elena Restrepo ◽  
Jorge E. Pezoa
Keyword(s):  
Network Design ◽  
Optimization Problems ◽  
Current Data ◽  
Sequential Optimization ◽  
Node Degree ◽  
Network Resilience ◽  
Correlated Failures ◽  
The Face ◽  
Network Operation ◽  
Network Topologies

Current data networks are highly homogeneous because of management, economic, and interoperability reasons. This technological homogeneity introduces shared risks, where correlated failures may entirely disrupt the network operation and impair multiple nodes. In this paper, we tackle the problem of improving the resilience of homogeneous networks, which are affected by correlated node failures, through optimal multiculture network design. Correlated failures regarded here are modeled by SRNG events. We propose three sequential optimization problems for maximizing the network resilience by selecting as different node technologies, which do not share risks, and placing such nodes in a given topology. Results show that in the 75% of real-world network topologies analyzed here, our optimal multiculture design yields networks whose probability that a pair of nodes, chosen at random, are connected is 1, i.e., its ATTR metric is 1. To do so, our method efficiently trades off the network heterogeneity, the number of nodes per technology, and their clustered location in the network. In the remaining 25% of the topologies, whose average node degree was less than 2, such probability was at least 0.7867. This means that both multiculture design and topology connectivity are necessary to achieve network resilience.

Diagnosis Rule Discovery Based on Causality in the Context of Fault Diagnosis in Rotating Machinery

2014 ◽  
Vol 532 ◽  
pp. 113-117
Author(s):  
Zhou Jin ◽  
Ru Jing Wang ◽  
Jie Zhang
Keyword(s):  
Fault Diagnosis ◽  
General Framework ◽  
Complex Structure ◽  
Rotating Machinery ◽  
Massive Data ◽  
Formal Definition ◽  
Rule Discovery ◽  
Rule Based ◽  
Simple Implementation ◽  
Definition Of

The rotating machineries in a factory usually have the characteristics of complex structure and highly automated logic, which generated a large amounts of monitoring data. It is an infeasible task for uses to deal with the massive data and locate fault timely. In this paper, we explore the causality between symptom and fault in the context of fault diagnosis in rotating machinery. We introduce data mining into fault diagnosis and provide a formal definition of causal diagnosis rule based on statistic test. A general framework for diagnosis rule discovery based on causality is provided and a simple implementation is explored with the purpose of providing some enlightenment to the application of causality discovery in fault diagnosis of rotating machinery.

scholarly journals Time to Harmonize Dengue Nomenclature and Classification

Viruses ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 569 ◽  
Author(s):  
Lize Cuypers ◽  
Pieter Libin ◽  
Peter Simmonds ◽  
Ann Nowé ◽  
Jorge Muñoz-Jordán ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Dengue Virus ◽  
Classification System ◽  
Formal Definition ◽  
Classification Procedure ◽  
Genotype 2 ◽  
Global Spread ◽  
Significant Burden ◽  
Definition Of ◽  
Epidemiological Characteristics

Dengue virus (DENV) is estimated to cause 390 million infections per year worldwide. A quarter of these infections manifest clinically and are associated with a morbidity and mortality that put a significant burden on the affected regions. Reports of increased frequency, intensity, and extended geographical range of outbreaks highlight the virus’s ongoing global spread. Persistent transmission in endemic areas and the emergence in territories formerly devoid of transmission have shaped DENV’s current genetic diversity and divergence. This genetic layout is hierarchically organized in serotypes, genotypes, and sub-genotypic clades. While serotypes are well defined, the genotype nomenclature and classification system lack consistency, which complicates a broader analysis of their clinical and epidemiological characteristics. We identify five key challenges: (1) Currently, there is no formal definition of a DENV genotype; (2) Two different nomenclature systems are used in parallel, which causes significant confusion; (3) A standardized classification procedure is lacking so far; (4) No formal definition of sub-genotypic clades is in place; (5) There is no consensus on how to report antigenic diversity. Therefore, we believe that the time is right to re-evaluate DENV genetic diversity in an essential effort to provide harmonization across DENV studies.

Concepts of Augmented Image Space and Transformed Feature Space for Efficient Visual Servoing of an “Eye-in-Hand Robot”

Robotica ◽  
1991 ◽  
Vol 9 (2) ◽  
pp. 203-212 ◽  
Author(s):  
Won Jang ◽  
Kyungjin Kim ◽  
Myungjin Chung ◽  
Zeungnam Bien
Keyword(s):  
Visual Feedback ◽  
Visual Servoing ◽  
Industrial Robot ◽  
Robot Vision ◽  
Feature Space ◽  
Image Features ◽  
Image Space ◽  
Formal Definition ◽  
Computational Burden ◽  
Definition Of

SUMMARYFor efficient visual servoing of an “eye-in-hand” robot, the concepts of Augmented Image Space and Transformed Feature Space are presented in the paper. A formal definition of image features as functionals is given along with a technique to use defined image features for visual servoing. Compared with other known methods, the proposed concepts reduce the computational burden for visual feedback, and enhance the flexibility in describing the vision-based task. Simulations and real experiments demonstrate that the proposed concepts are useful and versatile tools for the industrial robot vision tasks, and thus the visual servoing problem can be dealt with more systematically.

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