Distributed Single-Source Shortest Path Algorithms with Two-Dimensional Graph Layout

Many algorithms for graph layout have been devised over the last 30 years spanning both the graph drawing and information visualisation communities. This article first reviews the advances made in the field of graph drawing that have then often been applied by the information visualisation community. There then follows a discussion of a range of techniques developed specifically for graph visualisations. Graph drawing algorithms are categorised into the following approaches: force-directed layouts, the use of dimension reduction in graph layout and computational improvements including multi-level techniques. Methods developed specifically for graph visualisation often make use of node-attributes and are categorised based on whether the attributes are used to introduce constraints to the layout, provide a clustered view or define an explicit representation in two-dimensional space. The similarities and distinctions between these techniques are examined and the aim is to provide a detailed assessment of currently available graph layout techniques, specifically how they can be used by visualisation practitioners, and to motivate further research in the area.

Download Full-text

Experimental Study of Dynamic Single-Source Shortest Path Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.58-60.1493 ◽

2011 ◽

Vol 58-60 ◽

pp. 1493-1498

Author(s):

Qian Cai Xiao ◽

Ming Qi Li ◽

Wen Qiang Guo

Keyword(s):

Shortest Path ◽

Single Source ◽

Shortest Path Algorithm ◽

Time Efficiency ◽

Dynamic Algorithms ◽

Dynamic Topology ◽

Shortest Path Algorithms ◽

Relationship Of ◽

The Relationship ◽

Better Than

In this paper, software Inet 3.0 is applied to generate topology, which randomly generates dynamic topology nodes. Based on dynamic shortest path algorithms put forward by P.Narvaez, Xiaobin et al, we analyzed the time efficiency of dynamic and static shortest path algorithms, the different time efficiency inner dynamic shortest path algorithms, and the relationship of time efficiency between topology and dynamic shortest path algorithms. The result shows that Xiaobin algorithm is statistically better than Narvaez algorithm about 20-30 percent. Dynamic algorithms are not always better than static algorithms considering the amount of changed topology. Dynamic and static algorithms are roughly same when the amount of changed topology holds 10 percent. Dynamic algorithms perform better when less than 10 percent, otherwise static algorithms will be better. The time efficiency of dynamic algorithms is related to special topology.

Download Full-text

Comparison of Single Source Shortest Path Algorithms on Two Recent Asynchronous Many-task Runtime Systems

2015 IEEE 21st International Conference on Parallel and Distributed Systems (ICPADS) ◽

10.1109/icpads.2015.90 ◽

2015 ◽

Cited By ~ 1

Author(s):

Jesun Sahariar Firoz ◽

Martina Barnas ◽

Marcin Zalewski ◽

Andrew Lumsdaine

Keyword(s):

Shortest Path ◽

Runtime Systems ◽

Single Source ◽

Shortest Path Algorithms

Download Full-text

Spatial clustering analysis of green economy based on knowledge graph

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-219074 ◽

2021 ◽

pp. 1-10

Author(s):

Shiyuan Zhou ◽

Xiaoqin Yang ◽

Qianli Chang

Keyword(s):

Spatial Data ◽

Clustering Analysis ◽

Spatial Clustering ◽

Evaluation Model ◽

Principal Component ◽

Green Economy ◽

Membership Degree ◽

Two Dimensional ◽

Dimensional Graph ◽

Improved Algorithm

By organically combining principal component analysis, spatial autocorrelation algorithm and two-dimensional graph theory clustering algorithm, the comprehensive evaluation model of regional green economy is explored and established. Based on the evaluation index system of regional green economy, this paper evaluates the development of regional green economy comprehensively by using principal component analysis, and evaluates the competitive advantage of green economy and analyzes the spatial autocorrelation based on the evaluation results. Finally, the green economy and local index score as observed values, by using the method of two-dimensional graph clustering analysis of spatial clustering. In view of the fuzzy k –modes cluster membership degree measure method without considering the defects of the spatial distribution of object, double the distance and density measurement of measure method is introduced into the fuzzy algorithm of k –modes, thus in a more reasonable way to update the membership degree of the object. Vote, MUSH-ROOM and ZOO data sets in UCI machine learning library were used for testing, and the F value of the improved algorithm was better than that of the previous one, indicating that the improved algorithm had good clustering effect. Finally, the improved algorithm is applied to the spatial data collected from Baidu Map to cluster, and a good clustering result is obtained, which shows the feasibility and effectiveness of the algorithm applied to spatial data. Results show that the development of green economy using the analysis method of combining quantitative analysis and qualitative analysis, explores the connotation of green economy with space evaluation model is feasible, small make up for the qualitative analysis of the green economy in the past, can objective system to reflect the regional green economic development level, will help policy makers scientific formulating regional economic development strategy, green integrated development of regional green economy from the macroscopic Angle, the development of network system.

Download Full-text