Distributed Multithreaded Breadth-First Search on Large Graphs Using DXGraph

2016 ◽  
Author(s):  
Stefan Nothaas ◽  
Kevin Beineke ◽  
Michael Schottner
Keyword(s):  
Breadth First Search ◽  
Large Graphs

scholarly journals Chaotic Traversal (CHAT): Very Large Graphs Traversal Using Chaotic Dynamics

2017 ◽  
Vol 27 (14) ◽  
pp. 1750215 ◽  
Author(s):  
Boonyarit Changaival ◽  
Martin Rosalie ◽  
Grégoire Danoy ◽  
Kittichai Lavangnananda ◽  
Pascal Bouvry
Keyword(s):  
Language Processing ◽  
Topological Structure ◽  
Chaotic Dynamics ◽  
Computation Time ◽  
Classical Solutions ◽  
Breadth First Search ◽  
Large Graphs ◽  
Database Querying ◽  
Graph Traversal ◽  
Traversal Algorithm

Graph Traversal algorithms can find their applications in various fields such as routing problems, natural language processing or even database querying. The exploration can be considered as a first stepping stone into knowledge extraction from the graph which is now a popular topic. Classical solutions such as Breadth First Search (BFS) and Depth First Search (DFS) require huge amounts of memory for exploring very large graphs. In this research, we present a novel memoryless graph traversal algorithm, Chaotic Traversal (CHAT) which integrates chaotic dynamics to traverse large unknown graphs via the Lozi map and the Rössler system. To compare various dynamics effects on our algorithm, we present an original way to perform the exploration of a parameter space using a bifurcation diagram with respect to the topological structure of attractors. The resulting algorithm is an efficient and nonresource demanding algorithm, and is therefore very suitable for partial traversal of very large and/or unknown environment graphs. CHAT performance using Lozi map is proven superior than the, commonly known, Random Walk, in terms of number of nodes visited (coverage percentage) and computation time where the environment is unknown and memory usage is restricted.

scholarly journals Spikyball Sampling: Exploring Large Networks via an Inhomogeneous Filtered Diffusion

Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 275
Author(s):  
Benjamin Ricaud ◽  
Nicolas Aspert ◽  
Volodymyr Miz
Keyword(s):  
Social Networks ◽  
Large Scale ◽  
Sampling Methods ◽  
Breadth First Search ◽  
Large Graphs ◽  
New Approach ◽  
Random Subset ◽  
Large Size ◽  
Large Scale Networks ◽  
Search Approach

Studying real-world networks such as social networks or web networks is a challenge. These networks often combine a complex, highly connected structure together with a large size. We propose a new approach for large scale networks that is able to automatically sample user-defined relevant parts of a network. Starting from a few selected places in the network and a reduced set of expansion rules, the method adopts a filtered breadth-first search approach, that expands through edges and nodes matching these properties. Moreover, the expansion is performed over a random subset of neighbors at each step to mitigate further the overwhelming number of connections that may exist in large graphs. This carries the image of a “spiky” expansion. We show that this approach generalize previous exploration sampling methods, such as Snowball or Forest Fire and extend them. We demonstrate its ability to capture groups of nodes with high interactions while discarding weakly connected nodes that are often numerous in social networks and may hide important structures.

Algoritma Perencanaan Jalur Kendaraan Otonom berbasis Hibridisasi Algoritma BFS dan Path Smoothing

2020 ◽  
Vol 8 (1) ◽  
pp. 13-22
Author(s):  
Muhammad Aria
Keyword(s):  
Breadth First Search ◽  
Search Path ◽  
Path Smoothing

Abstrak – Pada penelitian ini dirancang algoritma alternatif untuk perencanaan jalur kendaraan otonom. Algoritma yang diusulkan adalah hibridisasi dari algoritma Breadth First Search (BFS) dan algoritma path smoothing (BFS – path smoothing). Berdasarkan pengamatan dari hasil pengujian, keuntungan dari algoritma BFS adalah dapat memberikan solusi yang menuju solusi optimal, tetapi memiliki kelemahan dari waktu komputasi yang tinggi. Agar diperoleh solusi yang optimal, maka jalur yang dihasilkan oleh algoritma BFS akan diproses lebih lanjut oleh algoritma path smoothing. Walaupun algoritma BFS - path smoothing memiliki waktu komputasi yang tinggi, tetapi untuk tujuan mendapatkan solusi yang optimal, waktu komputasi BFS – path smoothing masih lebih rendah daripada algoritma RRT* untuk mendapatkan solusi yang optimal. Algoritma RRT* adalah salah satu algoritma yang umum digunakan untuk perencanaan jalur pada kendaraan otonom. Proses hibridisasi ini dilakukan dengan cara menjalankan algoritma BFS terlebih dahulu untuk memberikan solusi awal. Solusi awal tersebut kemudian ditingkatkan kualitasnya menggunakan algoritma path smoothing untuk memperoleh solusi yang optimal. Pengujian algoritma BFS-path smoothing ini dilakukan secara simulasi menggunakan beberapa kasus benchmark yang ada, yaitu lingkungan narrow, maze, trap dan clutter. Kriteria optimalitas yang dibandingkan adalah biaya jalur dan waktu komputasi. Pada pengujian, performansi dari algoritma BFS-path smoothing dibandingkan dengan performansi dari algoritma RRT*. Kami menunjukkan bahwa algoritma yang diusulkan dapat menghasilkan output jalur dengan kualitas yang lebih tinggi daripada jalur yang diproduksi oleh RRT*.   Kata Kunci : Beadth First Search, path smoothing, perencanaan jalur, pengujian simulasi, RRT*

Network search

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Web Search ◽  
Distributed Databases ◽  
Small World ◽  
Peer Networks ◽  
Model Parameters ◽  
Breadth First Search ◽  
Ranking Algorithms ◽  
Network Search ◽  
Peer To Peer Networks ◽  
Search Processes

This chapter gives a discussion of search processes on networks. It begins with a discussion of web search, including crawlers and web ranking algorithms such as PageRank. Search in distributed databases such as peer-to-peer networks is also discussed, including simple breadth-first search style algorithms and more advanced “supernode” approaches. Finally, network navigation is discussed at some length, motivated by consideration of Milgram's letter passing experiment. Kleinberg's variant of the small-world model is introduced and it is shown that efficient navigation is possible only for certain values of the model parameters. Similar results are also derived for the hierarchical model of Watts et al.

Computer algorithms

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Data Structures ◽  
Analysis Of Algorithms ◽  
Shortest Paths ◽  
Minimum Cut ◽  
Network Data ◽  
Computer Algorithms ◽  
Breadth First Search ◽  
Augmenting Path ◽  
Basic Concepts ◽  
Maximum Flows

This chapter introduces some of the fundamental concepts of numerical network calculations. The chapter starts with a discussion of basic concepts of computational complexity and data structures for storing network data, then progresses to the description and analysis of algorithms for a range of network calculations: breadth-first search and its use for calculating shortest paths, shortest distances, components, closeness, and betweenness; Dijkstra's algorithm for shortest paths and distances on weighted networks; and the augmenting path algorithm for calculating maximum flows, minimum cut sets, and independent paths in networks.

VColor*: a practical approach for coloring large graphs

2021 ◽  
Vol 15 (4) ◽  
Author(s):  
Yun Peng ◽  
Xin Lin ◽  
Byron Choi ◽  
Bingsheng He
Keyword(s):  
Practical Approach ◽  
Large Graphs
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