Pomelo

Author:

Chen Zhuo1,Chen Yang2,Ding Cong3,Deng Beixing4,Li Xing4

Affiliation:

1. Tsinghua Universiy, Beijing, China

2. Duke University, Durham, USA

3. University of Goettingen, Goettingen, Germany

4. Tsinghua University, Beijing, China

Abstract

Computing the shortest-path distances between nodes is a key problem in analyzing social graphs. Traditional methods like breadth-first search (BFS) do not scale well with graph size. Recently, a Graph Coordinate System, called Orion, has been proposed to estimate shortest-path distances in a scalable way. Orion uses a landmark-based approach, which does not take account of the shortest-path distances between non-landmark nodes in coordinate calculation. Such biased input for the coordinate system cannot characterize the graph structure well. In this paper, we propose Pomelo, which calculates the graph coordinates in a decentralized manner. Every node in Pomelo computes its shortest-path distances to both nearby neighbors and some random distant neighbors. By introducing the novel partial BFS, the computational overhead of Pomelo is tunable. Our experimental results from different representative social graphs show that Pomelo greatly outperforms Orion in estimation accuracy while maintaining the same computational overhead.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Software

Reference6 articles.

1. Social computing data repository at arizona state university. http://socialcomputing.asu.edu/. Social computing data repository at arizona state university. http://socialcomputing.asu.edu/.

2. Phoenix: Towards an Accurate, Practical and Decentralized Network Coordinate System

3. Vivaldi

4. Predicting Internet network distance with coordinates-based approaches

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