On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Concrete Mathematics: A Foundation for Computer Science
Concrete Mathematics: A Foundation for Computer Science
Stochastic models for the Web graph
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Power laws and the AS-level internet topology
IEEE/ACM Transactions on Networking (TON)
Parallel Algorithms for Evaluating Centrality Indices in Real-world Networks
ICPP '06 Proceedings of the 2006 International Conference on Parallel Processing
Planetary-scale views on a large instant-messaging network
Proceedings of the 17th international conference on World Wide Web
Dynamics of large networks
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Proceedings of the 14th International Conference on Extending Database Technology
Efficient generation of networks with given expected degrees
WAW'11 Proceedings of the 8th international conference on Algorithms and models for the web graph
Hi-index | 0.00 |
Recently, there has been substantial interest in the study of various random networks as mathematical models of complex systems. As these complex systems grow larger, the ability to generate progressively large random networks becomes all the more important. This motivates the need for efficient parallel algorithms for generating such networks. Naive parallelization of the sequential algorithms for generating random networks may not work due to the dependencies among the edges and the possibility of creating duplicate (parallel) edges. In this paper, we present MPI-based distributed memory parallel algorithms for generating random scale-free networks using the preferential-attachment model. Our algorithms scale very well to a large number of processors and provide almost linear speedups. The algorithms can generate scale-free networks with 50 billion edges in 123 seconds using 768 processors.