Parallel Network Simulation under Distributed Genesis
Proceedings of the seventeenth workshop on Parallel and distributed simulation
Realistic Large-Scale Online Network Simulation
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Gossip-based aggregation in large dynamic networks
ACM Transactions on Computer Systems (TOCS)
Field review: Complex systems: Network thinking
Artificial Intelligence
A Primer for Real-Time Simulation of Large-Scale Networks
ANSS-41 '08 Proceedings of the 41st Annual Simulation Symposium (anss-41 2008)
Simulation of scale-free networks
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
Switching to High Gear: Opportunities for Grand-Scale Real-Time Parallel Simulations
DS-RT '09 Proceedings of the 2009 13th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications
Human Flesh Search Model Incorporating Network Expansion and GOSSIP with Feedback
DS-RT '09 Proceedings of the 2009 13th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications
Generation and analysis of large synthetic social contact networks
Winter Simulation Conference
Empirical Study on Entity Interaction Graph of Large-Scale Parallel Simulations
PADS '11 Proceedings of the 2011 IEEE Workshop on Principles of Advanced and Distributed Simulation
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Many social systems can be described in terms of complex networks of interacting dynamic entities. The research on social system's dynamics, such as epidemic or rumor spreading, are often suffered from constraints of relatively small to medium scale networks, or dependence on the underlying network assumptions, resulting in limited capacity for dynamics prediction. This paper proposes SUPE-Net, an efficient parallel simulation environment for large-scale social networks. Built on parallel discrete event simulation engine, the SUPE-Net enables high fidelity modeling of social networks with different topologies and complex dynamics protocols. SUPE-Net automatically maps large-scale social networks onto multi-processors and adopts the discrete event fashion to study the complex network dynamics. Different network topologies, including random, small-world, scale-free, and real networks, can be easily constructed and plugged in for comparative study. The execution efficiency of SUPE-Net is demonstrated by simulation experiments of gossip dynamics on the actor networks with millions of entities.