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Item Simulating large random Boolean networks(Massey University, 2007) Hawick, K.A.; James, H.A.; Scogings, C.J.The Kauffman N-K, or random boolean network, model is an important tool for exploring the properties of large scale complex systems. There are computational challenges in simulating large networks with high connectivities. We describe some high-performance data structures and algorithms for implementing large-scale simulations of the random boolean network model using various storage types provided by the D programming language. We discuss the memory complexity of an optimised simulation code and present some measured properties of large networks.Item Node importance ranking and scaling properties of some complex road networks(Massey University, 2007) Hawick, K.A.; James, H.A.The scaling and other quantifiable properties of a network have recently been proven valuable in understanding the robustness and vulnerability properties of various societal and infrastructural networks. In this paper we revisit the algorithms for computing various quantifiable properties of a planar road network and consider the algorithmic complexity and scalability in the light of recent technological advances. We compute properties for a sample of interesting trunk road networks and discuss their applicability in determining the relative importance or criticality to the whole network of a particular node. We discuss the implications of present and anticipated technological capabilities in calculating properties for anticipated network sizes in the light of 64-bit computer architectures and commodity parallel computing.
