FUNNet:a novel biologically-inspired routing algorithm based on fungi

Future data communication networks show three emerging trends: increasing size of networks, increasing traffic volumes and dynamic network topologies. Efficient network management solutions are required that are scalable, can cope with large, and increasing, traffic volumes and provide decentralised and adaptive routing strategies that cope with the dynamics of the network topology. Routing strategies are an important aspect of network management as they have a significant influence on the overall network performance. This paper introduces the preliminary studies for FUNNet, a new routing algorithm inspired by the kingdom of Fungi. Fungi form robust, resilient and responsive networks and these networks change topology as a consequence of changes in local conditions. Fungi are capable of expanding in size as they self-regulate and optimise the balance between exploration and exploitation which is dependent on the transport of the internal resource, i.e. ‘traffic’, within the network. FUNNet exploits the biological processes that are responsible for simulating fungal networks in a bio-inspired routing protocol. The initial results are positive and suggest that fungal metaphors can improve network management, although further evaluation of more complex scenarios is required

Intermediate dimension of images of sequences under fractional Brownian motion

We show that the almost sure θ-intermediate dimension of the image of the set Fp ={0, 1,1/2p,1/3p,...} under index-h fractional Brownian motion is θ/(ph+θ), a value that is smaller than that given by directly applying the Hölder bound for fractional Brownian motion. In particular this establishes the box-counting dimension of these images.PostprintPeer reviewe