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Unlike general purpose computer architectures that are comprised of complex processor cores and sequential computation, the brain is innately parallel and contains highly complex connections between computational units (neurons). Key to the architecture of the brain is a functionality enabled by the combined effect of spiking communication and sparse connectivity with unique variable efficacies and...
Information in neural networks is represented as weighted connections, or synapses, between neurons. This poses a problem as the primary computational bottleneck for neural networks is the vector-matrix multiply when inputs are multiplied by the neural network weights. Conventional processing architectures are not well suited for simulating neural networks, often requiring large amounts of energy...
The distributed, hop-by-hop routing architecture used in the Internet depends on algebraic properties of routing metrics to ensure traffic is forwarded over loop-free and best (LFB) paths. As the Internet evolves to serve as the converged communication infrastructure for the 21st century, the need for new metrics that violate these properties ([5], [9]) has been identified. Until recently, the behavior...
The work by Uthayanath Suthakar was supported by a Brunel University London College of Engineering, Design and Physical Sciences Thomas Gerald Gray postgraduate research scholarship. Uthayanath Suthakar also acknowledges the IEEE NSS-MIC for financial support in the form of a Trainee Grant.
The Internet is based on a hop-by-hop routing model where forwarding decisions are based on a packet's destination. With the evolution of the Internet to support real-time applications such as video and audio distribution, the Internet's routing architecture must be enhanced to support metrics that ensure the quality-of- service requirements of these applications. Sobrinho has shown that some of these...
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