Virtual network mapping is one of the main problems in network virtualization. At present, virtual networking mapping aims at minimal resource consumption at substrate network, but ignores the resource demanded by the hidden hops, making bottlenecks due to the resource shortage at the hidden hops. This paper aims at the simultaneous loading balance of the substrate node and the substrate link, ...

Current Neural Network learning algorithms are limited in their ability to model non-linear dynamical systems. Most supervised gradient-based recurrent neural networks (RNNs) suffer from a vanishing error signal that prevents learning from inputs far in the past. Those that do not, still have problems when there are numerous local minima. We introduce a general framework for sequence learning, ...

The idea of using RBF neural networks for fuzzy rule extraction from numerical data is not new. The structure of this kind of architectures, which supports clustering of data samples, is favorable for considering clusters as if-then rules. However, in order for real if-then rules to be derived, proper antecedent parts for each cluster need to be constructed by selecting the appropriate subspace...

We study compressible and incompressible nonlinear elasticity variational problems in a general context. Our main result gives sufficient condition for an equilibrium to be global energy minimi...

This paper proposes a Neural Network model using Generalised kernel functions for the hidden layer of a feed forward network. These functions are Generalised Radial Basis Functions (GRBF), and the architecture, weights and node topology are learned through an evolutionary algorithm. The proposed model is compared with the corresponding standard hidden-node models: Product Unit (PU) neural netwo...

Hadoop MapReduce framework is an important distributed processing model for large-scale data intensive applications. The current Hadoop and the existing Hadoop distributed file system’s rack-aware data placement strategy in MapReduce in the homogeneous Hadoop cluster assume that each node in a cluster has the same computing capacity and a same workload is assigned to each node. Default Hadoop d...