Considered is a mobile ad hoc network consisting of three types of nodes (source, destination and relay nodes) and using the two-hop relay routing protocol. Packets at relay nodes are assumed to have a limited lifetime in the network. All nodes are moving inside a bounded region according to some random mobility model. Both closed-form expressions, and asymptotic results when the number of nodes is large, are provided for the packet delivery delay and the energy needed to transmit a packet from the source to its destination. We also introduce and evaluate a variant of the two-hop relay protocol that limits the number of generated copies in the network. Our model is validated through simulations for two mobility models (random waypoint and random direction mobility models), numerical results for the two-hop relay protocols are reported, and the performance of the two-hop routing and of the epidemic routing protocols are compared.
An integrated Team-Artificial IntelligenceElectromagnetic, T-AI-EM, environment is developed to accurately determine the performance characteristics of synchronous reluctance motors (SynRM) with Axially Laminated Anisotropic (ALA) rotor configurations. This T-AI-EM is used to train a Fuzzy Logic system that predicts the optimal solution of the machine for any given input torque. The main objective of this optimization is to minimize the torque ripple corresponding to a given torque-load condition. The T-AI-EM is composed of two main blocks. The first consists of electromagnetic module utilizing indirectly coupled finite element state space (FE-SS) model. The second consists of an AI based model inspired from team member concept, that consists of several Adaptive Network Fuzzy Inference Systems, ANFISs, supervised by a Radial Based Network, RBN.
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