Category Archive: 'M.TECH OMNET++ PROJECT'

Experimental assessment of GMPLS/PCE-controlled Multi-Flow Optical Transponders in flexgrid networks

We propose and implement required GMPLS/PCE routing and signaling protocol extensions for the configuration/control of MF OTPs. A novel online RSMA algorithm allows experimentally evaluating the automatic provisioning of LSPs including MF OTPs.

The SDN/NFV Cloud Computing platform and transport network of the ADRENALINE testbed

This work extends NFV paradigm to transport networks, known as Transport NFV. This paper presents a detailed overview of the SDN/NFV services that are offered on top of the Cloud Computing platform and transport network of the ADRENALINE Testbed. On the one hand, we propose a generic architecture for SDN/NFV services deployed over multi-domain transport […]

Maximum power point tracking for a photovoltaic water pumping system with sliding mode control and fuzzy wavelet networkMaximum power point tracking for a photovoltaic network

This paper presents a maximum power point tracking method (MPPT) that combines fuzzy wavelet network with sliding mode control for a photovoltaic pumping system. For the best use, the photovoltaic (PV) generator must operate at its maximum power point (MPP). SMC uses a high switching gain to cover the neglected uncertainties in the system model. […]

An application oriented evaluation method for network performance reliability

Congestion phenomenon has been observed in communication networks for many years, and one important reason for this is the effect of network applications. In actual networks, different applications may be provided by the same server node. This results in coupling between the applications. This coupling relationship makes it difficult to evaluate actual network reliability, with […]

Rapid calculation of missile aerodynamic coefficients using artificial neural networks

A variety of machine-learning methods has been applied to problems for which physics-based solutions are either nonexistent or computationally expensive. Based on such methods, surrogate models, i.e., empirical models that are trained on outputs of the more computationally intensive methods, can provide acceptable accuracy while dramatically reducing execution time and expense. This work describes the […]