NFV Provisioning in Large-Scale Distributed Networks With Minimum Delay

Decentralized Adaptive Control of Large-Scale Non-affine Nonlinear Time-Delay Systems Using Neural Networks

In this paper, a decentralized adaptive neural controller is proposed for a class of large-scale nonlinear systems with unknown nonlinear, non-affine subsystems and unknown nonlinear time-delay interconnections. The stability of the closed loop system is guaranteed through Lyapunov-Krasovskii stability analysis. Simulation results are provided to show the effectiveness of the proposed approache...

Large Scale Distributed Deep Networks

Recent work in unsupervised feature learning and deep learning has shown that being able to train large models can dramatically improve performance. In this paper, we consider the problem of training a deep network with billions of parameters using tens of thousands of CPU cores. We have developed a software framework called DistBelief that can utilize computing clusters with thousands of machi...

Decentralized Interaction Estimators in Large Scale Power Systems with Neural Networks.

Distributed Simulation of Large-Scale PCS Networks

There has been rapid growth in demand for mobile communications over the past few years that has led to intensive research and development of complex PCS (personal communication service) networks. Capacity planning and performance modeling is necessary to maintain a high quality of service to the mobile subscriber while minimizing cost. Simulation is widely used in such studies, however, becaus...

Distributed distance measurement for large-scale networks

There is an increasing trend in the Internet that a set of replicated providers are qualified for a service or resource request from a client. In this case, it is advantageous to select the best provider considering some distance measures, such as hop count or path latency. In this paper, we present a Group-based Distance Measurement Service (GDMS), which estimates and disseminates distance inf...