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281 results on '"P. W. C. Prasad"'

1. Network slicing: a next generation 5G perspective

Author

Prashant Subedi, Abeer Alsadoon, P. W. C. Prasad, Sabih Rehman, Nabil Giweli, Muhammad Imran, and Samrah Arif

Subjects
5G communication, Software-defined networks, Network slicing, Slicing use cases, Network function virtualisation, Telecommunication, TK5101-6720, Electronics, TK7800-8360
Abstract

Abstract Fifth-generation (5G) wireless networks are projected to bring a major transformation to the current fourth-generation network to support the billions of devices that will be connected to the Internet. 5G networks will enable new and powerful capabilities to support high-speed data rates, better connectivity and system capacity that are critical in designing applications in virtual reality, augmented reality and mobile online gaming. The infrastructure of a network that can support stringent application requirements needs to be highly dynamic and flexible. Network slicing can provide these dynamic and flexible characteristics to a network architecture. Implementing network slicing in 5G requires domain modification of the preexisting network architecture. A network slicing architecture is proposed for an existing 5G network with the aim of enhancing network dynamics and flexibility to support modern network applications. To enable network slicing in a 5G network, we established the virtualisation of the underlying physical 5G infrastructure by utilising technological advancements, such as software-defined networking and network function virtualisation. These virtual networks can fulfil the requirement of multiple use cases as required by creating slices of these virtual networks. Thus, abstracting from the physical resources to create virtual networks and then applying network slicing on these virtual networks enable the 5G network to address the increased demands for high-speed communication.

Published
2021
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2. Complexity of XOR/XNOR boolean functions: a model using binary decision diagrams and back propagation neural networks

Author

Ali Assi, P. W. C. Prasad, Azam Beg, and V. C. Prasad

Subjects
binary decision diagrams (bdds), reduced ordered binary decision diagrams (robdds), xor/xnor min-terms, complexity, boolean functions, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95
Abstract

This paper proposes a model that predicts the complexity of Boolean functions with only XOR/XNOR min-terms using back propagation neural networks (BPNNs) applied to Binary Decision Diagrams (BDDs). The BPNN model (BPNNM) is developed through the training process of experimental data already obtained for XOR/XNOR-based Boolean functions. The outcome of this model is a unique matrix for the complexity estimation over a set of BDDs derived from Boolean expressions with a given number of variables and XOR/XNOR min-terms. The comparison results of the experimental and BPNNM underline the efficiency of this approach, which is capable of providing some useful clues about the complexity of the circuit to be implemented. It also proves the computational capabilities of NNs in providing reliable classification of the complexity of Boolean functions.

Published
2007

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