Research Article
NPRA: Novel Policy Framework for Resource Allocation in 5G Software Defined Networks
@ARTICLE{10.4108/eai.22-3-2018.154387, author={Sahrish Khan Tayyaba and Adnan Akhunzada and Noor Ul Amin and Munam Ali Shah and Faheem Khan and Ihsan Ali}, title={NPRA: Novel Policy Framework for Resource Allocation in 5G Software Defined Networks}, journal={EAI Endorsed Transactions on Mobile Communications and Applications}, volume={4}, number={13}, publisher={EAI}, journal_a={MCA}, year={2018}, month={3}, keywords={Resource Allocation; SDN, 5G, Cellular Network}, doi={10.4108/eai.22-3-2018.154387} }
- Sahrish Khan Tayyaba
Adnan Akhunzada
Noor Ul Amin
Munam Ali Shah
Faheem Khan
Ihsan Ali
Year: 2018
NPRA: Novel Policy Framework for Resource Allocation in 5G Software Defined Networks
MCA
EAI
DOI: 10.4108/eai.22-3-2018.154387
Abstract
In cellular networks, physical resources are always limited, especially when shared among different contributors such as mobile network operator (MNO) or mobile virtual network operators (MVNO) etc. Software Defined Network (SDN) and Network Function Virtualization (NFV) is a Current research area. SDN-based cellular networks provide high Quality of Services (QoS) to the end-user and NFV provides isolation. The sharing of resources is often provided by leveraging virtualization. SDN can generate new forwarding rules and policies for dynamic routing decision based on the traffic classification. However, virtualization in cellular networks is still in infancy and many issues and challenges remain unaddressed. The queue-length problem for providing QoS is cellular network requires attention. The queue management requires separate management protocols for fair allocation of resources. In this research paper, we propose a novel framework for resource allocation and bandwidth management in the 5G cellular network. We are using two level of virtualization, i.e., implementing dynamic resource optimization at network slice manager and executing optimized policies at the wireless virtual manager.
Copyright © 2018 Sahrish Khan Tayyaba et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.