ALFOUDI, Ali, NEWAZ, Shah, OTEBOLAKU, Abayomi, LEE, Gyu Myoung and PEREIRA, Rubem (2019). An efficient resource management mechanism for network slicing in LTE network. IEEE Access, 7, 89441-89457. [Article]
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Otebolaku-EfficientResourceManagement(VoR).pdf - Published Version
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Otebolaku-EfficientResourceManagement(VoR).pdf - Published Version
Available under License Creative Commons Attribution.
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Abstract
The proliferation of mobile devices and user applications has continued to contribute
to the humongous volume of data traffic in cellular networks. To surmount this challenge, service and
resource providers are looking for alternative mechanisms that can successfully facilitate managing network
resources in a more dynamic, predictive and distributed manner. New concepts of network architectures such
as Software Defined Network (SDN) and Network Function Virtualization (NFV) have paved the way to
move from static to flexible networks. They make networks more flexible (i.e. network providers capable of
on-demand provisioning), easily customizable and cost effective. In this regard, network slicing is emerging
as a new technology built on the concepts of SDN and NFV. It splits a network infrastructure into isolated
virtual networks and allows them to manage resources allocation individually based on their requirements
and characteristics. Most of the existing solutions for network slicing are computationally expensive because
of the length of time they require to estimate the resources required for each isolated slice. In addition, there
is no guarantee that the resource allocation is fairly shared among users in a slice. In this paper, we propose
a Network Slicing Resource Management (NSRM) mechanism to assign the required resources for each
slice in an LTE network, taking into consideration resources isolation between different slices. In addition,
NSRM aims to ensure isolation and fair sharing of distributed bandwidths between users belonging to the
same slice. In NSRM, depending on requirements, each slice can be customized (e.g. each can have a
different scheduling policy).
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