Dynamic load management for IMS networks using network function virtualization

Title Dynamic load management for IMS networks using network function virtualization
Author Dandin, Kaan, Hokelek, I., Karabulut Kurt, G.
Publication Date: 2016
Publication Place - IEEE
Subject IMS, NFV, Load management
Type Document
Language English
Digital Yes
Manuscript No
Library: Özyeğin University
Library Asset ID 2374-9709
Record ID 73e4822c-ffac-40b4-bc77-3ebac11bd3d4
Date 2016
Sample Text Network Function Virtualization (NFV) is utilized to simplfy the deployment and management of constantly evolving and highly complex networking services. In this paper, we propose a dynamic load management framework for IMS networks using NFV, where IMS functions are created within a single virtual machine (VM) instance and moved to the cloud environment. Requests coming from the IMS clients are first processed by a Load Balancer module to efficiently distribute the incoming load over a pool of IMS VMs. The decision of switching an IMS VM instance on or off is performed by the VM provisioning service using the resource utilization information periodically received from the IMS VMs. The proof-of-concept experiments using a realistic testbed demonstrate that the proposed framework increases the scalability of the IMS networks when there are sudden significant increases in traffic.
DOI 10.1109/NOMS.2016.7502948
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Dynamic load management for IMS networks using network function virtualization

Author Dandin, Kaan, Hokelek, I., Karabulut Kurt, G.
Publication Date 2016
Publication Place - IEEE
Subject IMS, NFV, Load management
Type Document
Language English
Digital Yes
Manuscript No
Library Özyeğin University
Library Asset ID 2374-9709
Record ID 73e4822c-ffac-40b4-bc77-3ebac11bd3d4
Date 2016
Sample Text Network Function Virtualization (NFV) is utilized to simplfy the deployment and management of constantly evolving and highly complex networking services. In this paper, we propose a dynamic load management framework for IMS networks using NFV, where IMS functions are created within a single virtual machine (VM) instance and moved to the cloud environment. Requests coming from the IMS clients are first processed by a Load Balancer module to efficiently distribute the incoming load over a pool of IMS VMs. The decision of switching an IMS VM instance on or off is performed by the VM provisioning service using the resource utilization information periodically received from the IMS VMs. The proof-of-concept experiments using a realistic testbed demonstrate that the proposed framework increases the scalability of the IMS networks when there are sudden significant increases in traffic.
DOI 10.1109/NOMS.2016.7502948
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