Paper Info
Title
Dynamic Auto-scaling of VNFs based on Task Execution Patterns
Abstract
Investigation and collection of real-time data plays a very crucial part in the orchestration of network resources. Selection of the correct data is very important as it decides to auto-scale the resources. In cloud & SDN environments such as NFV, auto-scaling becomes more critical in terms of precision and accuracy. In our case, we propose a solution for auto-scaling the network resources based on the calculations made for every action's execution-time [1] of respective instances of a VNF. The instances for each VNF are auto-scaled on the basis of execution-times per time slot, and the number of cores that are assigned by the usage of weight factor [2] used for virtual/physical cores. Hence by using the proposed solution, we are able to enhance the proper resource provisioning to fulfill the dynamic demands [3] of future mobile networks.
Year
DOI
Venue
2019
10.23919/APNOMS.2019.8892836
2019 20th Asia-Pacific Network Operations and Management Symposium (APNOMS)
Keywords
Field
DocType
autoscaling,datacenter,sdn,nfv,vnf,execution-time,self-management,networks
Resource (disambiguation),Weight factor,Computer science,Network Functions Virtualization,Computer network,Provisioning,Autoscaling,Orchestration (computing),Scaling,Distributed computing,Cloud computing
Conference
ISSN
ISBN
Citations 
2576-8565
978-1-7281-2733-0
0
PageRank 
References 
Authors
0.34
4
4
Name
Order
Citations
PageRank
Asif Mehmood132.86
Talha Ahmed Khan266.76
Javier Jose Diaz Rivera343.58
Wang-Cheol Song45425.56