Paper Info
Title
Extending IoT/M2M system scalability by network slicing.
Abstract
In this research, we have extended our initial effort in cloud-based IoT/M2M system scalability and developed a more robust solution by considering diverse QoS requirements from various IoT/M2M traffic patterns. Though our initial effort created a highly scalable architecture for IoT/M2M platforms based on OpenStack, it treated all IoT/M2M traffic without any discrepancy in the same underlying network (i.e. in the same network slice). Now, by leveraging software-defined networking in OpenStack and by using our traffic-slice optimal matching algorithm, we can direct different types of IoT traffic to feasible network slices in terms of QoS. Our experiments show that when compared with a system without network slicing, our scalability system performs better in terms of response time, power consumption, and computational cost.
Year
Venue
Field
2018
NOMS
Optimal matching,Computer science,Slicing,Response time,Computer network,Quality of service,Bandwidth (signal processing),Pattern matching,Cloud computing,Distributed computing,Scalability
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
David de la Bastida100.34
Fuchun Joseph Lin29620.75