Extending IoT/M2M system scalability by network slicing

David De La Bastida, Fuchun Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


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.

Original languageEnglish
Title of host publicationIEEE/IFIP Network Operations and Management Symposium
Subtitle of host publicationCognitive Management in a Cyber World, NOMS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)9781538634165
StatePublished - 6 Jul 2018
Event2018 IEEE/IFIP Network Operations and Management Symposium, NOMS 2018 - Taipei, Taiwan
Duration: 23 Apr 201827 Apr 2018

Publication series

NameIEEE/IFIP Network Operations and Management Symposium: Cognitive Management in a Cyber World, NOMS 2018


Conference2018 IEEE/IFIP Network Operations and Management Symposium, NOMS 2018


  • Cloud Computing
  • Internet of Things
  • Network Slicing
  • OpenStack
  • QoS Matching
  • Scalability
  • SDN


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