QoS and Resource-aware Security Orchestration and Life Cycle Management

Miloud Bagaa, Tarik Taleb, Jorge Bernal Bernabe, Antonio Skarmeta

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
71 Downloads (Pure)

Abstract

Zero-touch network and Service Management (ZSM) exploits Network Function Virtualization (NFV) and Software-Defined Networking (SDN) to efficiently and dynamically orchestrate different Service Function Chaining (SFC), whereby reducing capital expenditure and operation expenses. The SFC is an optimization problem that shall consider different constraints, such as Quality of Service (QoS), and actual resources, to achieve cost-efficient scheduling and allocation of the service functions. However, the large-scale, complexity and security issues brought by virtualized IoT networks, which embrace different network segments, e.g. Fog, Edge, Core, Cloud, that can also exploit proximity (computation offloading of virtualized IoT functions to the Edge), imposes new challenges for ZSM orchestrators intended to optimize the SFC, thereby achieving seamless user-experience, minimal end-to-end delay at a minimal cost. To cope with these challenges, this paper proposes a cost-efficient optimized orchestration system that addresses the whole life-cycle management of different SFCs, that considers QoS (including end-to-end delay, bandwidth, jitters), actual capacities of Virtual Network Functions (VNFs), potentially deployed across multiple Clouds-Edges, in terms of resources (CPU, RAM, storage) and current network security levels to ensure trusted deployments. The proposed orchestration system has been implemented and evaluated in the scope of H2020 Anastacia EU project<formula><tex>$^1$</tex></formula>, showing its feasibility and performance to efficiently manage SFC, optimizing deployment costs, reducing overall end-to-end delay and optimizing VNF instances distribution.

Original languageEnglish
Number of pages17
JournalIEEE Transactions on Mobile Computing
DOIs
Publication statusE-pub ahead of print - 2020
MoE publication typeA1 Journal article-refereed

Keywords

  • Cloud computing
  • Delays
  • Hardware
  • Optimization
  • Quality of service
  • Resource management
  • Security

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