A Cost-Effective Approach for End-to-End QoS Management in NFV-Enabled IoT Platforms

Abstract

The systematic scaling approach is used in the literature as the only option to meet QoS requirements in response to the traffic load increase in IoT platforms. Such a solution reduces the load on the congested nodes and leads to an increase in the provisioning costs that, when measured at the scale of billions of devices, may hinder acceptability. Our objective is to enhance the existing approaches using and extending the emerging concept of Virtualized Network Functions (VNF), promoting End-to-End IoT traffic control. We start from the observation that, within Cloud-enabled platforms, the allocated resources are not fully used, making it possible to deploy traffic control network functions (NFs). Instead of systematically scaling a congested node, we dynamically deploy, on under-loaded nodes, additional NFs that exploit the available computing resources to differentiate the traffic processing level and to apply a QoS-oriented policy. The considered NFs extend the notion of VNF defined within Network Function Virtualization (NFV), to take advantage of component-based software design. To enable a possible use of the implemented functions, we formulate a multi-objective optimization problem for the efficient planning of adequate NFs and scaling actions, according to the considered multi-constrained context. The planner, called QoS4NIP (QoS for NFVenabled IoT Platforms), is based on a Genetic Algorithm (GA). The GA metaheuristic relies on biologically inspired operators such as mutation, crossover, and selection. QoS4NIP uses the GA to generate solutions to the identified multi-objective optimization problem by making a series of improvements in an iterative process. The experiments conducted on a realistic case study show that QoS4NIP outperforms autoscalingbased approaches (65% financial cost saved).

Adaptive Performance Analysis in IoT Platforms

“…In previous work [30], we proposed to enhance the existing approaches using and extending the emerging concept of Virtualized Network Functions (VNF), promoting End-to-End IoT traffic control. From the observation that, within NFV-enabled IoT Platforms (NIPs), the allocated resources are not fully used, we promote deploying traffic control network functions (NFs).…”

“…This component is invoked by Adaptive Performance Analysis component every time the selected metrics subset is updated. The Recovery component (see [30]) determines the set of candidate actions to recover from identified bottlenecks. This paper is focused on the realization of the Adaptive Performance Analysis component.…”

“…In our work, we handle the NIPs that implement the common reference architectures, such as oneM2M [1]. We consider that NFV-I in the Cloud/Fog/Edge host Virtualized Network Functions (VNF), Application Network Function(ANF) [30] and Physical Network Functions (PNF) offering the NIP service to the IoT Application and IoT devices.…”

An Autonomic Management System for IoT Platforms based on Data Analysis Tasks

“…It presents an active QoS infrastructure of wireless sensor networks (WSN), named QISM, which is based on middleware and service-oriented. QISM includes the active regulation mechanism based on feedback and negotiation between applications and network S ✓ X X [40] They propose an approach using the concept of virtualized network functions to dynamically deploy, on under-loaded nodes, additional network functions that exploit the available computing resources to differentiate the traffic processing level and to apply a QoS-oriented policy.…”

“…The systematic scaling approach is used in the literature as the only option to meet Quality of Service (QoS) requirements in response to the traffic load increase in IoT platforms. In the paper [40], the authors propose an alternative approach using the concept of virtualized network functions (VNFs). In this approach, they dynamically deploy, on underloaded nodes, additional NFs that exploit the available computing resources to differentiate the traffic processing level and to apply a QoS-oriented policy.…”