Energy Efficiency Support for Software Defined Networks: a Serverless Computing Approach

TL;DR

This paper introduces a novel serverless, energy-aware approach for modular Software-Defined Networks, enabling on-demand deployment and significant energy efficiency improvements through analytical modeling and experimental validation.

Contribution

It pioneers the integration of serverless functions into SDN for energy efficiency, providing an analytical model and prototype to demonstrate practical benefits.

Findings

Significant energy efficiency improvements demonstrated.

Analytical model accurately predicts service time and power consumption.

Prototype implementation confirms practical applicability.

Abstract

Automatic network management strategies have become paramount for meeting the needs of innovative real-time and data-intensive applications, such as in the Internet of Things. However, meeting the ever-growing and fluctuating demands for data and services in such applications requires more than ever an efficient and scalable network resource management approach. Such approach should enable the automated provisioning of services while incentivising energy-efficient resource usage that expands throughout the edge-to-cloud continuum. This paper is the first to realise the concept of modular Software-Defined Networks based on serverless functions in an energy-aware environment. By adopting Function as a Service, the approach enables on-demand deployment of network functions, resulting in cost reduction through fine resource provisioning granularity. An analytical model is presented to approximate the service delivery time and power consumption, as well as an open-source prototype implementation supported by an extensive experimental evaluation. The experiments demonstrate not only the practical applicability of the proposed approach but significant improvement in terms of energy efficiency.