Disaggregation for Energy Efficient Fog in Future 6G Networks

TL;DR

This paper evaluates energy-efficient server disaggregation in future 6G fog networks, demonstrating up to 18% power savings and proposing a heuristic for optimized app placement considering delay constraints.

Contribution

It introduces a MILP model comparing traditional and disaggregated servers in fog networks and proposes a heuristic for energy and delay-aware app placement.

Findings

Disaggregated servers reduce fog network power consumption by up to 18%.

Proximity of fog sites to users affects app provisioning and delay performance.

The proposed heuristic effectively replicates MILP results for practical deployment.

Abstract

We study the benefits of adopting server disaggregation in the fog computing tier by evaluating energy efficient placement of interactive apps in a future fog 6G network. Using a mixed integer linear programming (MILP) model, we compare the adoption of traditional server (TS) and disaggregated server (DS) architectures in a fog network comprising of selected fog computing sites in the metro and access networks. Relative to the use of TSs, our results show that the adoption of DS improves the energy efficiency of the fog network and enables up to 18% reduction in total fog computing power consumption. More instances of interactive fog apps are provisioned in a fog network that is implemented over a network topology with high delay penalty. This ensures that minimal delay is experienced by distributed users. Our result also shows that the proximity of fog computing sites such as metro-central offices and radio cell sites to geo-distributed users of interactive fog applications make them important edge locations for provisioning moderately delay sensitive fog apps. However, fog applications with more stringent delay thresholds require in situ processing at directly connected radio cell sites or at the location of the requesting users. Finally, we propose a heuristic for energy efficient and delay aware placement of interactive fog apps in a fog network which replicates the trends observed during comprehensive analysis of the exact results obtained by solving the MILP model formulated in this paper. Our results and proposed MILP and heuristic provide a good reference and tool for fog network design and deployment.