Greening Geographical Load Balancing

, 2011

Category: EE

Overall Rating

1.6/5 (11/35 pts)

While this paper provided an early exploration into optimizing geographical data center load balancing for environmental objectives using formal optimization, its models and algorithms are based on significant simplifications of both the energy grid and data center technology that are now obsolete.
Modern research leveraging more sophisticated ML and holistic optimization techniques has already surpassed this work by addressing more realistic problem formulations.
Revisiting this specific paper offers no unique technical advantage for modern applications compared to starting with current state-of-the-art.

This paper's detailed analysis of the optimal mix of intermittent renewable energy sources (wind vs. solar) for a large, flexible, geographically distributed computing workload (internet-scale data centers) provides a unique lens...
...to explore unconventional approaches to AI-driven grid optimization and stability using highly flexible computational loads as active grid participants.
An unconventional research direction could be to use these advanced AI capabilities, combined with the foundational optimization framework for flexible load balancing presented in this thesis, to design and simulate a future grid paradigm where internet-scale data centers ... function as sophisticated, AI-controlled distributed energy resources.
They could perform intelligent, real-time load shifting across continents ... to actively respond to AI-powered forecasts predicting potential grid imbalances...

The paper's simplified model of "brown" versus "green" energy... doesn't capture the nuances of modern electricity markets.
Explicitly omitting switching costs (server on/off transition energy/wear-and-tear) and network congestion is a major flaw.
The algorithms (sequential Gauss-Seidel, gradient projection requiring complex projections) are likely more theoretically interesting than practically deployable at scale...
The treatment of storage in the local renewables section (Section 3.2.1) is highly simplistic.

Ignore