Chronotopic Optimization: A Temporal Sequencing Approach to Computational Resource Allocation

Posted: Oct 28, 2025

• Dr. Elara Vance
• Professor Kaito Tanaka
• Dr. Isabelle Moreau

Abstract

Contemporary computational systems face increasingly complex resource allocation challenges as demand patterns become more dynamic and unpredictable. Traditional optimization approaches, while effective in static or slowly changing environments, often struggle to adapt to the rapid temporal variations characteristic of modern computing workloads. This paper introduces a fundamentally different perspective on resource allocation by treating computational resources not as spatial entities to be distributed, but as temporal sequences to be orchestrated. The concept of chronotopic optimization emerged from our observation that many resource contention problems in computing systems exhibit periodic or quasi-periodic patterns that are poorly captured by existing optimization frameworks. Rather than focusing on where resources should be allocated at a given moment, we investigate when resources should be made available relative to demand patterns. This temporal sequencing approach represents a paradigm shift from spatial distribution to temporal orchestration. Our research addresses three fundamental questions: How can we formally characterize the temporal properties of computational resource demands? What algorithmic principles enable effective sequencing of resource availability?