Job-Scheduling Games with Time-Dependent Processing Times

TL;DR

This paper explores job-scheduling games with time-dependent processing times, analyzing equilibrium existence, efficiency, and proposing mechanisms to improve outcomes in environments with positive or negative deterioration.

Contribution

It introduces a unifying framework for equilibrium analysis with delay-averse agents, characterizes conditions for equilibrium existence, and proposes mechanisms with tight bounds on the Price of Anarchy.

Findings

Pure Nash equilibria exist for delay-averse jobs and can be computed efficiently.

Deciding equilibrium existence is NP-complete for non-delay-averse jobs.

Proposed mechanisms achieve constant or tight bounds on the Price of Anarchy.

Abstract

Job-scheduling games have traditionally assumed fixed processing times. However, in many realistic environments, ranging from cyber-security response to high-frequency trading, a task's duration depends on its starting time. We study job-scheduling games with time-dependent processing times, where job lengths are linear functions of their start times, exhibiting either positive deterioration (increasing length) or negative deterioration (decreasing length). We analyze these games under various coordination mechanisms and priority policies. By introducing the concept of delay-averse agents, we provide a unifying framework to characterize equilibrium existence. For delay-averse jobs, we show that stability is maintained and pure Nash equilibria (NE) can be computed efficiently. In contrast, for non-delay-averse jobs, we demonstrate that a NE may not exist, and prove that deciding its existence is NP-complete, even on identical machines - a fundamental departure from classical coordination mechanisms. Regarding equilibrium inefficiency, we show that the Price of Anarchy (PoA) can be significantly higher than in environments with fixed processing times. To mitigate this, we propose and analyze three coordination mechanisms: SBPT (Shortest Basic Processing Time), which reduces the PoA in games with positive deterioration to a constant, and SDR (Smallest Deterioration Rate) and LBDR (Largest Basic-Deterioration Ratio) for negative deterioration, which achieve tight constant PoA bounds of $2$ and $\max\{\frac{e}{e-1}, 2-\frac{1}{m}\}$, respectively. Our results bridge the gap between centralized time-dependent scheduling and decentralized game-theoretic analysis.