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Real Time Proportional Throughput Maximization: How much advance notice should you give your scheduler?

Nadim A. Mottu

TL;DR

The paper studies real-time throughput maximization under online scheduling with advance notice, introducing the $t$-advance-notice model. It proves a tight online competitive bound of $\frac{t}{2t+1}$ for $t\in[0,1]$ (reducing to $\frac{1}{3}$ when $t\ge 1$) and shows this bound is optimal for proportional weights, with a universal $\frac{1}{2}$ barrier regardless of advance notice. Beyond proportional weights, advance-notice does not guarantee constant competitiveness for $C$-benevolent or unweighted cases, demonstrated via adversarial constructions. The results highlight when advance notice helps in real-time scheduling and open questions about larger advance times and alternative notice definitions, with implications for CPU scheduling and similar systems.

Abstract

We will be exploring a generalization of real time scheduling problem sometimes called the real time throughput maximization problem. Our input is a sequence of jobs specified by their release time, deadline and processing time. We assume that jobs are announced before or at their release time. At each time step, the algorithm must decide whether to schedule a job based on the information so far. The goal is to maximize the value of the sum of the processing times of jobs that finish before their deadline, this is often called real time throughput with proportional weights. We extend this problem by defining a notion of $t$-advance-notice, a measure of how far in advance each job is announced relative to their processing time. We show that there exists a $\frac{t}{2t+1}$-competitive algorithm when all jobs have $t$-advance-notice for $t\in [0,1]$, this gives us a competitive ratio of $\frac{1}{3}$ when $t$ is greater than or equal to $1$. We also show that this ratio is optimal for all algorithms with $t$-advance-notice and that the upper bound of $\frac{t}{2t+1}$-competitiveness holds for all $t$, in particular that regardless of how much advance-notice is given, no algorithm can reach $\frac{1}{2}$-competitiveness.

Real Time Proportional Throughput Maximization: How much advance notice should you give your scheduler?

TL;DR

The paper studies real-time throughput maximization under online scheduling with advance notice, introducing the -advance-notice model. It proves a tight online competitive bound of for (reducing to when ) and shows this bound is optimal for proportional weights, with a universal barrier regardless of advance notice. Beyond proportional weights, advance-notice does not guarantee constant competitiveness for -benevolent or unweighted cases, demonstrated via adversarial constructions. The results highlight when advance notice helps in real-time scheduling and open questions about larger advance times and alternative notice definitions, with implications for CPU scheduling and similar systems.

Abstract

We will be exploring a generalization of real time scheduling problem sometimes called the real time throughput maximization problem. Our input is a sequence of jobs specified by their release time, deadline and processing time. We assume that jobs are announced before or at their release time. At each time step, the algorithm must decide whether to schedule a job based on the information so far. The goal is to maximize the value of the sum of the processing times of jobs that finish before their deadline, this is often called real time throughput with proportional weights. We extend this problem by defining a notion of -advance-notice, a measure of how far in advance each job is announced relative to their processing time. We show that there exists a -competitive algorithm when all jobs have -advance-notice for , this gives us a competitive ratio of when is greater than or equal to . We also show that this ratio is optimal for all algorithms with -advance-notice and that the upper bound of -competitiveness holds for all , in particular that regardless of how much advance-notice is given, no algorithm can reach -competitiveness.

Paper Structure

This paper contains 13 sections, 8 theorems, 2 equations, 3 figures, 1 algorithm.

Key Result

Theorem 2.1

Let Off be any optimal offline algorithm for proportional throughput. There exists an online algorithm $\mathcal{A}_\textsc{Off}$ which is at least $\frac{t}{2t+1}$-competitive for real time proportional throughput when all jobs have $t$-advance-notice for $t \in [0,1]$.

Figures (3)

  • Figure 1: Conflicting jobs partitioning
  • Figure 2: Dividing a job in conflicting with multiple jobs into partial jobs
  • Figure 3: $ALG$ vs $OPT$ schedule

Theorems & Definitions (16)

  • Definition 1.1
  • Theorem 2.1
  • Claim
  • Claim
  • Claim
  • Claim
  • Corollary 2.1
  • Corollary 2.2
  • Theorem 2.2
  • Corollary 2.3
  • ...and 6 more