Optimal Resource Scheduling and Allocation under Allowable Over-Scheduling

TL;DR

This paper develops an optimal resource scheduling method that incorporates allowable over-scheduling, using a novel AIMD-based algorithm with proven convergence, and demonstrates its effectiveness through an illustrative example.

Contribution

It introduces a new AIMD-like scheduling algorithm for optimal resource allocation with over-scheduling, including convergence analysis and tuning methods.

Findings

Convergence of the AIMD-like scheduling scheme is proven.

Optimal tuning methods for the AIMD algorithm are proposed.

The approach is validated through an illustrative example.

Abstract

This paper studies optimal scheduling and resource allocation under allowable over-scheduling. Formulating an optimisation problem where over-scheduling is embedded, we derive an optimal solution that can be implemented by means of a new additive increase multiplicative decrease (AIMD) algorithm. After describing the AIMD-like scheduling mechanism as a switching system, we show convergence of the scheme, based on the joint spectral radius of symmetric matrices, and propose two methods for fitting an optimal AIMD tuning to the optimal solution derived. Finally, we demonstrate the overall optimal design strategy via an illustrative example.