Delay Optimization in a Simple Offloading System: Extended Version

TL;DR

This paper analyzes a sequential offloading system with two service modes, deriving optimal policies for job assignment and resource partitioning to minimize delay, revealing a load-dependent switch in optimal routing strategy.

Contribution

It introduces a novel delay optimization framework for a two-mode offloading system, including a closed-form delay expression and a load-dependent assignment policy structure.

Findings

Optimal delay policy switches from single-mode to mixed-mode at a critical load.

Closed-form expression for delay under any job assignment strategy.

Characterization of the system's stability and throughput-maximizing service modes.

Abstract

We consider a computation offloading system where jobs are processed sequentially at a local server followed by a higher-capacity cloud server. The system offers two service modes, differing in how the processing is split between the servers. Our goal is to design an optimal policy for assigning jobs to service modes and partitioning server resources in order to minimize delay. We begin by characterizing the system's stability region and establishing design principles for service modes that maximize throughput. For any given job assignment strategy, we derive the optimal resource partitioning and present a closed-form expression for the resulting delay. Moreover, we establish that the delay-optimal assignment policy exhibits a distinct breakaway structure: at low system loads, it is optimal to route all jobs through a single service mode, whereas beyond a critical load threshold, jobs must be assigned across both modes. We conclude by validating these theoretical insights through numerical evaluation.