Dependency-Aware Dynamic Priority Scheduling for Online Multi-DAG Task Offloading in Mobile Edge Computing

doi:10.1109/JIOT.2025.3639051

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Dependency-Aware Dynamic Priority Scheduling for Online Multi-DAG Task Offloading in Mobile Edge Computing

2026-01-27

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DOI：10.1109/JIOT.2025.3639051

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Abstract

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The Internet of Things (IoT) revolution has led to unprecedented data generation, necessitating a shift from traditional centralized computing to more decentralized approaches. To address the challenges of data processing closer to the source, the paradigm of mobile edge computing (MEC) has emerged. It facilitates task offloading to nearby edge servers, thereby reducing delay and enhancing privacy. However, limited computation resources at the edge necessitate intelligent resource allocation through effective scheduling to maintain quality of service (QoS). Typically, a task comprises multiple subtasks with inherent dependencies, some of which are locally dependent and unsuitable for offloading. In subtask scheduling, one must account for both intersubtask and local dependencies, deploying different subtask types to near-optimal computing devices, whether edge servers or user equipments (UEs). This requirement presents significant challenges to scheduling strategies. Furthermore, since task offloading requests are inherently online, without prior task information before their arrival, improper scheduling can result in resource wastage and increased delays. To tackle these challenges, we formulate the online multi-DAG task scheduling with dependency awareness (OMSD) problem within a directed acyclic graph-based MEC (DAG-MEC) framework. This problem is modeled as an integer linear programming (ILP) problem and proven to be NP-hard. We propose a dynamic priority list scheduling (DPLS) algorithm to address this problem effectively. Our algorithm strategically determines subtask execution order by evaluating upward and downward ranks, task volume, and contention levels. Simulation results demonstrate that DPLS significantly outperforms existing benchmark algorithms regarding mean task completion time, server load balance, and maximum task completion time, offering a robust solution to the OMSD challenge in MEC environments.

Keywords:

Dynamic priority

intersubtask dependencies

local dependencies

mobile edge computing (MEC)

task scheduling