Dynamic workload balancing in decentralized edge systems: A marginal cost approach

IF 6.2 2区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-10-01 DOI:10.1016/j.future.2025.108167

Emanuele Carlini , Patrizio Dazzi , Luca Ferrucci , Jacopo Massa , Matteo Mordacchini

引用次数: 0

Abstract

The rise of edge computing poses resource management issues, especially in decentralized systems where scalability and responsiveness are crucial. This paper introduces a cost-driven framework for collaborative resource management using the marginal computing cost per user. It applies the economic principle of marginal cost to assess edge data centers’ (EDCs) ability to support more users, enabling efficient resource allocation. Simulations with PureEdgeSim and real-world data such as Alibaba Trace demonstrate substantial enhancements in resource use, latency, and active instance reduction, maintaining scalability and adaptability with high user demands.

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分散边缘系统中的动态工作负载平衡：边际成本方法

边缘计算的兴起带来了资源管理问题，特别是在可扩展性和响应性至关重要的分散系统中。本文介绍了一种基于用户边际计算成本的协同资源管理成本驱动框架。它应用边际成本的经济学原理来评估边缘数据中心（edc）支持更多用户的能力，从而实现有效的资源分配。PureEdgeSim和实际数据（如Alibaba Trace）的模拟显示，在资源使用、延迟和主动实例减少方面有了实质性的增强，在高用户需求下保持了可扩展性和适应性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Future Generation Computer Systems-The International Journal of Escience 工程技术-计算机：理论方法

CiteScore

19.90

自引率

2.70%

发文量

376

审稿时长

10.6 months

期刊介绍： Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.