文献类型：期刊文献

英文题名：Queue stability and dynamic throughput maximization in multi-agent heterogeneous wireless networks

作者：Yang, Ting[1];Sun, Jiabao[1];Mohajer, Amin[2]

机构：[1]Shaoxing Univ, Sch Informat & Elect Engn, Yuanpei Coll, Shaoxing 312000, Zhejiang, Peoples R China;[2]ICT Res Inst ITRC, Dept Commun Technol, Tehran, Iran

年份：2024

外文期刊名：WIRELESS NETWORKS

收录：SCI-EXPANDED(收录号：WOS:001201484900001)、、EI(收录号：20241615928565)、Scopus(收录号：2-s2.0-85190390054)、WOS

语种：英文

外文关键词：Maximum-weight scheduling; Queue stability; Distributed resource allocation; IIoT; Throughput utility maximization

外文摘要：The Industrial Internet of Things (IIoT) envisions enhanced surveillance and control for industrial applications through diverse IoT devices. However, the increasing heterogeneity of deployed end devices poses challenges to current practices, hampering overall performance as device numbers escalate. To tackle this issue, we introduce an innovative distributed power control algorithm leveraging the wireless channel's nature to approximate the centralized maximum-weight scheduling algorithm. Employing ubiquitous multi-protocol mobile devices as intermediaries, we propose a concurrent dual-hop/multi-hop backhauling strategy, improving interoperability and facilitating data relay, translation, and forwarding from end IoT devices. Our focus is directed towards addressing large-scale network stability and queue management challenges. We formulate a long-term time-averaged optimization problem, incorporating considerations of end-to-end rate control, routing, link scheduling, and resource allocation to guarantee essential network-wide throughput. Furthermore, we present a real-time decomposition-based approximation algorithm that ensures adaptive resource allocation, queue stability, and meeting Quality of Service (QoS) constraints with the highest energy efficiency. Comprehensive numerical results verify significant energy efficiency improvements across diverse traffic models, maintaining throughput requirements for both uniform and hotspot User Equipment (UE) distribution patterns. This work offers a comprehensive solution to enhance IIoT performance and address evolving challenges in industrial applications.