Application and Prospect of Artificial Intelligence in Network Communication

Abstract

The rapid evolution of artificial intelligence (AI) is fundamentally reshaping the landscape of network communication. This paper, building upon the foundational work of scholars such as Han Jianru, provides a comprehensive exploration of the applications, impacts, and future prospects of AI in this critical field. We commence by elucidating the core principles of AI and machine learning (ML), detailing how key technologies—including deep neural networks (DNNs), natural language processing (NLP), and computer vision—are being leveraged to solve complex problems in communication networks. The paper subsequently offers a systematic analysis of specific application domains. These include automated network management and orchestration for self-healing and self-optimizing capabilities, intelligent routing algorithms for dynamic traffic engineering, AI-powered security frameworks for robust intrusion detection and threat mitigation, real-time quality optimization of multimedia communications, and intelligent analysis and filtering of content on social media platforms. The profound impact of AI is then critically examined, highlighting demonstrable improvements in network performance and operational efficiency, the enhancement of end-user experience through personalized services, and the creation of new avenues for business innovation. However, the integration of AI is not without significant challenges. This study also addresses critical limitations and risks, with a focused discussion on data privacy and security concerns arising from massive data collection, the ethical and moral dilemmas inherent in algorithmic decision-making (e.g., bias and transparency), and the practical technological hurdles related to computational complexity and system integration. Finally, the paper presents a forward-looking perspective on the future development of AI in network communication. We anticipate trends such as the maturation of explainable AI (XAI) for trustworthy network operations, the deep convergence of AI with next-generation networking architectures like 6G and intent-based networking, and the emergence of fully autonomous network ecosystems. This analysis concludes that the symbiotic integration of AI and network communication is an irreversible trend poised to drive the next wave of technological and economic growth, provided the associated challenges are proactively addressed.