Decentralized Systems and Distributed Computing

16Artificial Intelligence in a Distributed System of the Future

Kadambri Agarwal^1*, Ojasw Khare¹, Aastha Sharma¹, Ayushi Prakash² and Abhishek Kumar Shukla¹

¹Department of CSE, ABES Engineering College, Ghaziabad, India

²Department of CSE, AKGEC, Ghaziabad, India

Abstract

The integration of artificial intelligence (AI) approaches with distributed systems has emerged as a game-changing paradigm, transforming how we build, administer, and optimize large-scale networks. This chapter emphasizes the significant influence of AI on distributed systems, highlighting how it improves productivity and scalability. Due to their capacity to manage massive volumes of data and provide services to a variety of users, distributed systems, such as cloud computing platforms, Internet of Things (IoT) networks, and edge computing infrastructures, have taken the place of central processing units in modern computing. However, the difficulties in managing distributed systems have created substantial problems that call for clever solutions. By offering automation, self-optimization, and adaptive decision-making capabilities, AI plays a crucial role in tackling these issues. Distributed systems may analyze large datasets in real time using machine learning algorithms, resulting in intelligent resource allocation, load balancing, and fault tolerance decisions. Additionally, security breaches and system failures are detected and mitigated with the use of AI-powered anomaly detection systems, assuring ...