In recent years, soft computing techniques have emerged as a successful tool to understand and analyze the collective behavior of service- oriented computing software. Algorithms and mechanisms of self- organization of complex natural systems have been used to solve problems, particularly in complex systems, which are adaptive, ever- evolving, and distributed in nature across the globe. What fits more perfectly into this scenario other than the rapidly developing era of Fog, IoT, and Edge computing environment? Service- oriented computing can be enhanced with soft computing techniques embedded inside the Cloud, Fog, and IoT systems. Soft Computing Principles and Integration for Real-Time Service-Oriented Computing explores soft computing techniques that have wide application in interdisciplinary areas. These soft computing techniques provide an optimal solution to the optimization problem using single or multiple objectives.The book focuses on basic design principles and analysis of soft computing techniques. It discusses how soft computing techniques can be used to improve quality-of-service in serviceoriented architectures. The book also covers applications and integration of soft computing techniques with a service-oriented computing paradigm. Highlights of the book include: Soft computing also collaborates with various intelligent techniques used. (1) neural networks (NNs); (2) fuzzy logic; (3) genetic algorithm; (4) decision tree; (5) case base reasoning; (6) Probabilistic Reasoning (PR); and (7) Evolutionary Computation (EC) and other techniques of soft computing.