IoT Software Engineering: Balancing Trade-offs

Abstract

This paper presents a critical analysis of software engineering for Internet of Things (IoT) systems, moving beyond a descriptive survey to examine the inherent  trade-offs  between key non-functional requirements such as security, performance, and resource efficiency. Through a structured review of recent literature, we identify that prevailing solutions like edge computing, AI, and blockchain are not silver bullets but introduce new design complexities. Our analysis reveals that the core challenge in IoT software engineering is managing the tension between decentralized intelligence and centralized control, between robust security and system responsiveness, and between advanced functionality and energy constraints. We synthesize these findings into a framework for evaluating design choices and provide targeted recommendations for researchers and practitioners. The paper concludes that the future evolution of IoT systems depends on developing adaptive software architectures capable of dynamically balancing these critical trade-offs, with emerging paradigms like AI-driven orchestration and post-quantum cryptography poised to reshape the landscape.