Authors: Suryansh Malhotra
Abstract: As the Internet of Things (IoT) evolves from isolated deployments into massive, city-scale and even nation-scale wireless infrastructures, the limitations of traditional engineering methodologies are becoming increasingly evident. Classical approaches largely focused on device-level optimization, protocol efficiency, or incremental network scaling struggle to address the nonlinear interactions, emergent behaviors, and cascading failures that arise when millions of heterogeneous devices operate within shared physical, computational, and regulatory environments. In this context, the need for Holistic Systems Engineering Models has become paramount. Holistic systems engineering reframes IoT not as a collection of independent nodes, but as a tightly coupled cyber-physical ecosystem. Wireless communication, sensing, actuation, computation, and human interaction are treated as co-evolving layers rather than separable design domains. This shift enables architects to reason about systemic properties such as resilience, adaptability, sustainability, and trust properties that cannot be fully captured through component-level analysis alone. A central enabler of this transformation is the adoption of Model-Based Systems Engineering (MBSE). MBSE replaces document-centric workflows with formalized, executable models that span the entire system lifecycle. Using languages such as SysML, engineers can explicitly represent structural relationships, behavioral flows, constraints, and requirements across physical devices, wireless links, data pipelines, and control logic. These models support traceability from high-level policy objectives such as latency guarantees or energy budgets—down to radio parameters and actuator timing, allowing design decisions to be evaluated in a system-wide context.
DOI: https://doi.org/10.5281/zenodo.18229606
