"Innovative Roles of Operating Systems in Driving Emerging Technologies"

Abstract

Operating systems (OS) have undergone significant transformation from monolithic batch processors to smart, adaptive platforms enabling AI, IoT, edge, and quantum computing. This paper presents a comprehensive review of modern OS evolution and highlights innovations enabling real-time performance, modular design, and scalable deployment across emerging hardware platforms. Comparative analysis across experimental metrics, such as inference latency, response time, and energy efficiency, illustrates the OS’s strategic role in future computing architectures.

Objectives: This paper aims to:

• Examine OS architectural evolution in response to emerging technologies.


• Analyze performance across AI, IoT, Edge, and Quantum platforms.


• Propose best practices for scalable, modular, and intelligent OS design.

Methods: We selected representative OS from various domains including Android (AI), Zephyr (IoT), Ubuntu Core (Edge), and Qiskit OS (Quantum). Benchmarks were conducted on:

• AI inference latency using MobileNetV2 and EfficientNet-B0.


• RTOS round-trip time for sensor-actuator communication.


• Edge OS throughput and energy efficiency.


• Quantum task scheduling latency and decoherence impact.

Results: The results were presented in four tables and six figures.AI Platforms: Fuchsia OS achieved 27% lower inference latency than Android and iOS [6].

• IoT Platforms: Zephyr recorded a 12 ms average round-trip response, outperforming RIOT and TinyOS [5].


• Edge OS: Ubuntu Core provided the highest throughput (200 msg/sec) with 88% efficiency [18].


• Quantum OS: Qiskit OS showed the lowest average latency (25 ms) and coherence loss (5%) among quantum environments [11].

Detailed results are in:

• Table 1: AI Inference Timings


• Table 2: IoT Event Round-Trip Times


• Table 3: Edge Throughput and Power Efficiency


• Table 4: Quantum OS Latency Metrics


• Figures 1–6: Supporting visual comparisons
  

  Conclusions: Results confirm that OS innovations must address domain-specific constraints. AI systems benefit from kernel-level acceleration layers [6], while IoT OS must remain minimal and deterministic [5]. Edge OS require scalable containerization with real-time scheduling, and quantum OS must support probabilistic execution while minimizing coherence loss [11]. A modular, layered OS structure with adaptive scheduling is the key recommendation for next-gen OS developers [2][12][17]..