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International Journal of Modern Computer Science and IT Innovations

Open Access Peer Review International
Open Access

Architecting Secure and Cost-Optimized Iot-Cloud Ecosystems: Integrating AI-Driven Intrusion Detection, Multi-Path Routing, And Intelligent Workload Scheduling in Distributed Systems

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Dr. Eleanor Whitfield 1 ,
4 Department of Computer Science, University of Edinburgh, United Kingdom

Abstract

The rapid convergence of Internet of Things (IoT) infrastructures with cloud-scale computing platforms has introduced unprecedented opportunities for automation, data intelligence, and distributed control, while simultaneously amplifying systemic vulnerabilities across network, computation, and application layers. This study develops a unified architectural framework that integrates IoT-based smart security systems, modified hashing techniques for secure device communication, AI-driven intrusion detection strategies, multi-path routing optimization algorithms, and intelligent workload placement mechanisms in hybrid cloud environments. Drawing upon foundational and contemporary works in IoT security, routing optimization, large-scale cluster management, and cloud scheduling systems-including Borg, Apollo, Fuxi, and intelligent hybrid cloud models-this research proposes a layered, security-aware, cost-optimized IoT-cloud ecosystem. The study synthesizes insights from door security IoT implementations (Tiwari & Waoo, 2024), cryptographic communication enhancements (Rao & Waoo, 2024), multi-path routing algorithms (Waoo & Sharma, 2014; Waoo, Sharma, & Jain, 2014), AI-driven network intrusion detection (Waoo, 2024), cloud cost analysis (Dubey & Tiwari, 2024), and intelligent workload placement in hybrid clouds (Hebbar & Maheshkar, 2025). Through detailed theoretical modeling and comparative systems analysis, the research demonstrates that security, performance, and cost efficiency must be co-optimized rather than treated as independent design goals. The findings reveal that integrating adaptive routing with AI-enhanced threat detection and cloud-aware workload orchestration significantly enhances resilience against distributed attacks, reduces latency in IoT communications, and optimizes resource allocation under fluctuating demand. The paper contributes a conceptual architecture that bridges edge devices, network routing, cloud cluster management, and hybrid cloud economics into a cohesive and scalable framework. The proposed approach addresses contemporary literature gaps by unifying security hardening, intelligent scheduling, and cost governance in distributed IoT-cloud systems.

Keywords

IoT security, AI-driven intrusion detection, multi-path routing

References

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