2025· International Journal of Emerging Trends in Multidisciplinary Research· Vol 8, pp. 01-18· 0 citations
TL;DR
This paper highlights key challenges, including interoperability, security, heterogeneous resource management, and sustainable computing, while demonstrating the potential of Edge–Cloud collaboration to improve computational efficiency, response time, energy efficiency, scalability, and privacy for next-generation smart applications.
Abstract
The rapid growth of IoT, 5G, AI, and cyber-physical systems has accelerated the development of smart applications that require low-latency, reliable, and intelligent computing. Traditional cloud computing faces challenges in meeting these demands due to latency, bandwidth, and privacy limitations. Intelligent Edge–Cloud collaboration addresses these issues by combining edge computing with cloud resources for efficient workload distribution, AI-driven resource management, and adaptive service orchestration. This paper reviews recent advances in collaborative architectures, distributed AI, intelligent orchestration, and resource optimization. It also highlights key challenges, including interoperability, security, heterogeneous resource management, and sustainable computing, while demonstrating the potential of Edge–Cloud collaboration to improve computational efficiency, response time, energy efficiency, scalability, and privacy for next-generation smart applications.
The study concludes that intelligent edge computing architectures will play a vital role in supporting future real-time applications and next-generation 6G-enabled digital ecosystems.
Alan Bundy· International Journal of Mod...· 0 citations
This review examines emerging trends in Artificial Intelligence (AI)-driven resource management within this continuum, with a focus on three directions: the transition from centralized to distributed and collaborative intelligence, cross-domain adaptation and knowledge transfer for heterogeneous IoT applications, and t...
Zhi-Yu Wang, Nilotpal Kapri, L. Bittencourt et al.· Frontiers in The Internet of...· 1 citation
This paper presented an Intelligent Edge Computing Framework for Secure, Low-Latency, and Energy-Efficient Smart Devices that integrates edge intelligence, adaptive task scheduling, resource-aware computation, secure communication, and cloud-assisted services to address the limitations of conventional cloud-centric arc...
Kolipaka Vinay, Valusa Venkat Sai Kumar, D. A. Kumar· International Journal of Sci...· 0 citations
This review explores the recent approaches of the state of the art focused on service orchestration in IoT edge-cloud environments, concentrating on architectures and methodologies that enable resource allocation and service management.
An AI-based context-aware IoT that is based on the edge and cloud computing to simplify real-time campus operations, enhance the utilization of the available resources, and provide intelligent decision-making is proposed.
Abhijeet Kaiwade, Neeta Bendre· Proceedings of the 1st Inter...· 0 citations
This paper introduced an Intelligent Portable Edge – Cloud Computing Architecture (IPECA) that combines the portable computing hardware, AI-based workload prediction, adaptive resource optimization, container-based virtualization and secure edge-cloud collaboration into a single computing architecture.
Pradeep Kachakayala, Akshith Kachakayala· International Journal for Re...· 0 citations
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