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.
Abstract
The advent of 6G networks and the rapid growth of Internet of Things (IoT) are revolutionizing the telecommunication sector, integrating edge-cloud systems with vast amounts of data from IoT and AI techniques. These advancements make these systems essential in managing and delivering a multitude of services, offered by smart cities and industrial domains, being just a few among the many possible application scenarios. Specifically, this shift introduces complexities in orchestrating services and managing available resources while addressing challenges such as reducing latency, growing bandwidth, ensuring trust, and integrating different technologies. In this sense, 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. Furthermore, it examines platforms for orchestration development, highlighting their characteristics and contributions. Finally, emerging concerns such as network topology and trust, which previous surveys have often overlooked, are discussed together with the most relevant research directions.
A comprehensive review of edge computing as a modern trend in information technology, including the convergence of edge computing with artificial intelligence (Edge AI), 6G networks, digital twins, and serverless edge architectures is presented.
Awiti Gideon Appiah, Dr. Lazarus Kwao, Benjamin Opoku Atuahene· International Journal of Cre...· 0 citations
The results of the analysis indicate that 6G can contribute to a substantial improvement of IoT performance in smart cities, healthcare, industrial automation and control applications (manufacturing science), autonomous transportation and precision agriculture.
Md Asaduzaman, Ferdous Hossain, T. Geok· International Journal of Ele...· 0 citations
A lightweight yet comprehensive open-source smart city platform architecture that serves as a bridge between theoretical research and practical deployment, reducing barriers to entry and accelerating the development of smarter, more sustainable urban systems is proposed.
Nikolaos Monios, P. Papageorgas, Dimitrios D. Piromalis et al.· Electronics· 0 citations
The rapid proliferation of IoT devices and ecosystems creates significant challenges in managing increasing data traffic and service requests while maintaining system performance [1]– [3]. In oneM2M-based IoT systems, overloaded Common Service Entities (CSEs) can become bottlenecks, leading to resource saturation, higher latency, and request loss [4]. To address these challenges, this paper proposes IoTScal-2CoM-ALO, an adaptive load orchestration framework that introduces a two-level collaboration model (2CoM) enabling distributed CSEs to cooperate within and across domains. The framework incorporates an Adaptive Load Orchestration (ALO) mechanism that continuously monitors key performance indicators, including CPU utilization, memory consumption, round-trip time (RTT), and packet loss, to detect overload conditions and dynamically redirect traffic to suitable neighboring CSEs. The proposed approach is evaluated in a simulated distributed oneM2M environment under heterogeneous traffic conditions. Experimental results demonstrate significant performance improvements compared with non-collaborative and static collaboration approaches, achieving up to 73% reduction in memory consumption, RTT peak reductions of up to 4750 ms, and success rate improvements of approximately 4.8%. These results highlight the effectiveness of IoTScal-2CoM-ALO in improving resource utilization and maintaining service continuity in scalable IoT systems.
S. Abourriche, A. Zyane, A. Ghammaz· International Conference on...· 0 citations
A comprehensive survey of current technologies in cloud infrastructure automation, including Infrastructure as Code (IaC), configuration management, continuous integration/continuous deployment (CI/CD), and containerization is provided.
Nimal Perera, Tharindu Jayasinghe· International Journal of Art...· 0 citations
The Internet of Things (IoT) systems generate vast amounts of data from numerous connected devices, posing significant challenges in terms of data processing, latency, and bandwidth utilization. Traditional cloud-based analytics systems face limitations, especially in real-time data processing. Edge computing, which brings computation closer to the data source, presents an ideal solution to overcome these challenges. This paper explores the design and implementation of edge computing pipelines for distributed analytics in IoT systems. It discusses the architecture of edge computing in IoT, the role of distributed analytics, and the flow of data through edge analytics pipelines. The paper also examines the benefits of edge computing, such as reduced latency, bandwidth efficiency, and enhanced real-time decision-making. Furthermore, we address the challenges in scaling, securing, and maintaining edge devices and propose various applications across smart cities, industrial IoT, healthcare, and agriculture. Finally, the paper highlights emerging trends and future directions for enhancing edge analytics capabilities in the ever-evolving IoT ecosystem.
Jose Fernandez· International Journal of Dat...· 0 citations
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