Internet of Things最新文献_第8页

Blockchain-assisted attribute-based multi-keyword search for dynamic encrypted data in cloud-edge-IoT 云边缘物联网中基于属性的区块链辅助多关键字动态加密数据搜索

IF 7.6 3区计算机科学

Internet of Things Pub Date : 2026-03-01 Epub Date: 2025-12-06 DOI: 10.1016/j.iot.2025.101838

Hanlei Cheng , Sio-Long Lo , Jing Lu

{"title":"Blockchain-assisted attribute-based multi-keyword search for dynamic encrypted data in cloud-edge-IoT","authors":"Hanlei Cheng , Sio-Long Lo , Jing Lu","doi":"10.1016/j.iot.2025.101838","DOIUrl":"10.1016/j.iot.2025.101838","url":null,"abstract":"<div><div>Keyword search is a fundamental technique for retrieving data outsourced to the cloud. Although encryption preserves data confidentiality, existing searchable encryption schemes often fail to efficiently support dynamic authorization and flexible retrieval. To address these limitations, we propose <span><math><mi>BAMKS</mi></math></span>, a blockchain-assisted attribute-based multi-keyword search scheme that supports secure and efficient search over version-aware encrypted data. In <span><math><mi>BAMKS</mi></math></span>, multiple data owners collaboratively generate version-bound access tokens that grant authorized users decryption privileges over evolving data. The scheme further enables conjunctive keyword search with updatable indexes. To ensure the integrity of search results, users can verify their correctness using an aggregated Schnorr-based non-interactive zero-knowledge proof, which is validated by smart contracts. In addition, <span><math><mi>BAMKS</mi></math></span> provides efficient attribute and user revocation without re-encrypting the stored ciphertexts, and supports user traceability for identifying malicious users from leaked keys. We formally prove that <span><math><mi>BAMKS</mi></math></span> achieves security against chosen-plaintext attacks (IND-CPA) and chosen-keyword attacks (IND-CKA) under the Decisional Bilinear Diffie-Hellman (DBDH) assumption. Performance evaluations show that the scheme achieves lightweight decryption and efficient multi-keyword search, thereby reducing client-side computation and making it suitable for resource-constrained IoT environments. These features demonstrate the practicality of <span><math><mi>BAMKS</mi></math></span> for distributed cloud-edge-IoT storage applications.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"36 ","pages":"Article 101838"},"PeriodicalIF":7.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

End-To-end response-time analysis of DDS-based real-time applications 基于dds的实时应用的端到端响应时间分析

IF 7.6 3区计算机科学

Internet of Things Pub Date : 2026-03-01 Epub Date: 2025-12-17 DOI: 10.1016/j.iot.2025.101853

Gerlando Sciangula , Daniel Casini , Alessandro Biondi , Claudio Scordino , Marco Di Natale

{"title":"End-To-end response-time analysis of DDS-based real-time applications","authors":"Gerlando Sciangula , Daniel Casini , Alessandro Biondi , Claudio Scordino , Marco Di Natale","doi":"10.1016/j.iot.2025.101853","DOIUrl":"10.1016/j.iot.2025.101853","url":null,"abstract":"<div><div>The Data Distribution Service (DDS) is established as a middleware communication standard based on a data-centric publish-subscribe protocol. This standard is pivotal for applications in autonomous driving, smart cities, and Industry 4.0, facilitating communication among diverse devices across the IoT-to-Edge-to-Cloud continuum. Particularly in the automotive industry, modern autonomous systems, built on top of frameworks like ROS 2 and Autoware, heavily rely on DDS for real-time data exchange across distributed software components. The DDS is however typically implemented with a multithreaded software structure and leverages middleware-specific policies for message dispatching, posing considerable challenges in guaranteeing timing constraints. This paper fills significant gaps in the current understanding of DDS’s real-time performance. We introduce a comprehensive DDS model that includes both synchronous and asynchronous communication under various dispatching policies. The model is then used to derive a holistic response-time analysis capable of bounding the end-to-end latency of DDS-enabled real-time applications. Furthermore, we integrate our analysis with a state-of-the-art executor-based analysis for ROS2-based systems. The effectiveness of our approach is validated through experiments on a real platform using FastDDS, a popular DDS implementation, and a modern automotive testbed taken from the WATERS 2019 Industrial Challenge by Bosch. Finally, our analysis method is evaluated with both a ROS2 case-study application and the Autoware reference system, a realistic testbed from the open-source Autoware.Auto framework for autonomous driving.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"36 ","pages":"Article 101853"},"PeriodicalIF":7.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analyzing the influence of users, devices, and search engines on viral spread in the social internet of things 分析社交物联网中用户、设备、搜索引擎对病毒式传播的影响

IF 7.6 3区计算机科学

Internet of Things Pub Date : 2026-01-01 Epub Date: 2025-12-03 DOI: 10.1016/j.iot.2025.101842

Chenquan Gan, Hongming Chen, Yi Qian, Liang Tian, Qingyi Zhu, Deepak Kumar Jain, Vitomir Štruc

{"title":"Analyzing the influence of users, devices, and search engines on viral spread in the social internet of things","authors":"Chenquan Gan, Hongming Chen, Yi Qian, Liang Tian, Qingyi Zhu, Deepak Kumar Jain, Vitomir Štruc","doi":"10.1016/j.iot.2025.101842","DOIUrl":"10.1016/j.iot.2025.101842","url":null,"abstract":"<div><div>The Social Internet of Things (SIoT) seamlessly integrates the Internet of Things (IoT) with social networks, intensifying the interconnections among objects, humans, and their interactions. While SIoT facilitates rapid information access and sharing through search engines, it also increases the risk of computer virus propagation. It is, therefore, critical to understand how viruses propagate in SIoT networks and which factors contribute the most to viral spread. While such understanding is of paramount importance, comprehensive studies on this topic are still limited in the literature. To address this gap, we study in this paper the long-term behavior of viral spread in SIoT, examining the roles of users, devices, and search engines. Specifically, we propose a novel dynamical virus propagation model that accounts for key factors, such as user awareness, device security levels, search engines, and external storage media. In comparison to competing solutions, the proposed model offers a unique perspective on viral spread in SIoT by focusing on multiple influential factors, their interactions, while also considering the inherent characteristics of the SIoT framework. A comprehensive theoretical analysis of the model is conducted to identify patterns and the key aspects of virus propagation in SIoT. To further validate the findings, a virus propagation algorithm is also designed, and multiple simulations are conducted on two real network datasets (Facebook and P2P), demonstrating the validity of the theoretical findings.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"35 ","pages":"Article 101842"},"PeriodicalIF":7.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Proactive context aware task offloading in digital twin driven federated IoT systems with large language models 具有大型语言模型的数字孪生驱动的联邦物联网系统中的主动上下文感知任务卸载

IF 7.6 3区计算机科学

Internet of Things Pub Date : 2026-01-01 Epub Date: 2025-11-17 DOI: 10.1016/j.iot.2025.101826

Klea Elmazi , Donald Elmazi , Jonatan Lerga

{"title":"Proactive context aware task offloading in digital twin driven federated IoT systems with large language models","authors":"Klea Elmazi , Donald Elmazi , Jonatan Lerga","doi":"10.1016/j.iot.2025.101826","DOIUrl":"10.1016/j.iot.2025.101826","url":null,"abstract":"<div><div>This study considers the combination of Digital Twins (DT), Federated Learning (FL), and computation offloading to establish a context-aware framework for effective resource management in IoT networks. Although DT models can predict battery levels, CPU usage, and network delays to aid reinforcement learning (RL) agents, earlier RL-based controllers require significant training and are slow to adapt to changes. To overcome this issue, we propose a Large Language Model (LLM)-assisted offloading method that transforms real-time DT predictions and selected historical Explainable DT with Federated Multi-Agent RL (MARL) examples into structured natural-language prompts. Through in-context learning, LLM deduces offloading tactics without retraining, while FL aligns global convergence metrics to optimize the balance between inference accuracy and energy efficiency. Simulation studies conducted for baseline and unstable wireless network scenarios reveal that the LLM controller persistently maintains near-optimal latency and reduces energy use. In a baseline scenario with <span><math><mrow><mi>N</mi><mo>=</mo><mn>36</mn></mrow></math></span> devices, the LLM achieves an average latency of 252 ms, which is only 5 % higher than edge offloading, while cutting energy consumption by around 20 %. Under unstable wireless conditions, it achieves an average latency of 276 ms with energy use of 0.122 J, as opposed to 0.154 J for edge offloading. These findings validate that LLM-based decision making facilitates scalable, adaptive, and energy-efficient task scheduling, presenting a viable alternative to RL controllers in DT-enabled federated IoT systems.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"35 ","pages":"Article 101826"},"PeriodicalIF":7.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145570538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy-efficient cryptographic optimization for narrowband IoT security: Integrating blockchain and EP-CuMAC with ECM-SHA256 窄带物联网安全节能加密优化：区块链和EP-CuMAC与ECM-SHA256集成

IF 7.6 3区计算机科学

Internet of Things Pub Date : 2026-01-01 Epub Date: 2025-11-18 DOI: 10.1016/j.iot.2025.101828

Hafizullah Kakar , Vamshi S. Mohan , Swapnoneel Roy , Ayan Dutta , O. Patrick Kreidl , Ladislau Bölöni , Sriram Sankaran

{"title":"Energy-efficient cryptographic optimization for narrowband IoT security: Integrating blockchain and EP-CuMAC with ECM-SHA256","authors":"Hafizullah Kakar , Vamshi S. Mohan , Swapnoneel Roy , Ayan Dutta , O. Patrick Kreidl , Ladislau Bölöni , Sriram Sankaran","doi":"10.1016/j.iot.2025.101828","DOIUrl":"10.1016/j.iot.2025.101828","url":null,"abstract":"<div><div>Narrowband Internet of Things (NB-IoT) continues to expand but faces challenges of cryptographic overhead and energy consumption. Security frameworks such as blockchain and Energy-Performance Cumulative Message Authentication Codes (EP-CuMAC) rely heavily on SHA-256, which is not optimized for energy-limited devices. This work unifies two complementary approaches-a hybrid blockchain-based NB-IoT framework and an EP-CuMAC-based framework-by engineering their cryptographic core with an Energy Complexity Model-optimized SHA-256 (ECM-SHA256). ECM applies parallel memory-bank mapping and block-level access optimization to reduce redundant power usage while preserving algorithmic integrity. Experimental evaluation on identical Intel DDR3 systems using pyRAPL shows energy savings of 2–13 % across blockchain (Unique ID Generation, Device Join, Transactions) and EP-CuMAC modules (Feedback, Prediction, Verification, Retransmission). The optimization leverages the Energy Complexity Model’s parallel memory-bank mapping of SHA-256, implemented on identical Intel DDR3 systems using pyRAPL for repeatable measurements. The results position ECM-SHA256 as a generalizable cryptographic optimization strategy for secure and sustainable NB-IoT deployments.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"35 ","pages":"Article 101828"},"PeriodicalIF":7.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145570536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intelligent latency optimization in hyperledger fabric for seamless metaverse integration 超级账本结构中的智能延迟优化，实现无缝的元数据集成

IF 7.6 3区计算机科学

Internet of Things Pub Date : 2026-01-01 Epub Date: 2025-12-02 DOI: 10.1016/j.iot.2025.101835

Jummai Enare Abang , Rabab Al-Zaidi , Haifa Takruri , Mohammed Al-Khalidi

{"title":"Intelligent latency optimization in hyperledger fabric for seamless metaverse integration","authors":"Jummai Enare Abang , Rabab Al-Zaidi , Haifa Takruri , Mohammed Al-Khalidi","doi":"10.1016/j.iot.2025.101835","DOIUrl":"10.1016/j.iot.2025.101835","url":null,"abstract":"<div><div>Blockchain technology underpins secure, decentralized digital ecosystems and supports applications ranging from finance and supply chains to the emerging Metaverse. However, latency remains a key challenge, particularly for real time applications. Hyperledger Fabric (HLF), a leading enterprise blockchain, suffers from transaction delays due to its endorsement policies, which enhance security but introduce computational and communication overhead. This paper addresses the latency challenge in HLF by proposing a reinforcement learning (RL)-based dynamic endorsement mechanism. The model learns from past transaction patterns and system states to predict the optimal number of endorsers needed for each transaction. By dynamically adjusting the “AND” endorsement policy based on whether the observed latency meets a defined threshold, the approach balances security with performance, which is critical for low-latency applications like the Metaverse. Experimental evaluations across diverse HLF configurations, using both mathematical and empirical methods, show that the proposed RL model reduces transaction latency by up to 37.54 % compared to static policies and outperforms other RL models (SARSA, Dueling DQN, Double Q-learning) by 6.81 % to 16.04 %. Results confirm the model’s adaptability and superior performance, particularly in single-client environments. In terms of throughput, the proposed RL model consistently surpasses the static configuration across all workloads, demonstrating strong adaptability to varying transaction loads with the most notable improvement of 27.61 % under single-client conditions, underscoring the model’s capability to optimise light workloads. This research contributes to the development of scalable, responsive, and secure blockchain infrastructures, offering an intelligent solution for real-time latency optimisation in digital applications such as the Metaverse.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"35 ","pages":"Article 101835"},"PeriodicalIF":7.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing beamforming performance in 6G-V2X base stations using meta-deep reinforcement Q-learning 利用元深度强化q学习增强6G-V2X基站的波束成形性能

IF 7.6 3区计算机科学

Internet of Things Pub Date : 2026-01-01 Epub Date: 2025-11-14 DOI: 10.1016/j.iot.2025.101825

Ali Belgacem , Abbas Bradai

引用次数: 0

HealthCare 5.0: An industry 5.0 perspective for next-generation medical systems with synergistic integration of IoT, AI, and 6G 医疗保健5.0：具有物联网、人工智能和6G协同集成的下一代医疗系统的行业5.0视角

IF 7.6 3区计算机科学

Internet of Things Pub Date : 2026-01-01 Epub Date: 2025-11-07 DOI: 10.1016/j.iot.2025.101815

Abolfazl Younesi , Elyas Oustad , Mohsen Ansari , Thomas Fahringer , Rajkumar Buyya

{"title":"HealthCare 5.0: An industry 5.0 perspective for next-generation medical systems with synergistic integration of IoT, AI, and 6G","authors":"Abolfazl Younesi , Elyas Oustad , Mohsen Ansari , Thomas Fahringer , Rajkumar Buyya","doi":"10.1016/j.iot.2025.101815","DOIUrl":"10.1016/j.iot.2025.101815","url":null,"abstract":"<div><div>The rising demand for personalized, reliable, and sustainable health services requires a significant shift beyond current technology barriers. This paper introduces HealthCare 5.0, a transformative vision for next-generation medical systems. It brings the Internet of Things (IoT), Artificial Intelligence (AI), and 6G communications together under the human-centered, sustainable, and resilient principles of Industry 5.0. HealthCare 5.0 showcases the convergence of IoT for continuous health monitoring, AI for intelligent reasoning, and 6G for dependable, low-latency connectivity. These elements work together to provide real-time, personalized, and proactive care. The analysis looks into how this collaboration supports advancements like remote diagnostics, digital twins, federated learning, explainable AI (XAI), and medical large language models (MedLLMs). It also addresses challenges in interoperability, energy efficiency, data privacy, and ethical AI. The framework stresses the importance of digital twins, ambient sensing, and wearable devices in facilitating predictive and patient-centered care. Despite progress, there are still gaps in standardization, clinician adoption, and the ethical use of these technologies. To overcome these issues, we propose a complete approach that combines IoT, AI, and 6G based on Industry 5.0 principles. This closed-loop model of “sense, transmit, reason, act” is backed by key performance indicators, real-world case studies, and a roadmap for compliance and regulatory support. By merging innovation with human values and systemic resilience, HealthCare 5.0 offers a forward-thinking plan for smart, safe, and fair healthcare systems.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"35 ","pages":"Article 101815"},"PeriodicalIF":7.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145500386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bluetooth 5 power consumption for an opportunistic edge computing system based on low-power IoT devices 基于低功耗物联网设备的机会性边缘计算系统的蓝牙5功耗

IF 7.6 3区计算机科学

Internet of Things Pub Date : 2026-01-01 Epub Date: 2025-11-26 DOI: 10.1016/j.iot.2025.101834

Ángel Niebla-Montero , Iván Froiz-Míguez , Paula Fraga-Lamas , Tiago M. Fernández-Caramés

{"title":"Bluetooth 5 power consumption for an opportunistic edge computing system based on low-power IoT devices","authors":"Ángel Niebla-Montero , Iván Froiz-Míguez , Paula Fraga-Lamas , Tiago M. Fernández-Caramés","doi":"10.1016/j.iot.2025.101834","DOIUrl":"10.1016/j.iot.2025.101834","url":null,"abstract":"<div><div>The rapid expansion of the Internet of Things (IoT) has created a growing demand for efficient and reliable wireless communication, particularly in environments with limited network coverage. Opportunistic Edge Computing (OEC) has emerged as a viable solution by leveraging smart IoT gateways to provide Edge Computing services, route communications and store data in a distributed way, thus reducing reliance on Cloud infrastructure. This article explores the potential of Bluetooth 5 as a low-power communications protocol for OEC systems based on Single Board Computers (SBCs). For such a purpose, a novel OEC architecture and stack protocol are proposed to integrate a version of Bluetooth 5 adapted to enable opportunistic data exchanges in resource-constrained IoT environments. To evaluate the proposed solution, a testbed was built and experiments were carried out to measure the system latency and power consumption. The obtained results demonstrate the differences between using Bluetooth Legacy and LE Coded modulations in four different OEC scenarios. The findings show the Bluetooth 5 potential for enhancing decentralized IoT networks while maintaining low power consumption, making it a suitable choice for developing OEC IoT applications. Thus, this article provides useful guidelines for selecting the most appropriate Bluetooth 5 mode for the researchers and developers of the next-generation OEC solutions.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"35 ","pages":"Article 101834"},"PeriodicalIF":7.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving power consumption in IoT devices through neural network-based decision making 通过基于神经网络的决策改善物联网设备的功耗

IF 7.6 3区计算机科学

Internet of Things Pub Date : 2026-01-01 Epub Date: 2025-11-19 DOI: 10.1016/j.iot.2025.101827

Vladimir G. Da Silva , Nelson S. Rosa , Fernando Aires , Wellison R.M. Santos

{"title":"Improving power consumption in IoT devices through neural network-based decision making","authors":"Vladimir G. Da Silva , Nelson S. Rosa , Fernando Aires , Wellison R.M. Santos","doi":"10.1016/j.iot.2025.101827","DOIUrl":"10.1016/j.iot.2025.101827","url":null,"abstract":"<div><div>Advances in the Internet of Things (IoT) have led to several challenges across domains, creating opportunities for new solutions. The large volume of data and high processing demands of IoT applications, typically handled by cloud providers, make this approach costly regarding storage, computation, and latency. This fact has led to the emergence of the fog computing paradigm that enables the integrated use of edge and cloud resources. In this new scenario, one of the main challenges is managing containerised IoT applications that may migrate from fog nodes (IoT Devices) to the cloud and vice versa. This management is needed to preserve system performance and user experience while considering cloud resource costs. The container migration becomes especially critical for battery-powered devices, whose energy autonomy is a significant concern. Existing solutions do not consider power consumption and the cost of fog-cloud settings in the migration process. This paper proposes <span>IRAS-IoT</span> (Intelligent Replacement as a Service for IoT), a solution for autonomously migrating containers between fog nodes and the cloud. Based on MAPE-K, <span>IRAS-IoT</span> adopts a Multilayer Perceptron (MLP) neural network model to decide on migrating containers and optimising workload distribution according to devices’ power consumption. Regarding cost optimisation, in scenarios where fog nodes become overloaded, the solution may also allocate containers to a cloud provider, selecting the most cost-effective option. Experimental results show that IRAS-IoT reduces energy consumption by up to 18% and extends battery life by 34%, and lowers cloud operational costs compared to the baseline scenario.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"35 ","pages":"Article 101827"},"PeriodicalIF":7.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145570535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0