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Reliability-Aware Personalized Deployment of Approximate Computation IoT Applications in Serverless Mobile Edge computing

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ieee TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND systems 2025年第2期44卷 430-443页

作者： Cao, Kun Chen, Mingsong Karnouskos, Stamatis Hu, Shiyan Jinan Univ Coll Informat Sci & Technol Guangzhou 510632 Peoples R China East China Normal Univ Engn Res Ctr Software Hardware Codesign Technol & Minist Educ Shanghai 200062 Peoples R China SAP D-69190 Walldorf Germany Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ England

Over the past few years, the integration of mobile edge computing (MEC) and serverless computing, known as serverless MEC (SMEC), has garnered considerable attention. Despite abundant existing works on SMEC exploration, there remains an unaddressed gap in guaranteeing dependable application outputs due to ignoring the threat of both soft and bit errors on SMEC infrastructures. Furthermore, existing works fall short of accommodating the personalized requirements and approximate computation of Internet of Things (IoT) applications, thereby resulting in holistic quality-of-service (QoS) degradation of SMEC systems typically provisioned by limited edge resources. In this article, we investigate the reliability-aware personalized deployment of approximate computation IoT applications for QoS maximization in SMEC environments. To this end, we propose a hybrid methodology composed of offline and online optimization phases. At the offline phase, a decomposition-based function placement method is devised to accomplish function-to-server mapping by integrating convex optimization, cross-entropy method, and incremental control techniques. At the online phase, a lightweight reinforcement learning scheme based on proximal policy optimization (PPO) is developed to handle the inherent dynamicity of IoT applications. We also build a simulation platform upon the real-world base station distribution in Shanghai Telecom and the practical cluster trace in the Alibaba open program. Evaluations demonstrate that our hybrid approach boosts the holistic QoS by 63.9% compared with the state-of-the-art peer algorithms.

关键词： Approximate computation personalized Internet of Things (IoT) deployment Reliability serverless mobile edge computing (SMEC) Approximate computation personalized Internet of Things (IoT) deployment reliability serverless mobile edge computing (SMEC)

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Design of Automated Container Layout and Resource Optimization Algorithm based on Cloud computing Technology

Design of Automated Container Layout and Resource Optimizati...

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2024 international conference on Mechatronics and intelligent Control, ICMIC 2024

作者： Zhang, Feng Shandong Province Light Industry Collective Enterprise Association Information Department Shandong Jinan China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

With the rapid development and widespread application of cloud computing, container technology has become a hot topic for enterprises and research institutions in recent years. This article proposes an automated container arrangement and resource optimization algorithm design based on cloud computing technology to address these issues. This algorithm can predict and adjust resources based on real-time and historical data of applications, ensuring efficient resource utilization and good application performance. The experimental results show that our optimization algorithm has improved by about 16% compared to the optimal adaptation strategy. Due to the more precise resource allocation of the algorithm in this article, the response time of the application has not been significantly affected. In the testing of system throughput, it can be found that our algorithm has improved throughput by about 15% compared to random strategies. Finally, energy consumption was tested and the results showed that our algorithm reduced energy consumption by approximately 28% due to higher resource utilization. These results demonstrate that our algorithm outperforms existing strategies in multiple key metrics. © 2025 SPIE.

关键词： Cloud platforms

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Design and Analysis of Optimized Power Internet of Things System Based on Edge computing

Design and Analysis of Optimized Power Internet of Things Sy...

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2024 international conference Optoelectronic Information and Optical Engineering, OIOE 2024

作者： Yu, Fei Rao, Wei Liu, Mingliu Li, Yiwen State Grid Hubei Electric Power Co. Ltd. China State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute China

ISBN: (数字)9781510688209

ISBN: (纸本)9781510688193

In the development of China's power Internet construction, in order to better meet the characteristics of network transportation, the key technology to the edge computing framework as the core has been highly valued by the power industry. Nowadays, the professional information systems of China power grid Co., Ltd. have problems such as information cannot be shared and the level of intelligent management and control is low, which requires the power industry to create a smart iot system with existing technical means. On the basis of understanding the current operation status of the power network system, this paper mainly studies the optimized power Internet of Things system architecture and application functions based on edge computing, and then discusses the application effects of relevant technical functions combined with practical cases, so as to prove the application advantages of edge computing framework in the current power Internet of Things system. © 2025 SPIE.

关键词： computing systems Internet of things Power grids Telecommunications Design Network security Engineering Computer security Industry Safety

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Novel Abnormal Data Mining and Detection Algorithm for intelligent systems 4

Novel Abnormal Data Mining and Detection Algorithm for Intel...

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4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Xu, Shaomei Fan, Yanling Lin, Bing Continuing Education Service Center Shandong Institute of Commerce and Technology Shandong Jinan250103 China

ISBN: (纸本)9798331523923

In intelligent systems, as the amount of data increases, how to analyse data and extract abnormal information is an important task. Based on this, in order to improve the detection efficiency and accuracy of abnormal data in intelligent systems, this study proposes a new and efficient abnormal data mining and detection algorithm. In the initial modelling process, this study introduced the minimum modification cost principle based on cross entropy for modelling. This algorithm optimizes the time series data cleaning process, thereby removing noise data while maintaining the integrity of the data sequence. Then, the extreme gradient boosting algorithm is combined with the Gaussian kernel function to achieve data dimension reduction. This operation can reduce data dimensions and feature redundancy. Finally, the overall anomaly detection operation by integrating the improved Ada boost algorithm with the sampling balance technology can improve the accuracy of the classifier while solving the problem of unbalanced data. The experimental results show that the proposed method is superior to the traditional algorithms in comprehensive indicators. © 2025 ieee.

关键词： Abnormal Data Detection Data Mining Algorithms Efficiency Optimization intelligent systems

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Adapting NIST Aerial Drone Tests for Thermal Identification, Inspection, and Suppression of Wildfires 15

Adapting NIST Aerial Drone Tests for Thermal Identification,...

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15th ieee Annual computing and Communication Workshop and conference, CCWC 2025

作者： Fraley, Alex Nowery, Ethan Devine, McCarthy Jacoff, Adam Oh, Paul Y. Project The Intelligent Systems Division The Engineering Laboratory GaithersburgMD20899 United States Department of Mechanical Engineering Las VegasNV89119 United States Department of Aerospace Engineering BoulderCO80309 United States in the Intelligent Systems Division The Engineering Laboratory GaithersburgMD20899 United States University of Nevada Las Vegas Faculty of Mechanical Engineering United States

ISBN: (纸本)9798331507695

The National Institute of Standards and Technology (NIST) has developed standard test methods to evaluate the capabilities of aerial drones, ground robots, and aquatic vehicles, as well as the proficiency of their operators. The aerial drone tests measure key capabilities such as maneuverability, visual acuity, and thermal acuity. With a rising demand for aerial drones among first responders, these tests are essential for assessing system performance, mitigating risk, and improving operational effectiveness to ensure the safety of responders and the public. Given the increasing prominence of wildfire threats and the widespread destruction they cause, aerial drones are being adapted to help detect, inspect, and contain them. This paper outlines how NIST-developed aerial drone tests can be adapted to simulate wildfire threats and provide a framework of reproducible tests that measure the system capabilities of aerial drones and the proficiency of operators in mitigating these threats. © 2025 ieee.

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HealthIUI: Workshop on intelligent and Interactive Health User Interfaces 25

HealthIUI: Workshop on Intelligent and Interactive Health Us...

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30th international conference on intelligent User Interfaces Companion, IUI 2025

作者： Brusilovsky, Peter Parra, Denis Rahdari, Behnam Raj, Shriti Torkamaan, Helma School of Computing and Information University of Pittsburgh PittsburghPA United States Department of Computer Science Pontificia Universidad Catolica de Chile Santiago Chile Stanford University Palo AltoCA United States Multi-Actor Systems Delft University of Technology Delft Netherlands

ISBN: (纸本)9798400714092

The HealthIUI workshop explores the integration of intelligent user interfaces in health and care, focusing on AI-driven solutions that enhance user engagement, support clinical decision-making, and improve health information access. The workshop brings together experts from human-computer interaction, AI, and healthcare to address challenges such as transparency, usability, and ethical considerations in AI-assisted health applications. Topics covered include generative AI for patient and caregiver support, AI-powered clinical decision support, adaptive visualization for consumer health information, and explainable AI in nursing care. Through paper presentations and discussions, the workshop fosters interdisciplinary collaboration to advance intelligent health interfaces that balance technical innovation with user-centric design principles. © 2025 Copyright held by the owner/author(s).

关键词： Electronic health record

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Blockchain-Enabled intelligent Vehicle Communication systems: Trust Bit Rewards and Clustering for Autonomous Vehicles 3

Blockchain-Enabled Intelligent Vehicle Communication Systems...

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3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Nirmala, P. Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331509675

In the absence of a permanent infrastructure, the networks are utilized for temporary events, military operations, and disaster recovery. A Blockchain-Enabled intelligent Vehicle Communication systems: Trust Bit Rewards and Clustering for Autonomous Vehicles (BIVC-CA), an algorithm designed to ensure secure communication between devices and optimize efficient routing in intelligent vehicle systems, is also used to provide quick emergency response. Using blockchain, each vehicle is given its own Bit Trust ID to track its past data and calculate its trust levels. This system ensures transparency and trust between vehicles through cryptographic processes such as key generation, secure message encryption, and message verification, which improve overall communication security. It also includes an Emergency Vehicle Communication System (EUC) that uses OBU devices and sensors to detect collisions and send GSM-based rescue messages, greatly improving road safety and the efficiency of emergency operations. The road-based clustering model optimizes route selection considering traffic conditions and distances and organizes vehicles into clusters to ensure effective communication and coordination. Using the path distance algorithm, clustering is achieved by computing the similarity of routes and grouping accordingly for efficient route management with minimal network congestion. In addition, the model introduces a comprehensive network architecture that integrates vehicle cloud technology and blockchain technology, enabling intelligent vehicles to make quick decisions based on real-time data. With these integrated components, the BIVC-CA model provides a reliable framework for secure data transmission, intelligent routing, and rapid emergency response. This framework will ultimately improve the efficiency of intelligent vehicle systems and contribute to the development of advanced vehicle networks and smarter transportation solutions. We calculated the results with routing expe

关键词： Blockchain

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intelligent Production and Quality Control Technology based on Computer Technology and Internet of Things Technology 1

Intelligent Production and Quality Control Technology based ...

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1st international conference on intelligent systems and Computational Networks, ICISCN 2025

作者： Li, Yaping Business School Ludong University Shandong Yantai China

ISBN: (纸本)9798331529246

The traditional manufacturing process seriously limits the improvement of production efficiency and product quality due to incomplete data collection and lagging information feedback. This paper uses genetic algorithms to construct an intelligent production scheduling model in the workshop, optimize production scheduling, and help enterprises shorten production cycles. At the same time, the Stacking algorithm is used for product quality prediction, and the deviation of a single model is effectively evaluated and corrected by integrating multiple models, thereby improving the prediction accuracy. Experiments show that the workshop production scheduling model based on genetic algorithm has a resource utilization rate of 96.14% when processing 1,000 production tasks;using the model constructed by Stacking, the average accuracy rate of product defect rate prediction is 94.5%.The method proposed in this article can quickly find the optimal or approximately optimal production scheduling scheme, and significantly improve production efficiency. © 2025 ieee.

关键词： Smart manufacturing

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Load balancing promotes effective IoT-based data transfer in Snowflake Storage systems 3

Load balancing promotes effective IoT-based data transfer in...

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3rd international conference on intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Jesupriya, J. Kavitha, M. Deeksha Presidency University India Presidency College Bengaluru India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515911

In networked devices, efficient data transportation is important for guaranteeing dependable and scalable Internet of Things (IoT) infrastructures. For this purpose, in the current work, a dynamic load-balancing mechanism is proposed to optimize the data transfer between Internet of Things nodes and Snowflake data storage. It may be fairly distributing the distributed data between IoT nodes, but traditional round-robin load balancing often overlooks the difference in node performance, which may lead to inefficient data transfer. A solution to this problem is a dynamic load-balancing mechanism that depends on nodes in real-time performing, hence its variation with transfer speed and latency. This system would dynamically select the most effective nodes that are to transmit the data and would ensure quicker and more dependable delivery of information. In the following simulation, round-robin and dynamic load-balancing strategies are compared using ten IoT nodes that are sending segmented data to a Snowflake server. Outcomes: These show that although the round-robin accomplishes reduced latency and faster transfer rates, the dynamic approach presents a fairer distribution of the load as well as reduces the possibility of node overloading while enhancing overall system robustness in the long term. This work adds to the future prospects of IoT load-balancing solutions, thus vividly showing how round-robin and dynamic approaches could present trade-offs between one another. © 2025 ieee.

关键词： Snow melting systems

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IoT based Thermal Management and State of Charge Estimation of LFP battery 3

IoT based Thermal Management and State of Charge Estimation ...

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3rd international conference on intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Anand, Deepthi Paraag, V. Naik, Sahana Kavana, T.M. Vasudha, Karanam Shubha Rao, K. Bnm Institute of Technology Dept. of Eee Bangalore India

ISBN: (纸本)9798331515911

Efficient storage of electricity is pivotal in modern applications, necessitating the use of batteries. However, enclosing batteries in compact spaces, such as power plants or electric vehicles, often leads to excessive heat generation, diminishing efficiency and longevity. Heat generation primarily stems from the charging and discharging processes. A liquid cooling system, powered by a motor connected to the battery system, circulates fluid externally around the battery layers to manage temperature, optimizing the battery's performance within the ideal range of 25°C to 35°C. Thermal Modelling of the battery is implemented in systems to understand how temperature changes affect their performance, efficiency, and reliability. IoT-based Battery Thermal Management System (IoT-BTMS) is introduced resulting in a sophisticated solution utilizing sensors, communication technologies, and data analytics. This system monitors and regulates battery temperature in real-time, based on sensed data a relay will enable cooling system if temperature values exceed the limit values or when the system becomes unstable, the cooling system continues until the system stabilizes and temperatures fall within limits. © 2025 ieee.

关键词： Cooling systems

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