Shounak Mandal¹, Subhadip Pati^1,#, Nirmallyadeb Ray^1,#, Bipasha Guha Roy^2,#, Priyanka Saha³, Deepsubhra Guha Roy^2,*

Digital Engineering and Digital Twin, Vol.4, pp. 27-47, 2026, DOI:10.32604/dedt.2026.081859 - 14 August 2026

Abstract HealthyBrain is a scalable, interoperable, and intelligent Remote Patient Monitoring (RPM) platform built on Internet of Things (IoT) technologies and a modular microservices architecture. The system integrates wearable IoT devices, MQTT (Message Queuing Telemetry Transport)-based lightweight messaging, and high-throughput real-time data streaming via Apache Kafka. Edge-side preprocessing enables low-latency analytics, while machine learning-based anomaly detection models facilitate early identification of critical health events. To ensure clinical interoperability, the platform adheres to the HL7 FHIR (Fast Healthcare Interoperability Resources) standard for electronic health record exchange. The system’s novel contribution lies in the unified integration of edge… More >

Dogukan Sugolu, Lutfiye Kusak^*

Revue Internationale de Géomatique, Vol.35, pp. 461-489, 2026, DOI:10.32604/rig.2026.079178 - 29 July 2026

Abstract Disasters are occurring much more frequently and their impacts are worsening due to factors such as climate change, rapid urbanization, and environmental degradation. The need for technologies like Mobile Geographic Information Systems (Mobile GIS) in disaster management is increasing every day. This study evaluates mobile GIS applications in disaster management using a hybrid method combining bibliometric analysis with a PRISMA-based systematic review approach. Analyzing 353 publications, the study reveals that mobile GIS research is among the preferred technologies in disaster management. However, a significant structural imbalance is also noticeable in the literature, with a large… More >

Khamza Eshankulov¹, Bahodir Muminov², Robiya Farmonova¹, Dilnavoz Sodikova³, Bakhriddin Bozorov⁴, Zavqiddin Temirov⁵, Rashid Nasimov^6,*

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.081803 - 23 July 2026

Abstract Cloud-based Business Intelligence (BI) systems operate under highly dynamic analytical workloads, including bursty OLAP queries, concurrent aggregations, and real-time microservice interactions, where static resource allocation leads to latency spikes and inefficient resource utilization. This paper proposes a decentralized adaptive Pareto-based multi-agent decision model for real-time resource coordination in cloud BI microservice environments. The agent placement problem is formulated as a multi-criteria decision process that minimizes service response latency, improves computational resource utilization, and preserves Quality-of-Service (QoS) stability. Instead of constructing a centralized global optimization policy, the proposed framework relies on decentralized locally Pareto-efficient decisions combined More >

Xiaoyun Yuan^1,2,3,*, Zhengge Yi^1,2, Jingxi Zhang^1,2, Hairui Zhang³

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.072275 - 23 July 2026

Abstract Website Fingerprinting (WF) has emerged as a promising technique for identifying user access patterns to Hidden Services (HS). Despite growing interest in WF for HS, the absence of well-established foundations and systematic guidelines for feature selection undercuts the robustness of WF techniques in the face of concept drift. To address this gap, we present an empirical study focusing on feature resilience under concept drift in WF for HS. Specifically, we categorize features into network-specific and network-agnostic groups and quantify their information leakage potential via mutual information. We further assess each feature’s resilience to concept drift More >

Zewen Ge^1,*, Jihui Liu², Shuai Yuan¹, Mufan Zhuang^3,*

Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.082217 - 12 July 2026

Abstract Limiting warming to the Paris temperature goals requires a rapid scale-up of low-carbon energy, yet recent experience suggests that deployment is increasingly shaped by delivery constraints rather than by technology cost trends alone. This review synthesizes peer-reviewed evidence on five constraints that repeatedly slow net-zero buildouts: lengthy approval and grid-connection processes; capital-intensive investment profiles that heighten sensitivity to the cost of capital and revenue risk; bottlenecks in critical minerals, processing, and manufacturing; social contestation and local governance that translate into siting exclusions, delays, and cancellations; and modeling traditions that can underrepresent these non-marginal frictions. Accordingly,… More > Graphic Abstract

Hitesh Mohapatra^*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.080961 - 15 June 2026

Abstract This review systematically analyzes Reinforcement Learning approaches for self-healing in energy-constrained secure edge IoT networks across 82 studies from 2020 to 2026. Unlike existing surveys that focus on general RL applications, the proposed review focuses on a three-level taxonomy that uniquely addresses edge IoT deployment realities through formulation-scope-hardware mapping. The work develops a novel three-level taxonomy classifying recovery scope (node, link, service, network), RL formulations (tabular, deep, multi-agent, model-based), and constraint integration (energy, latency, security, hybrid), revealing service migration dominance at 30% coverage and node recovery achieving 38% maximum energy savings. Normalized performance baselines establish More >

Bin Fang¹, Qi Yu¹, Han Wu², Xingxing Hou², Jingyu Zhang^2,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.080210 - 15 June 2026

Abstract The integration of Internet of Things (IoT) with blockchain technology introduces significant challenges in handling massive and frequent transaction data generated by distributed IoT devices. The Unspent Transaction Output (UTXO) model, widely adopted in blockchain systems like Bitcoin, faces critical scalability issues when applied to IoT environments. This is because the datasets it processes expand rapidly, which consumes a large amount of memory and increases the disk access latency of resource-constrained IoT nodes. Existing optimization approaches exhibit limitations in dynamic adaptability and protocol compatibility. To address these challenges, we propose an improved blockchain-empowered storage service More >

Hamza Ahmed¹, Hassan Jamil Syed^2,*, Aqsa Aslam¹, Sehar Zehra¹, Ummay Faseeha¹, Nurzati Iwani Othman²

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.080115 - 15 June 2026

Abstract Edge computing is an emerging model for latency-sensitive and distributed applications. However, the observability of edge computing systems in heterogeneous environments remains a challenge, as most existing approaches are limited to only the system, service, application, and network layers. This paper surveys state-of-the-art solutions for edge observability and monitoring. The paper further introduces a thematic taxonomy that groups the state-of-the-art edge observability and monitoring literature based on monitoring intent, telemetry indicators, observability scope, architectural layers, deployment environments, and observability toolchains. Finally, we compare representative solutions in terms of latency, system overhead, bandwidth consumption, and detection More >

Goodness Adediran¹, Kenny Awuson-David², Yussuf Ahmed^1,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.077606 - 12 March 2026

Abstract Amazon Web Services (AWS) CloudTrail auditing service provides detailed records of operational and security events, enabling cloud administrators to monitor user activity and manage compliance. Although signature-based threat detection methods have been enhanced with machine learning and Large Language Models (LLMs), these approaches remain limited in addressing emerging threats. This study evaluates a two-step Retrieval Augmented Generation (RAG) approach using Gemini 2.5 Pro to enhance threat detection accuracy and contextual relevance. The RAG system integrates external cybersecurity knowledge sources including the MITRE ATT&CK framework, AWS Threat Technique Catalogue, and threat reports to overcome limitations of… More >

Xinli Hao¹, Qingyuan Gong², Yang Chen^1,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073155 - 12 January 2026

Abstract Topological information is very important for understanding different types of online web services, in particular, for online social networks (OSNs). People leverage such information for various applications, such as social relationship modeling, community detection, user profiling, and user behavior prediction. However, the leak of such information will also pose severe challenges for user privacy preserving due to its usefulness in characterizing users. Large-scale web crawling-based information probing is a representative way for obtaining topological information of online web services. In this paper, we explore how to defend against topological information probing for online web services,… More >