Ad Hoc Networks最新文献_第8页

MobiAuth: Blockchain-driven decentralized authentication for enhanced security and privacy in mobile networks MobiAuth：区块链驱动的分散身份验证，用于增强移动网络的安全性和隐私性

IF 4.8 3区计算机科学

Ad Hoc Networks Pub Date : 2026-02-01 Epub Date: 2025-10-30 DOI: 10.1016/j.adhoc.2025.104064

Narendra K. Dewangan , Gauri Shankar

{"title":"MobiAuth: Blockchain-driven decentralized authentication for enhanced security and privacy in mobile networks","authors":"Narendra K. Dewangan , Gauri Shankar","doi":"10.1016/j.adhoc.2025.104064","DOIUrl":"10.1016/j.adhoc.2025.104064","url":null,"abstract":"<div><div>Decentralized authentication in dynamic mobile networks faces significant challenges due to high node mobility, resource constraints, and vulnerabilities to side-channel attacks. In this work, we present <strong>MobiAuth</strong>, a blockchain-driven framework based on Hyperledger Iroha and OMNET<span>++</span> that enables secure, peer-to-peer authentication using compact Ed25519 signatures and ephemeral session keys. Our protocol eliminates single points of failure by distributing trust across a permissioned ledger and employs constant-time cryptographic operations to thwart timing and power-analysis attacks. We validate MobiAuth through co-simulation in OMNET<span>++</span> integrated with Iroha via a Python gRPC bridge and benchmark its performance with Hyperledger Caliper.</div><div>Simulation yields 95% packet delivery with an authentication latency ranging from 12 ms in the only OMNeT<span>++</span> and baseline to 20–150ms in the full ledger-integrated system, and a ledger write throughput of 250tps. Comparative experiments demonstrate a 33% reduction in communication overhead and robust operation under random Control Point failures and Byzantine Access Node behavior. Analysis of on-device ledger synchronization further highlights practical storage growth and bandwidth requirements for long-term deployment. These results indicate that MobiAuth achieves strong security and privacy with modest energy impact, scalable performance, and compatibility with mobile devices in real-world network environments.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"181 ","pages":"Article 104064"},"PeriodicalIF":4.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145468555","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

Cross-Technology Interference awareness for multi-user OFDMA scheduling in IEEE 802.11ax IEEE 802.11ax中多用户OFDMA调度的跨技术干扰感知

IF 4.8 3区计算机科学

Ad Hoc Networks Pub Date : 2026-02-01 Epub Date: 2025-10-27 DOI: 10.1016/j.adhoc.2025.104057

Thijs Havinga, Xianjun Jiao, Wei Liu, Baiheng Chen, Robbe Gaeremynck, Ingrid Moerman

{"title":"Cross-Technology Interference awareness for multi-user OFDMA scheduling in IEEE 802.11ax","authors":"Thijs Havinga, Xianjun Jiao, Wei Liu, Baiheng Chen, Robbe Gaeremynck, Ingrid Moerman","doi":"10.1016/j.adhoc.2025.104057","DOIUrl":"10.1016/j.adhoc.2025.104057","url":null,"abstract":"<div><div>Cross-Technology Interference (CTI) significantly degrades the performance of heterogeneous wireless communication systems operating within a shared spectrum. Traditional mitigation techniques, such as Clear Channel Assessment (CCA), often fail due to, amongst others, varying bandwidth and detection threshold. Orthogonal Frequency Division Multiple Access (OFDMA), introduced to Wi-Fi in IEEE 802.11ax (Wi-Fi 6), allows multiple users to be served simultaneously using distinct subcarrier sets, known as Resource Units (RUs), providing enhanced flexibility in the frequency domain. This paper explores and evaluates several Wi-Fi 6 compliant methods for multi-user OFDMA scheduling with CTI awareness. Through simulations, we assess the benefits of different techniques in various scenarios, in terms of either total throughput or average latency. To effectively apply the mitigation techniques, we propose a methodology that incorporates CTI feedback from stations and real-time CCA per RU. Given that commercial Wi-Fi 6 access points lack control over low-level OFDMA features, we use <em>openwifi</em>, a full-stack Wi-Fi transceiver running on software-defined radio, to implement the CTI-aware OFDMA scheduler. Real-life experiments validate the effectiveness of the scheduler and confirm its real-time performance capabilities.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"181 ","pages":"Article 104057"},"PeriodicalIF":4.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145419843","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

Enhancement of fuzzy trust evaluation via autoencoders in game-theory based security distributed Wireless Sensor Networks 基于博弈论的安全分布式无线传感器网络中自编码器增强模糊信任评价

IF 4.8 3区计算机科学

Ad Hoc Networks Pub Date : 2026-02-01 Epub Date: 2025-11-04 DOI: 10.1016/j.adhoc.2025.104068

Xuegang Wu , Xu Zhang , Kun Gou , Jianfeng Wang

{"title":"Enhancement of fuzzy trust evaluation via autoencoders in game-theory based security distributed Wireless Sensor Networks","authors":"Xuegang Wu , Xu Zhang , Kun Gou , Jianfeng Wang","doi":"10.1016/j.adhoc.2025.104068","DOIUrl":"10.1016/j.adhoc.2025.104068","url":null,"abstract":"<div><div>With the rapid development of Internet of Things (IoT) technology, Wireless Sensor Networks (WSNs) have been widely applied in various fields, such as environmental monitoring, health detection, and smart homes. Since wireless sensor nodes are typically deployed in open and dynamically changing environments, the data are susceptible to interference and outliers, directly affecting the network’s reliability and decision-making accuracy. Therefore, effectively detecting and processing anomalous data has become a critical issue for the regular operation of WSNs.</div><div>This paper proposes techniques to enhance trust evaluation in game-theory based WSNs using autoencoders. These techniques effectively address the security challenges inherent in WSNs. The protocol first assigns a trust value to each node through fuzzy trust evaluation and recommendation mechanisms to differentiate between reliable and abnormal data. Subsequently, the game theory is used to select the optimal cluster head to optimize inter-node interactions and resource allocation, thereby enhancing overall network performance and robustness. Finally, an autoencoder is employed for dimensionality reduction and data reconstruction, with abnormal data being precisely detected by comparing the reconstruction error against a preset threshold and incorporating historical trust information.</div><div>Experimental results demonstrate that the proposed methods achieve high detection accuracy with low false positive or false negative rates in practical applications. Compared with traditional approaches, the proposed techniques exhibit stronger robustness and higher detection efficiency in complex environments, effectively meeting the demands of large-scale WSNs applications.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"181 ","pages":"Article 104068"},"PeriodicalIF":4.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145468466","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

Decentralized opportunistic crowdsensing task allocation with global and local communication 分散的机会主义众感任务分配与全球和本地通信

IF 4.8 3区计算机科学

Ad Hoc Networks Pub Date : 2026-02-01 Epub Date: 2025-11-01 DOI: 10.1016/j.adhoc.2025.104069

Chunyu Tu , Yanghui Chen , Zhiyong Yu , Fangwan Huang , Yuezhong Wu , Xianwei Guo , Chao Yang , Runhe Huang

{"title":"Decentralized opportunistic crowdsensing task allocation with global and local communication","authors":"Chunyu Tu , Yanghui Chen , Zhiyong Yu , Fangwan Huang , Yuezhong Wu , Xianwei Guo , Chao Yang , Runhe Huang","doi":"10.1016/j.adhoc.2025.104069","DOIUrl":"10.1016/j.adhoc.2025.104069","url":null,"abstract":"<div><div>Traditional opportunistic crowdsensing is usually managed by a central platform that assigns tasks, which imposes significant demands on the platform’s performance and increases the risk of privacy breaches for participants. To address these issues, this paper proposes a decentralized opportunistic sensing-based solution to achieve task allocation under a global budget constraint and maximize task coverage. Unlike traditional approaches, this solution allows participants to decide whether to join sensing tasks autonomously, forming a collaborative multi-agent system. In this decentralized environment, ensuring efficient task allocation while adhering to global constraints poses the main challenge. Since the communication conditions between participants directly affect the execution and coordination efficiency of global constraints, this paper designs corresponding global and local communication algorithms to address large-scale decentralized task allocation. Under global communication conditions, we adopt the concept of a cellular model and propose a decentralized genetic algorithm (D-GA). This approach utilizes global communication to evaluate the fitness of individuals, enabling coordinated problem-solving among agents. In addition, we consider local communication and design a decentralized soft-constrained probabilistic decision algorithm (DS-PD) to address scenarios where global communication is impractical. D-GA achieves 59.1%–81.2% task coverage, performing within 4.5%–5.8% of centralized integer linear programming while reducing execution time by over 96%. DS-PD significantly outperforms all methods under node failures, maintaining robust performance with only 2.1%–3.4% degradation.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"181 ","pages":"Article 104069"},"PeriodicalIF":4.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145468463","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

Optimization of ship engine room communication based on ray tracing method and ZigBee technology 基于光线追踪法和ZigBee技术的船舶机舱通信优化

IF 4.8 3区计算机科学

Ad Hoc Networks Pub Date : 2026-02-01 Epub Date: 2025-10-28 DOI: 10.1016/j.adhoc.2025.104067

Lige Yuan , Yangzhou Hao , Yinghua Li

{"title":"Optimization of ship engine room communication based on ray tracing method and ZigBee technology","authors":"Lige Yuan , Yangzhou Hao , Yinghua Li","doi":"10.1016/j.adhoc.2025.104067","DOIUrl":"10.1016/j.adhoc.2025.104067","url":null,"abstract":"<div><div>The communication quality in the engine room of the ship is not ideal because of the complicated internal environment of the ship during the voyage at sea. The communication quality of the existing communication methods is not high, which is affected by the environment of the engine room, and the signal is unstable and the transmission fails. In view of this situation, a communication optimization method for ship engine room based on ZigBee technology and ray tracing method is proposed. Firstly, ZigBee technology was used to design the networking structure, and simulation software and ray final method were used to simulate the ship scene and radio wave transmission. In addition, the state of the communication signal is predicted by the short-time memory network and the communication scheme is adjusted in time. Genetic algorithm is used to optimize the antenna parameters. Finally, according to the simulation model, the design network structure and node layout parameters are optimized, and the communication optimization of the ship engine room is finally realized. The experimental results show that the transmission rate, data packet transmission delay time and transmission error rate indicators of the communication system after using the communication optimization scheme designed in the research are 214.05kbps, 20.14ms and 0.52 % respectively. And its node coverage exceeds 90 %. It can be seen that the communication optimization method designed in this study can effectively improve the quality of communication transmission data, improve the transmission efficiency, and provide reliable communication technology support for ship navigation. The research method provides a new idea for the design of wireless communication system in similar complex environment.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"181 ","pages":"Article 104067"},"PeriodicalIF":4.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145468462","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

Stochastic Fractal Search with Reinforcement Learning for dynamic routing in resource-constrained IoT networks 基于强化学习的随机分形搜索在资源受限的物联网网络中的动态路由

IF 4.8 3区计算机科学

Ad Hoc Networks Pub Date : 2026-02-01 Epub Date: 2025-11-04 DOI: 10.1016/j.adhoc.2025.104083

Anupama Mondal , Dipankar Ch. Barman , Nabajyoti Mazumdar

{"title":"Stochastic Fractal Search with Reinforcement Learning for dynamic routing in resource-constrained IoT networks","authors":"Anupama Mondal , Dipankar Ch. Barman , Nabajyoti Mazumdar","doi":"10.1016/j.adhoc.2025.104083","DOIUrl":"10.1016/j.adhoc.2025.104083","url":null,"abstract":"<div><div>The Internet of Things (IoT) enables pervasive connectivity and large-scale data exchange among heterogeneous devices, driving advancements in intelligent automation and decision-making. However, the resource-constrained nature of IoT nodes and the increasing data traffic in dense deployments demand energy-efficient and adaptive communication strategies. This paper presents a hybrid framework that integrates Stochastic Fractal Search (SFS) for energy-efficient, trust-aware clustering with Q-Learning-based Reinforcement Learning (RL) for dynamic multi-hop routing in IoT and edge-assisted environments. The SFS-based clustering mechanism optimizes cluster-head selection by minimizing intra-cluster energy consumption and ensuring balanced load distribution, while the RL-based routing module adaptively learns optimal forwarding paths based on residual energy, link distance, and trust metrics. A dual trust model, incorporating both energy trust and data trust, is employed to detect and isolate unreliable nodes, thereby enhancing network reliability and security. The proposed SFSRL framework effectively reduces redundant transmissions, balances energy utilization, and enhances scalability across heterogeneous IoT-edge infrastructures. Simulation results validate that SFSRL outperforms existing protocols such as TEC-SFS, RINA, GATERP, and MODRL in terms of energy efficiency, network lifetime, Packet Delivery Ratio (PDR), data rate, throughput, and end-to-end delay, establishing it as a robust and scalable solution for next-generation IoT applications.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"181 ","pages":"Article 104083"},"PeriodicalIF":4.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145468554","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

A dual-mode framework for indoor localization via temporal learning and knowledge distillation 基于时间学习和知识升华的室内定位双模框架

IF 4.8 3区计算机科学

Ad Hoc Networks Pub Date : 2026-02-01 Epub Date: 2025-11-05 DOI: 10.1016/j.adhoc.2025.104089

Huang Lin, Yan Chen, Shuo Li, Wei Peng

引用次数: 0

Task offloading in satellite–MEC networks for latency-sensitive IoT applications: A martingale-based game approach 针对延迟敏感物联网应用的卫星- mec网络任务卸载：基于鞅的游戏方法

IF 4.8 3区计算机科学

Ad Hoc Networks Pub Date : 2026-02-01 Epub Date: 2025-10-24 DOI: 10.1016/j.adhoc.2025.104052

Xintong Pei , Zhenjiang Zhang , HanChieh Chao , Zihang Yu , Wenhui Wang

{"title":"Task offloading in satellite–MEC networks for latency-sensitive IoT applications: A martingale-based game approach","authors":"Xintong Pei , Zhenjiang Zhang , HanChieh Chao , Zihang Yu , Wenhui Wang","doi":"10.1016/j.adhoc.2025.104052","DOIUrl":"10.1016/j.adhoc.2025.104052","url":null,"abstract":"<div><div>To address the growing demand for latency-sensitive Internet of Things (IoT) applications in remote regions, satellite–integrated mobile edge computing (SMEC) deploys computational resources on Low Earth Orbit (LEO) satellites to provide seamless network access and edge computing services for IoT devices lacking terrestrial network coverage. However, ensuring quality of service (QoS) for latency-sensitive tasks in SMEC systems remains challenging due to two critical limitations: existing deterministic models cannot adequately capture the stochastic nature of discontinuous satellite–ground links, leading to inaccurate queuing delay predictions, and current approaches fail to adapt to dynamic user task preferences that significantly impact offloading effectiveness. In response to these challenges, this paper develops a novel dynamic task offloading framework that integrates martingale-based delay analysis with adaptive game-theoretic optimization. We employ Markov Chain Monte Carlo (MCMC) methods to characterize discontinuous satellite–ground stochastic service processes and apply martingale theory to derive tight statistical delay guarantees that significantly outperform conventional moment generating function approaches. Based on this analytical foundation, we formulate multi-task offloading as an exact potential game and propose the Temporal-Enhanced Stochastic Learning (TESL) algorithm, which leverages historical trend learning and environmental dynamics detection to achieve robust convergence in non-stationary environments. Experimental results demonstrate that TESL achieves a 37% lower delay violation probability compared to the best-performing baseline algorithm, exhibiting superior convergence efficiency and adaptability while improving utility, making it well-suited for practical SMEC deployments.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"181 ","pages":"Article 104052"},"PeriodicalIF":4.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145419847","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

MQTTEEB-D: A high-fidelity benchmark for real-time MQTT anomaly detection using machine learning techniques MQTTEEB-D：使用机器学习技术进行实时MQTT异常检测的高保真基准

IF 4.8 3区计算机科学

Ad Hoc Networks Pub Date : 2026-02-01 Epub Date: 2025-10-27 DOI: 10.1016/j.adhoc.2025.104062

Hamza Allaga , Mohamed Biniz , Abderrazak Farchane

{"title":"MQTTEEB-D: A high-fidelity benchmark for real-time MQTT anomaly detection using machine learning techniques","authors":"Hamza Allaga , Mohamed Biniz , Abderrazak Farchane","doi":"10.1016/j.adhoc.2025.104062","DOIUrl":"10.1016/j.adhoc.2025.104062","url":null,"abstract":"<div><div>Message Queuing Telemetry Transport (MQTT) is essential for resource-constrained Internet of Things (IoT) environments; however, its widespread adoption has introduced significant security vulnerabilities. Although machine learning (ML) offers a promising solution for anomaly detection, existing models are often hindered by unrealistic data, severe class imbalances, and high computational costs. To address these limitations, we present a comprehensive ML framework for MQTT anomaly detection benchmarked on MQTTEEB-D, a high-fidelity dataset from a physical IoT testbed. Our framework evaluates a diverse suite of algorithms, including tree ensembles and boosting methods, on both original imbalanced and balanced data. We assessed performance using standard metrics, imbalance-stable metrics such as the Matthews Correlation Coefficient (MCC), and a Performance–Efficiency Score (PES) to quantify the trade-off between predictive power and computational cost. Our results establish a new state-of-the-art, with the top models achieving over 98.8% accuracy and F1-score. These models also yielded dramatic efficiency gains, including a 43-fold reduction in training time and a 299-fold speedup in inference latency over previous benchmarks. Critically, we found that a model’s resilience to class imbalance is more vital for real-world deployment than its peak performance on artificially balanced data. Simpler tree-based models remained robust under imbalanced conditions, where more complex algorithms failed. These findings provide a new benchmark and reorient model selection towards efficient, reliable, and deployable IoT security systems.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"181 ","pages":"Article 104062"},"PeriodicalIF":4.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145419830","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

Collaborative deployment of Large AI Models on the edge: A microservice approach to heterogeneous training and quantized inference 边缘上大型人工智能模型的协作部署：异构训练和量化推理的微服务方法

IF 4.8 3区计算机科学

Ad Hoc Networks Pub Date : 2026-02-01 Epub Date: 2025-11-03 DOI: 10.1016/j.adhoc.2025.104080

Seyed Hossein Ahmadpanah , Meghdad Mirabi , Sanaz Sobhanloo , Pania Afsharfarnia , Donya Fallah , Mobina Bayati

{"title":"Collaborative deployment of Large AI Models on the edge: A microservice approach to heterogeneous training and quantized inference","authors":"Seyed Hossein Ahmadpanah , Meghdad Mirabi , Sanaz Sobhanloo , Pania Afsharfarnia , Donya Fallah , Mobina Bayati","doi":"10.1016/j.adhoc.2025.104080","DOIUrl":"10.1016/j.adhoc.2025.104080","url":null,"abstract":"<div><div>While Large AI Models (LAMs) offer transformative intelligence, their deployment in real-time Internet-of-Things (IoT) applications is constrained by the heterogeneity of edge networks and high cloud latency. To enable cooperative LAM deployment across diverse edge hardware, we propose a modular, hardware-aware framework. Our approach introduces two key innovations. First, a heterogeneity-aware training framework combines Quantization-Aware Training with parameter-efficient federated fine-tuning, reducing communication overhead by over 98% and allowing devices with different hardware (FP32 vs. INT8) to collaboratively refine a single model with near-native accuracy (84.9% vs. 85.5%). Second, a precision-aware inference architecture virtualizes LAM features, including Chain-of-Thought (CoT) steps and Mixture-of-Experts (MoE) layers, into multi-precision microservices. A dynamic orchestrator selects the optimal microservice for each task, balancing energy, latency, and accuracy. Compared to existing edge deployments, experiments show over 70% reduction in active memory usage and nearly 60% reduction in end-to-end inference latency. This framework provides a scalable, privacy-preserving solution for hardware-aware LAM intelligence on heterogeneous edge networks, effectively overcoming key deployment challenges.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"181 ","pages":"Article 104080"},"PeriodicalIF":4.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145468465","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