Ad Hoc Networks最新文献

{"title":"Generative AI-based intrusion detection systems for intra-vehicle networks","authors":"Guettouche Asaouer,&nbsp;Djallel Eddine Boubiche","doi":"10.1016/j.adhoc.2025.104031","DOIUrl":"10.1016/j.adhoc.2025.104031","url":null,"abstract":"<div><div>With the rise of connected and autonomous vehicles, securing Intra-Vehicle Networks against cyber threats has become a critical challenge. The Controller Area Network bus, a widely used communication protocol in modern vehicles, remains highly vulnerable to sophisticated intrusion attacks. Traditional Machine Learning and Deep Learning based Intrusion Detection Systems have demonstrated limitations in adaptability, real-time performance, and handling zero-day attacks. This survey explores the emerging role of Generative Artificial Intelligence in enhancing IVN security. It examines key GenAI—assessing their potential to address the shortcomings of conventional IDS techniques. A comprehensive review of recent literature is conducted, analyzing the effectiveness of generative approaches in intrusion detection compared to deterministic methods. Key aspects such as detection time, adaptability to unknown threats, and real-time processing constraints are evaluated. Additionally, this paper identifies existing research gaps, emphasizing the need for standardized datasets, federated learning strategies, and improved deployment techniques to ensure the practical viability of GenAI-based IDS in real-world vehicular environments. The insights presented aim to guide future research toward more robust and adaptive security solutions for IVNs.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"180 ","pages":"Article 104031"},"PeriodicalIF":4.8,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160001","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}

{"title":"Exploiting multiple links with a single interface: A performance study","authors":"Stefano Avallone,&nbsp;Pasquale Imputato,&nbsp;Ferdinando Marrone","doi":"10.1016/j.adhoc.2025.104029","DOIUrl":"10.1016/j.adhoc.2025.104029","url":null,"abstract":"<div><div>The IEEE 802.11 working group is in the final stages of completing the 802.11be amendment, which outlines the features to be supported by Wi-Fi 7 devices. One of the key innovations introduced is Multi-Link Operation (MLO), which enables a device to function across multiple frequency channels simultaneously. Among the various MLO configurations, Enhanced Multi-Link Single Radio (EMLSR) has garnered significant attention from vendors due to its ability to leverage multiple links with reduced hardware complexity.</div><div>This paper begins by presenting an overview of the EMLSR specifications as defined in the standard and outlines the implementation model used in the ns-3 simulator, one of the most widely used simulators for wired and wireless networks. The performance of EMLSR operations has not been analyzed in depth so far. To the best of our knowledge, this paper is the first one to offer a theoretical analysis along with a simulation-based evaluation to assess the performance of an EMLSR client. Under saturated network conditions without external interference, the EMLSR client demonstrates throughput performance comparable to – or even exceeding – that of a traditional Single-Link Device (SLD), despite the overhead introduced by MLO functionality. In scenarios with unsaturated traffic and interference, the EMLSR client not only achieves lower latency than an SLD but also matches or outperforms a Multi-Link Device (MLD) with more advanced hardware that operates across multiple links simultaneously.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"180 ","pages":"Article 104029"},"PeriodicalIF":4.8,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145134835","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}

{"title":"OCUS: A game-theoretic approach to optimal UAV coalitions in UAV-as-a-Service platforms","authors":"Prince Kumar ,&nbsp;Akhand Pratap Narayan Singh ,&nbsp;Anchal Dubey ,&nbsp;Farid Nait-Abdesselam ,&nbsp;Arijit Roy","doi":"10.1016/j.adhoc.2025.104030","DOIUrl":"10.1016/j.adhoc.2025.104030","url":null,"abstract":"<div><div>This paper presents OCUS, an optimal coalition formation scheme designed to enhance the performance of UAV-as-a-Service (UaaS) platforms for Internet of Things (IoT) applications. UaaS platforms typically involve a set of heterogeneous UAVs owned by different entities. Serving IoT applications such as agriculture, traffic monitoring, and surveillance often requires multiple UAVs with diverse sensing, processing, and communication capabilities. Thus, forming an optimal coalition of these UAVs is essential for efficient resource utilization and application performance. Despite the growing interest in UAV-based services, existing literature lacks coalition formation schemes tailored for UaaS platform. To address this gap, OCUS leverages a coalition game-theoretic approach, where each UAV acts as a player in the game. The scheme introduces a selection score, which evaluates UAV owners based on reputation, cost competitiveness, and task allocation fairness. Using a payoff-driven method, OCUS promotes coalition stability and maximizes utility for UaaS platforms. The payoff function considers utility, reputation, task allocation fairness, costs, and equilibrium constraints. By employing Nash Equilibrium (NE) principles, OCUS ensures stable coalitions, discouraging UAVs from switching coalitions for higher payoffs. OCUS optimizes coalition formation by maximizing task completion rates, minimizing energy consumption, and ensuring fair and stable UAV participation through game-theoretic modeling. To evaluate OCUS, simulation experiments were conducted over 100 iterations involving 1 to 25 heterogeneous UAVs across a 50 × 50 unit² area, with varying distances and task counts (<span><math><mrow><mn>1</mn><mo>−</mo><mn>15</mn></mrow></math></span>). Simulation results demonstrate that OCUS achieves 25%–30% more stable coalitions compared to state-of-the-art approaches. Furthermore, NE principles enable OCUS to form coalitions that balance efficiency and fairness, advancing the capabilities of UaaS platforms in diverse IoT scenarios. OCUS offers promising applicability in real-world domains such as urban infrastructure management and emergency response, where adaptive and coordinated UAV operations can significantly enhance the delivery of services.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"180 ","pages":"Article 104030"},"PeriodicalIF":4.8,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160000","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}

{"title":"User willingness aware task allocation for cloud–edge–terminal collaborative crowdsensing system","authors":"Junru Hei,&nbsp;Lin Cong,&nbsp;Huansheng Xue,&nbsp;Yongji Sun,&nbsp;Haozhou Liu,&nbsp;Honglong Chen","doi":"10.1016/j.adhoc.2025.104028","DOIUrl":"10.1016/j.adhoc.2025.104028","url":null,"abstract":"<div><div>Cloud–Edge–Terminal Collaborative Crowdsensing (CETCS) has emerged as a novel research paradigm in the field of Mobile Crowdsensing (MCS). By leveraging edge servers for task computation, CETCS effectively mitigates communication delays and request congestion caused by the increasing scale of sensing tasks and growing data complexity. However, in real-world deployments, edge servers are characterized by resource and service heterogeneity. The Heterogeneous Edge Servers based Task Allocation (HESTA) problem has been formally formulated and proven to be NP-hard. Previous studies have largely overlooked two critical aspects: users’ willingness to execute tasks and the complexity involved in task offloading decisions. To address these limitations, we propose a unified framework that integrates Willingness-Aware Repair with a Probability Genetic Algorithm and Proximal Policy Optimization with the Dynamically Masked Action Space to jointly optimize task allocation, offloading, and computation during the task execution process. Our work differs from previous works in the following aspects: (1) We develop a comprehensive optimization framework that explicitly incorporates user willingness into the task allocation process to maximize overall platform utility; (2) We systematically categorize potential scenarios arising during task offloading and design corresponding utility functions to guide decision-making; (3) We propose a novel task offloading and computation selection algorithm aimed at maximizing the average remaining time of all tasks, thereby enhancing system responsiveness and efficiency. The extensive simulations are conducted on both synthetic and real-world datasets to demonstrate the effectiveness and superiority of the proposed approach.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 104028"},"PeriodicalIF":4.8,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158486","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}

{"title":"Trustworthy computation offloading in digital twin edge networks: A hierarchical game-based approach","authors":"Soumaya Bounaira ,&nbsp;Ahmed Alioua ,&nbsp;Anna Maria Vegni ,&nbsp;Ibraheem Shayea","doi":"10.1016/j.adhoc.2025.104008","DOIUrl":"10.1016/j.adhoc.2025.104008","url":null,"abstract":"<div><div>The rapid adoption of artificial intelligence (AI) across Internet of things (IoT) applications has intensified the demand for substantial computational resources. Due to the inherent resource limitations of IoT mobile devices, they are often unable to run most resource-intensive applications locally. Mobile edge computing (MEC) emerges as a promising solution, enabling task offloading to powerful edge servers. Although the technical aspects of task offloading are well-investigated in literature, the critical dimensions of security and trust concerns often remain under-explored. To address this gap, we introduce a blockchain-based trust management mechanism for digital Twin (DT) empowered MEC, facilitating informed offloading decision-making in task delegation and processing. The proposed trust management mechanism uses DT to enhance dynamic real-time task offloading. DT provides insights into the physical MEC environment and shares AI agent training data deployed on IoT devices, optimizing workload distribution. Our proposed trust management mechanism is based on an incentive cooperation model based on a hierarchical game model. Initially, we model cooperation among reliable servers as a hedonic coalition formation game, capturing edge servers’ selfish behavior and aiming to maximize utilities. Subsequently, we model interactions between service-seeking devices and the coalition as a two-stage Stackelberg game, encouraging devices to delegate tasks to the most reliable coalition. The simulation results validate the effectiveness of our trustworthy approaches, demonstrating significant improvements in energy efficiency compared to existing related works. Our study shows up to a 60% increase in energy consumption fairness, while ensuring trust among nodes.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 104008"},"PeriodicalIF":4.8,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158586","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}

{"title":"PORPRS: Priority-aware task offloading in HAP-aided Internet of Vehicles via GRPO with Dynamic residual shrinkage networks","authors":"Kunkun Yue ,&nbsp;Kai Peng ,&nbsp;Yuanlin Lin ,&nbsp;Xiaoyue Zhao ,&nbsp;Xiaolong Xu ,&nbsp;Victor C.M. Leung","doi":"10.1016/j.adhoc.2025.104004","DOIUrl":"10.1016/j.adhoc.2025.104004","url":null,"abstract":"<div><div>In Internet of Vehicles (IoV), the uneven distribution of heterogeneous computing resources leads to unmet quality of service demands for tasks in certain areas. Leveraging their substantial computing resources, extensive spatial coverage, and the assistance of intelligent reflecting surfaces, high-altitude platforms present a viable solution to mitigate resource scarcity in remote IoV. Although existing research has significantly advanced the development of computation offloading strategies, many studies overlook the impact of task priority in heterogeneous scenarios on the overall quality of task execution. To address these problems, we propose a priority-aware computation offloading that evaluates task priority through a multi-dimensional framework. This framework considers delay constraints to ensure timely execution for delay-sensitive tasks, energy consumption to balance computing demands with system utility, regional computing resources to prioritize tasks in resource-constrained areas, and policy reliability to maintain the completion rate of tasks. To mitigate the impact of task priority on the overall quality of task execution, tasks with higher priority are executed first. Specifically, the computation offloading sequence is dynamically adjusted based on the task priority. On the basis of the dynamic sequence, to facilitate rational offloading strategy-making by agents, we design a group relative policy optimization with dynamic residual shrinkage networks, which enhances algorithm robustness by eliminating redundant features. Finally, extensive experiments are conducted on real datasets. The experimental results show that our algorithm can improve the completion rate of tasks while reducing delay and energy consumption.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 104004"},"PeriodicalIF":4.8,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096991","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}

{"title":"Waves interference for perfect output VES in spite of swarm Byzantine participants","authors":"Shlomi Dolev ,&nbsp;Alexander Fok ,&nbsp;Michael Segal","doi":"10.1016/j.adhoc.2025.104026","DOIUrl":"10.1016/j.adhoc.2025.104026","url":null,"abstract":"<div><div>Visual Encryption Schemes (VES) encode the pixels of a secret image into <span><math><mi>n</mi></math></span> subpixel maps (shares), each of size <span><math><mrow><mi>m</mi><mo>×</mo><mi>m</mi></mrow></math></span>, where <span><math><mi>m</mi></math></span> is a scheme parameter. The encoding relies on a visual property such as transparency, and the resulting shares appear as random patterns of black and white subpixels. Each individual share reveals no information about the original image.</div><div>To reconstruct the secret image, at least <span><math><mi>k</mi></math></span> out of <span><math><mi>n</mi></math></span> shares must be stacked, where <span><math><mi>k</mi></math></span> is a predefined threshold. This structure poses a challenge in swarm-based applications – such as Unmanned Aerial Vehicle (UAV) swarms – where each UAV holds only a single share and collaborates to identify a target image.</div><div>In this work, we propose an optical VES solution that leverages wave interference as a physical encoding mechanism. The reconstructed image contains only pure black and white pixels, thus overcoming the grayscale degradation associated with traditional VES methods. Furthermore, the proposed scheme retains the computational efficiency of classical approaches while offering an improved security model: it achieves statistical information-theoretic security against honest-but-curious adversaries and is also resilient to active Byzantine adversaries.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 104026"},"PeriodicalIF":4.8,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158588","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}

{"title":"On WVSN deployment, load balancing and scheduling for 3D indoor monitoring: A cross-layer design approach","authors":"Zhonghui Wang ,&nbsp;Xi Jin ,&nbsp;Qingsong Zhao ,&nbsp;Feng Wang ,&nbsp;Khaled Sabahein","doi":"10.1016/j.adhoc.2025.104024","DOIUrl":"10.1016/j.adhoc.2025.104024","url":null,"abstract":"<div><div>Wireless Visual Sensor Networks (WVSNs), as a recent advancement in the domain of Wireless Sensor Networks (WSNs), exhibit several unique characteristics owing to their directional visual sensing capabilities. These distinctions render traditional WSN methodologies, such as k-coverage, inadequate for addressing the challenges posed by WVSNs. In particular, visual data — being substantially larger, real-time, and more complex than scalar data — introduce new demands on data routing, load balancing, and traffic scheduling mechanisms.</div><div>This paper presents a top-down cross-layer optimization framework to address these challenges within the context of three-dimensional (3D) indoor monitoring. At the Application layer, the study introduces the concept of 2-angular-coverage, extending the conventional k-coverage model by accounting for directional perspectives from multiple visual sensors. To this end, both a greedy heuristic and an enhanced depth-first search (DFS) algorithm are proposed to optimize sensor deployment while ensuring angular diversity.</div><div>At the Network layer, this research critiques the limitations of tree-based topologies commonly used in WSNs for traffic routing. It proposes an alternative strategy that leverages the entire network topology, formulating the load balancing task as a generalized maximum flow problem and solving it via an efficient optimization algorithm.</div><div>At the Link layer, a Time Division Multiple Access (TDMA)-based scheduling algorithm is developed to ensure contention-free transmission of visual streaming data. Moreover, optimization insights from upper layers are integrated to enable cross-layer refinement, thereby improving visual data quality and minimizing end-to-end transmission latency.</div><div>The results demonstrate the effectiveness of the proposed methods in enhancing visual coverage quality, achieving balanced network traffic, and reducing overall communication latency in WVSNs.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 104024"},"PeriodicalIF":4.8,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096992","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}

{"title":"Data collection with a team of capacity-constrained unmanned aerial vehicles assisted by a mobile recharger","authors":"Ahmet Enes Ok ,&nbsp;Deniz Ozsoyeller","doi":"10.1016/j.adhoc.2025.104025","DOIUrl":"10.1016/j.adhoc.2025.104025","url":null,"abstract":"<div><div>Wireless Sensor Networks (WSNs) have been utilized in various applications such as environmental monitoring, precision agriculture, disaster response, and military surveillance. A critical challenge that affects the system lifetime is the limited battery capacity of the sensors. In this paper, we study the sensor data collection problem with a team of unmanned aerial vehicles (UAVs) and a single unmanned ground vehicle (UGV). The UAVs work as data collectors while the UGV provides recharging and data-relaying services to the UAVs. We envision partitioned WSN scenarios, where the communication graph on the initial locations of all sensors is not connected. The objective is to minimize the total time required for the UAVs to collect the data of all sensors. We present a multi-stage online data collection algorithm that plans the paths for the UAVs that do not know the locations of the sensors in advance and are subject to both energy and storage capacity constraints. Our algorithm also plans the path of the UGV and determines the recharging sites for UGV-UAV rendezvous considering not only the limited energy capacity of the UAVs but also the total units of sensor data to be collected by each UAV. We analyze its performance theoretically, in extensive simulations, and on well-known benchmark instances.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 104025"},"PeriodicalIF":4.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096994","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}

{"title":"SEROS: Shared exploration and reward optimization task scheduling strategy for multi-agent collaboration in edge computing networks","authors":"Lei Jin,&nbsp;Junyan Chen,&nbsp;Rui Yao,&nbsp;Jiahao Chen,&nbsp;Xinmei Li","doi":"10.1016/j.adhoc.2025.103992","DOIUrl":"10.1016/j.adhoc.2025.103992","url":null,"abstract":"<div><div>The integration of mobile edge computing (MEC) into dynamic wireless ad hoc networks has intensified the challenges of computational resource scheduling, particularly under queue load constraints. Current research primarily focuses on global average metrics while neglecting fairness in resource allocation among devices across cross-time slot task scenarios. This oversight leads to significant disparities in the resources allocated to different devices, with some devices consistently lacking computational resources due to imbalanced scheduling. To address these limitations, we propose SEROS (Shared Exploration and Reward Optimization Strategy), a multi-agent reinforcement learning framework designed for cross-timeslot task scheduling in MEC environments. The method dynamically balances local optimization objectives with global collaboration through a weighted shared reward mechanism while enhancing training efficiency via hybrid sample trajectory utilization, enabling adaptive task offloading decisions. First, we construct a mobile edge computing model incorporating queue load constraints to address cross-timeslot task scheduling challenges, improving resource utilization for time-sensitive workloads through delayed optimization objectives. Second, we design a collaborative incentive mechanism based on global–local reward balancing and develop a sample trajectory-sharing scheme to accelerate policy convergence while preserving agent specialization. Simulation experiments validate the effectiveness of SEROS, demonstrating that compared with baseline methods, the proposed approach exhibits superior comprehensive performance in task completion rate improved by 7% and inter-device completion rate concentration enhanced by 40%, along with stability and task completion time.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 103992"},"PeriodicalIF":4.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158587","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}