Ad Hoc NetworksPub Date : 2025-09-10DOI: 10.1016/j.adhoc.2025.104018
Ling Tan, Jing Song, Haifeng Wang, Hai Xu
{"title":"Device cooperation and energy efficiency optimization for backscatter-assisted wireless-powered D2D in Industrial Internet of Things","authors":"Ling Tan, Jing Song, Haifeng Wang, Hai Xu","doi":"10.1016/j.adhoc.2025.104018","DOIUrl":"10.1016/j.adhoc.2025.104018","url":null,"abstract":"<div><div>To address the issues of energy lifetime and resource utilization in the Industrial Internet of Things (IIoT), the combination of wireless energy harvesting and Backscatter Communication (BC) technology significantly enhances the large-scale interconnection capability of IIoT. In this paper, we propose a hybrid Device-to-Device (D2D) communication framework that combines BC with Active Transmission (AT), where devices can make intelligent decisions to switch between modes based on distance, channel, and energy conditions. By jointly optimizing device associations, backscatter coefficients, load, and time allocation, the system maximizes energy efficiency while meeting delay, energy, and task requirements. Meanwhile, considering that selfish device behaviors may hinder collaboration, we design a payment mechanism based on resource-sharing benefits, incorporating social relationships to incentivize devices to actively participate in cooperation. Additionally, we propose a Multiagent Deep Deterministic Policy Gradient algorithm in the D2D hybrid communication network to solve the long-term joint optimization problem, enabling devices to dynamically adjust offloading strategies and construct optimal D2D links. Simulation results show that the proposed algorithm achieves higher rewards and faster learning speeds, improving system energy efficiency by approximately 5.3% compared to A3C-HAB and by about 33.3% compared to other benchmark solutions, demonstrating superior energy efficiency performance.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 104018"},"PeriodicalIF":4.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145059933","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":"BMCH: Blockchain-enhanced multidimensional behavior scoring and privacy-preserving cluster head election scheme for the internet of vehicles","authors":"Ping Guo , Yuheng Jiang , Yanglei Gao , Puwadol Oak Dusadeerungsikul","doi":"10.1016/j.adhoc.2025.104022","DOIUrl":"10.1016/j.adhoc.2025.104022","url":null,"abstract":"<div><div>The high mobility and dynamic nature of vehicles pose significant challenges for existing cluster head election mechanisms, which struggle to maintain network stability and efficiency amidst frequent topology changes. To address these challenges, this study proposes a novel scheme based on Blockchain-enhanced Multidimensional vehicle behavior scoring for Cluster Head election (BMCH). The proposed method evaluates a range of factors, including participation degree, integrity degree, vehicle resources allocation, location and mobility pattern, vehicle compliance and legal adherence and vehicle anomalous behaviors. By dynamically adjusting scoring weights, the mechanism thereby ensures more accurate cluster head election under varying network conditions. Additionally, blockchain technology is integrated to encrypt and securely store trust scores and election outcomes, ensuring data integrity, consistency and decentralized tamper resistance. Experimental simulations demonstrate that the proposed approach enhances network stability even in the presence of malicious nodes, while achieving shorter cluster head election times, higher packet delivery rates, increased blockchain throughput, and acceptable energy consumption compared to representative existing schemes.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 104022"},"PeriodicalIF":4.8,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050105","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}
Ad Hoc NetworksPub Date : 2025-09-07DOI: 10.1016/j.adhoc.2025.103996
Yang Zhang , Ling Yang , Yan Tan
{"title":"Age of information-aware multi-agent task scheduling strategy for vehicular edge computing","authors":"Yang Zhang , Ling Yang , Yan Tan","doi":"10.1016/j.adhoc.2025.103996","DOIUrl":"10.1016/j.adhoc.2025.103996","url":null,"abstract":"<div><div>The rapid proliferation of intelligent transportation applications has created unprecedented demands for real-time data processing in vehicular networks. Vehicular Edge Computing (VEC) addresses these challenges by leveraging computing resources on moving vehicles, but ensuring information timeliness remains problematic due to network dynamics and resource constraints. This paper proposes a novel multi-agent scheduling framework that utilizes Age of Information (AoI) as the primary metric to maintain data freshness in VEC environments. Unlike conventional approaches that focus solely on latency reduction, our strategy employs a distributed multi-agent architecture where vehicle-mounted servers collaborate through limited information exchange to make coordinated scheduling decisions. We develop a hybrid optimization model combining game theory and reinforcement learning that enables agents to balance individual and collective objectives while adapting to vehicular mobility patterns. The scheduling mechanism operates across three dimensions: spatial (server selection), temporal (execution timing), and priority-based (task importance). Simulation results using real-world urban traffic datasets demonstrate that our approach reduces average AoI by 37 % compared to centralized scheduling methods, while improving computational resource utilization by 42 % and decreasing communication overhead by 29 %. The proposed framework shows particular effectiveness in dense urban scenarios and heterogeneous task environments, offering a scalable solution for maintaining information freshness in next-generation intelligent transportation systems.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 103996"},"PeriodicalIF":4.8,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050102","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}
Ad Hoc NetworksPub Date : 2025-09-04DOI: 10.1016/j.adhoc.2025.104007
Lucas Bréhon╌Grataloup , Rahim Kacimi , André-Luc Beylot
{"title":"Reliable multi-RAT connectivity in urban V2X architectures: An experimental campaign","authors":"Lucas Bréhon╌Grataloup , Rahim Kacimi , André-Luc Beylot","doi":"10.1016/j.adhoc.2025.104007","DOIUrl":"10.1016/j.adhoc.2025.104007","url":null,"abstract":"<div><div>The future of smart cities relies on the quick and reliable exchange of contextual information between devices. Deploying access points at the edge of the network significantly reduces the propagation distance of sidelink messages, resulting in very low latencies. However, urban environments pose significant challenges, as numerous obstacles can block direct links between devices and their intended destinations. While the typical fallback solution is cellular connectivity, the difference in performance is substantial. To address this, the present work puts forward solutions for improved reliability in multiple Radio Access Technology urban vehicular architectures. On the one hand, we address situations where multiple links are available, by establishing a make-before-break vertical handover scheme for optimized radio interface selection, monitoring the performance of received packets. On the other hand, we also reflect on the situations where communication ranges are shortened, and thus propose a method where packets sent via Cellular-Vehicle-to-Everything (C-V2X) sidelink are relayed. Here, the initial message is received by an intermediary with better connectivity to the target access point and then retransmitted from this improved position. These solutions have yet to be studied in real-life urban testbeds. We thus present experimental campaigns aimed at exploring the performance and reliability of such communications in urban V2X architectures, exploiting C-V2X, 5G, autonomous vehicles and state-of-the-art hardware. We study multiple scenarios, extending or shortening line-of-sight situations to analyze coverage and performance. Performance analysis of our vertical handover solution shows a reduced usage of cellular connectivity, leading to a 27% reduction of packet latency. Then, relayed C-V2X packets show high reliability at up to 200-meter ranges from one peer to another, with observed latencies being, at worst, 42% more favorable than the cellular fallback.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 104007"},"PeriodicalIF":4.8,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050106","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}
Ad Hoc NetworksPub Date : 2025-09-03DOI: 10.1016/j.adhoc.2025.104006
Shuaiyang Ma , Zhengyi Chai , Yalun Li , Jiani Fu , LiLing Sun
{"title":"Computation offloading for vehicular networks via sparse-attention-based multi-agent reinforcement learning","authors":"Shuaiyang Ma , Zhengyi Chai , Yalun Li , Jiani Fu , LiLing Sun","doi":"10.1016/j.adhoc.2025.104006","DOIUrl":"10.1016/j.adhoc.2025.104006","url":null,"abstract":"<div><div>For Mobile Edge Computing (MEC) offloading in large-scale Internet of Vehicles (IoV), existing methods struggle to provide low-latency services. This paper proposes a multi-agent algorithm based on sparse attention weighting, aiming to minimize the expected cost. Specifically, a long short-term memory (LSTM) model is integrated into the actor network to assist VUs in predicting the future states of edge servers (ESs). Additionally, a sparse attention mechanism is employed to compress the joint observation space, reducing computational complexity and enabling adaptation to large-scale VU environments. Furthermore, to address the convergence difficulties arising from a large number of agents, curriculum learning is adopted for phased training. We conduct evaluations in a custom IoV simulation environment,experimental results demonstrate that the proposed Multi-Agent Sparse-Attention Soft Actor–Critic (MASASAC) algorithm outperforms baseline methods in both performance and convergence speed, achieving an improvement of approximately 16.4 % to 37.6 % and further enhancing performance by approximately 10.9 % through curriculum learning.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 104006"},"PeriodicalIF":4.8,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027123","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}
Ad Hoc NetworksPub Date : 2025-09-01DOI: 10.1016/j.adhoc.2025.103999
Wenjin Yang, Bo Li
{"title":"Connectivity-aware UAV mobility in cellular networks: DRL path planning and predictive handover","authors":"Wenjin Yang, Bo Li","doi":"10.1016/j.adhoc.2025.103999","DOIUrl":"10.1016/j.adhoc.2025.103999","url":null,"abstract":"<div><div>The seamless integration of unmanned aerial vehicles (UAVs) into cellular networks promises transformative advances in logistics and emergency response, yet is fundamentally challenged by volatile airspace connectivity and inefficient handover mechanisms. To address these issues, we present a synergistic framework that unifies three-dimensional deep reinforcement learning (DRL)-based path planning with a predictive Reference Signal Received Power (RSRP)-aware handover algorithm. This framework jointly optimizes global path selection—using a multi-step dueling double deep Q-network (D3QN) to navigate challenging connectivity—and local handover management—employing a foresighted, proactive strategy to enhance handover efficiency. Such anticipatory decision-making ensures robust UAV communication under dynamic channel conditions. Unlike traditional separate optimization, it couples path planning with handover via future trajectory insights, enabling proactive adjustments. This integration yields superior performance, balancing throughput, outage risk, and handover overhead more effectively than isolated methods. Simulation results demonstrate substantial improvements over baseline methods in throughput, outage probability, and handover frequency across diverse flight scenarios. This work highlights that an integrated, anticipatory approach is crucial for developing scalable and resilient UAV communications in next-generation wireless networks.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 103999"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004387","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}
Ad Hoc NetworksPub Date : 2025-09-01DOI: 10.1016/j.adhoc.2025.103994
Shuang Zhang , Wen Tian , Xufei Ding , Xin Sun , Huaifeng Shi
{"title":"A tripartite matching game model for resource allocation in Multi-UAV assisted WSNs under asymmetric information","authors":"Shuang Zhang , Wen Tian , Xufei Ding , Xin Sun , Huaifeng Shi","doi":"10.1016/j.adhoc.2025.103994","DOIUrl":"10.1016/j.adhoc.2025.103994","url":null,"abstract":"<div><div>Unmanned aerial vehicles (UAVs) assisted wireless sensor networks (WSNs), a key component of the Internet of Things (IoT), comprise high mobility data collection device and numerous sensor nodes (SNs) that possess capabilities in sensing, computation, and wireless communication. However, UAV assisted WSN is limited by finite battery energy resources, which can result in substantial resource waste and increased energy consumption due to incorrect matching after multiple UAVs deployments. To resolve this matter, this paper proposes a tripartite matching game model for resource allocation in multi-UAV assisted WSNs (TGRUW) under asymmetric information. Specifically, the TGRUW combines the Vickrey–Clarke–Groves-based reverse (Reverse VCG) auction and the Second-price sealed auction (SPSA) algorithm, which can be used to deal with false information in the process of communication device matching and reduce energy consumption in device matching and communication, while considering computational efficiency, Nash equilibrium, and individual rationality. Finally, numerical simulation results demonstrate that the proposed algorithms achieve significant energy saving compared with random sampling-based method (RSBM), low cost preferred method (LCPM) and high valuation preferred method (HVPM).</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 103994"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144997713","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}
Ad Hoc NetworksPub Date : 2025-09-01DOI: 10.1016/j.adhoc.2025.104005
Feng Zhang , Yongqiang Shi , Gang Xu , Guanghui Wei , Zixuan Yuan
{"title":"Heuristic community path awareness based routing algorithm in opportunistic Networks","authors":"Feng Zhang , Yongqiang Shi , Gang Xu , Guanghui Wei , Zixuan Yuan","doi":"10.1016/j.adhoc.2025.104005","DOIUrl":"10.1016/j.adhoc.2025.104005","url":null,"abstract":"<div><div>To address the challenge of excessive transmission overhead during message delivery in large-scale opportunistic networks, this paper proposes a routing algorithm based on heuristic community path awareness (HCAR). Nodes with similar social relationships are first grouped into communities. Differentiated strategies are then employed for intra-community and inter-community message forwarding. Specifically, within the same community, a heuristic function optimizes routing paths between source and destination nodes. For inter-community message forwarding, a community proximity metric is introduced to evaluate a node’s interaction density with the target community. This metric serves as an encounter-driven heuristic function to identify the shortest inter-community routing path. Relay node selection for both scenarios is dynamically optimized by integrating heuristic functions with encounter probability models. Extensive experiments using both simulation scenarios and real-world datasets were conducted to validate the effectiveness of HCAR. Compared to EPST, BubbleRap, Epidemic, and Prophet routing algorithms, HCAR achieves at least a 15.6% higher message delivery rate, 12% lower latency, and a notably reduced transmission overhead of 36.5%.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 104005"},"PeriodicalIF":4.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989988","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}
Ad Hoc NetworksPub Date : 2025-08-30DOI: 10.1016/j.adhoc.2025.104002
Prajisha C. , Vasudevan A.R.
{"title":"Detection and mitigation of Multicast DIS flooding attacks in RPL-based IoT networks","authors":"Prajisha C. , Vasudevan A.R.","doi":"10.1016/j.adhoc.2025.104002","DOIUrl":"10.1016/j.adhoc.2025.104002","url":null,"abstract":"<div><div>Routing Protocol for Low-Power and Lossy Networks (RPL) is the de facto standard for IPv6-based wireless sensor networks in Internet of Things (IoT) environments. However, the inherent characteristics of Low Power and Lossy Networks (LLNs), including limited energy resources, constrained memory and processing capabilities, high packet loss rates, and dynamic network topologies, make RPL highly susceptible to control plane disturbances. Among these, multicast DIS flooding attacks are particularly damaging, as they repeatedly trigger Trickle timer resets across multiple neighbors, causing excessive control message propagation, severe energy depletion, and routing instability. Existing countermeasures often require protocol modifications, incur high overhead, or fail to discriminate between normal and malicious multicast DIS patterns in dynamic environments. Motivated by these challenges, this work proposes DIS-FDM, a lightweight, fully distributed detection and mitigation scheme for multicast DIS floods. DIS-FDM employs Dempster-Shafer theory (DST) to fuse evidence from local DIS traffic load and parent change frequency, allowing accurate attack detection without altering core RPL functions. The simulation results in Contiki/Cooja demonstrate that DIS-FDM significantly reduces control overhead, improves packet delivery ratio, and reduces power consumption compared to baseline RPL and existing defenses.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"179 ","pages":"Article 104002"},"PeriodicalIF":4.8,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989987","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}