Ad Hoc NetworksPub Date : 2025-03-17DOI: 10.1016/j.adhoc.2025.103829
Weibing Zeng , Zhendong Wang , Shuxin Yang , Daojing He , Sammy Chan
{"title":"ICMH-CHR: An intra-cluster multi-hop based cluster head rotation protocol for wireless sensor networks","authors":"Weibing Zeng , Zhendong Wang , Shuxin Yang , Daojing He , Sammy Chan","doi":"10.1016/j.adhoc.2025.103829","DOIUrl":"10.1016/j.adhoc.2025.103829","url":null,"abstract":"<div><div>In wireless sensor networks (WSN), clustered routing protocols usually require periodic re-clustering to balance the energy among nodes. Frequent clustering aggravates the energy consumed by the network into clusters and ignores whether the network needs to be re-clustered every round, cluster head (CH) rotation is proposed to counter this problem. In this paper, we propose an intra-cluster multi-hop based CH rotation (ICMH-CHR) protocol for WSN. This protocol sets two thresholds based on the average residual energy in the cluster. These thresholds are used to dynamically regulate the network re-clustering and CH rotation strategies, respectively, to reduce the number of network re-clustering and avoid the premature death of CH nodes. In addition, the intra-cluster multi-hop strategy is used to solve the problem of CHs moving away from the cluster center due to intra-cluster rotation. For inter-cluster communication, the CH selects the most energy-efficient relay node by measuring the distance to other CHs through RSSI. Simulation results show that the proposed ICMH-CHR effectively extends the network lifetime and performs well in load balancing compared to LEACH, EEUC, T-LEACH, EEHCCP, and EAUCA.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"173 ","pages":"Article 103829"},"PeriodicalIF":4.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642154","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 : 2025-03-15DOI: 10.1016/j.adhoc.2025.103828
Mai Cuong Tho , Le Huu Binh , Tu T. Vo
{"title":"GPSR-CB: A novel routing algorithm for FANET using cross-layer models in combination with multi-level backbone UAV","authors":"Mai Cuong Tho , Le Huu Binh , Tu T. Vo","doi":"10.1016/j.adhoc.2025.103828","DOIUrl":"10.1016/j.adhoc.2025.103828","url":null,"abstract":"<div><div>This paper presents GPSR-CB, a cross-layer approach to enhance the performance of greedy forwarding in the Greedy Perimeter Stateless Routing (GPSR) protocol for flying ad-hoc networks (FANETs) with multi-level backbone unmanned aerial vehicle (UAV). The cross-layer design combines adaptive transmission power control, link quality monitoring to assess and select reliable links, and ACK-based feedback mechanisms to address routing-void challenges in location-based routing. Specifically, GPSR-CB leverages a multi-level backbone UAV to support the greedy forwarding mode, whereas power control, link quality assessment, and ACK-based feedback help mitigate the changes in network topology, unstable links, and unreliable channels, particularly in FANET environments with noise and interference. Through comprehensive simulations conducted using OMNeT++, we demonstrate that GPSR-CB outperforms the compared protocols in terms of packet delivery ratio, network throughput, and power consumption.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"173 ","pages":"Article 103828"},"PeriodicalIF":4.4,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643748","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":"DRL-based Task Scheduling Scheme in Vehicular Fog Computing: Cooperative and mobility aware approach","authors":"Mekala Ratna Raju , Sai Krishna Mothku , Manoj Kumar Somesula","doi":"10.1016/j.adhoc.2025.103819","DOIUrl":"10.1016/j.adhoc.2025.103819","url":null,"abstract":"<div><div>In the realm of Vehicular Fog Computing (VFC), the dynamic nature of vehicular networks presents substantial challenges for effective task scheduling and resource allocation. The rapidly changing mobility patterns of vehicles complicate the management of service delays for vehicular requests and the energy usage of servers. Our research addresses these challenges by focusing on cooperative and mobility-aware task scheduling in VFC, aiming to optimize fog server performance and ensure the timely processing of vehicular tasks. We model vehicle mobility using a Markov renewal process to determine vehicle movements. The task scheduling problem is formulated as a mixed-integer non-linear programming (MINLP) problem, considering constraints such as task deadlines, resource limits, and vehicle mobility. To tackle this problem, we utilize a deep reinforcement learning (DRL) technique, which allows for adaptive and intelligent task scheduling and resource allocation. Through extensive simulations, our approach demonstrates significant improvements over existing benchmark techniques, achieving a 12% reduction in service delays and a 14% decrease in energy consumption.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"173 ","pages":"Article 103819"},"PeriodicalIF":4.4,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643830","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 : 2025-03-12DOI: 10.1016/j.adhoc.2025.103832
Tao He , Ya-Peng Zhang , Ming-Ze Yan , Wei-Ping Luo , Shuang-Bao Ma
{"title":"A hierarchical DV-Hop localization algorithm based on RSSI with self-localization weighted offset correction","authors":"Tao He , Ya-Peng Zhang , Ming-Ze Yan , Wei-Ping Luo , Shuang-Bao Ma","doi":"10.1016/j.adhoc.2025.103832","DOIUrl":"10.1016/j.adhoc.2025.103832","url":null,"abstract":"<div><div>The classic DV-Hop (Distance Vector Hop) localization algorithm in wireless sensor networks not only has poor performance in non-regular random topology networks, but also relies heavily on the local network topology for localization accuracy in uniform random topology networks. To address this issue, this paper proposes a hierarchical DV-Hop localization algorithm (H-DV Hop RSIWOC) based on RSSI and self-positioning weighted offset correction. The best error estimation of the whole network is deduced by self-localization of the anchor nodes; the unknown nodes in the whole network are graded and localized level by level, and for the initial localization results, the best estimation error circle and RSSI circle are constructed, and the offset vectors and offset weights are computed, and the weighted offset corrections are applied to the initial localization coordinates. The simulation results indicate that within an identical experimental setting, compared with the classical DV-Hop algorithm and other improved algorithms, H-DV-Hop-RSIWOC possesses higher localization accuracy and stability in non-regular random topological networks, and also shows excellent algorithmic performance in uniform random topological networks.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"173 ","pages":"Article 103832"},"PeriodicalIF":4.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143680670","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":"Asynchronous time-based indoor localization systems—Comparative analysis under realistic industrial-oriented conditions","authors":"Rubén Ferrero-Guillén , Javier Díez-González , Rubén Álvarez , Joaquín Torres-Sospedra , Hilde Perez , Adriano Moreira","doi":"10.1016/j.adhoc.2025.103816","DOIUrl":"10.1016/j.adhoc.2025.103816","url":null,"abstract":"<div><div>The growing need for accurate localization in increasingly interconnected industrial environments has driven research towards developing new indoor localization systems. This work analyzes and compares three asynchronous localization methods based on the Two-Way-Ranging (TWR) protocol: Single-Sided TWR (SS-TWR), Symmetric Double-Sided TWR (SDS-TWR), and Alternative Double-Sided TWR (AltDS-TWR) in addition to the Asynchronous Time Difference of Arrival (A-TDOA) system. Similar comparisons have been previously reported, however, these only take into consideration clock-associated errors and unrealistic test conditions, thus overlooking the impact of signal paths required by each method, therefore reaching conclusions far from those expected in real applications. In this paper, we propose a more complete and fair comparison among these four asynchronous systems. For this purpose, we propose a clock, noise, and multipath error characterization for each localization system to perform a realistic comparison over multiple industrial scenarios where Autonomous Mobile Robots freely navigate. In order to ensure a fair comparison, a sensor distribution optimization has been carried out for attaining the best achievable performance of each analyzed system. Results show that the selection of the best localization system may depend on the scenario and application conditions as well as the deployment budget. Nevertheless, results from the AltDS-TWR method highlight the potential of this system, yet further research should be conducted to verify the influence of moving targets for this TWR method.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"173 ","pages":"Article 103816"},"PeriodicalIF":4.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ad Hoc NetworksPub Date : 2025-03-10DOI: 10.1016/j.adhoc.2025.103830
Vidyapati Jha, Priyanka Tripathi
{"title":"Remediation of chaos in cognitive Internet of Things sensor network","authors":"Vidyapati Jha, Priyanka Tripathi","doi":"10.1016/j.adhoc.2025.103830","DOIUrl":"10.1016/j.adhoc.2025.103830","url":null,"abstract":"<div><div>The cognitive Internet of Things (CIoT) is an emerging field that integrates cognitive capabilities into IoT systems, enabling devices to learn, reason, and make autonomous decisions. This advancement enhances the intelligence and adaptability of IoT applications. However, the vast, unpredictable, diversified, and time-dependent nature of data generated by these applications presents significant challenges in data management. Without a cognitively inspired framework, effectively managing this complex data becomes increasingly difficult. The behaviour of the data stream should be cognitively assessed in a number of scenarios to ensure that CIoT applications continue to operate smoothly and exhibit non-chaotic behaviour. In order to address it, this research proposes a novel design to detect the chaotic behaviour of the multisensory data stream and further tries to step it up to correct and return from a chaotic state to a non-chaotic state. In the proposed design, the Lyapunov exponent is computed for the detection of chaotic behaviour in the massive heterogeneous data stream, and if the system is found chaotic, then it designs the three novel algorithms, i.e., total variation (TV) regularization, maximum a posteriori (MAP) estimation, and informative value replacement for chaotic sensor data of the system from returning to non-chaotic state. This is done in a computationally efficient manner so that there is no extra burden posed on the fusion center. The suggested algorithm outperforms competing algorithms (accuracy > 99%) in an experimental evaluation, which is carried out utilizing environmental data spanning 21.25 years and uncovered by cross-validation using several measures.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"173 ","pages":"Article 103830"},"PeriodicalIF":4.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143680669","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":"Securing cross-domain data access with decentralized attribute-based access control","authors":"Ahmad Salehi Shahraki , Carsten Rudolph , Hooman Alavizadeh , A.S.M. Kayes , Wenny Rahayu , Zahir Tari","doi":"10.1016/j.adhoc.2025.103807","DOIUrl":"10.1016/j.adhoc.2025.103807","url":null,"abstract":"<div><div>In attribute-based access control (ABAC), access to resources depends on the specific attributes of the entity requesting access. Existing ABAC models primarily depend on local attribute authorities to define and confirm attributes, which makes it challenging to support access decisions cross-domains without introducing centralization. Centralized solutions often conflict with individual domains’ security, privacy, and control requirements and, if compromised for any reason, can impact access to large datasets across participating domains. This paper introduces a novel access control model for cross-domain environments that significantly reduces central control. Our decentralized ABAC (D-ABAC) model uses group signature techniques to exchange attribute information securely and privately within cross-domains. Each domain maintains its own policies and attribute authorities, reducing the need for global trust or centralization to mutual trust between attribute authorities. We further design and implement a proof-of-concept system to demonstrate the practical feasibility of our proposed system for the collaborative and secure sharing of healthcare data in cross-domain environments. The proposed system model enhances security, scalability, and privacy in cross-domain settings, making it suitable for sensitive environments such as healthcare.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"173 ","pages":"Article 103807"},"PeriodicalIF":4.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ad Hoc NetworksPub Date : 2025-03-06DOI: 10.1016/j.adhoc.2025.103805
Shoulan Chen, Kaimin Wei, Tingrui Pei, Saiqin Long
{"title":"AoI-Guaranteed UAV Crowdsensing: A UGV-assisted deep reinforcement learning approach","authors":"Shoulan Chen, Kaimin Wei, Tingrui Pei, Saiqin Long","doi":"10.1016/j.adhoc.2025.103805","DOIUrl":"10.1016/j.adhoc.2025.103805","url":null,"abstract":"<div><div>Unmanned Aerial Vehicles (UAVs), with their excellent environmental adaptability and flexible maneuverability, are increasingly being deployed in smart city applications for data collection. The Age of Information (AoI) is essential in these applications. Prior research on AoI has predominantly focused on static task scenarios, often overlooking the dynamics of task arrivals. For this reason, we propose an unmanned ground vehicle (UGV)-assisted deep reinforcement learning approach (U-DRL), which employs key factors affecting AoI to mitigate the AoI of data in dynamic task scenarios. We use EfficientNet, a state-of-the-art neural network architecture, to effectively extract features from dynamic task arrival scenarios. Based on these features, we utilize an intrinsic reward module (IRM) to swiftly process the input encapsulating global information, optimizing flight paths and enabling the exploration of expanded areas by UAVs. In addition, we leverage the active mobility of UGVs to recharge UAVs timely, thereby maximizing the flight time of UAVs. Through an extensive series of experiments, we validate the effectiveness of U-DRL. The experimental results demonstrate that U-DRL outperforms comparative algorithms in key performance metrics, significantly reducing the AoI of data, with breakthroughs of 54.14% and 67.90% in two real-world maps.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"173 ","pages":"Article 103805"},"PeriodicalIF":4.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592995","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 : 2025-03-05DOI: 10.1016/j.adhoc.2025.103797
Zhigang Jin, Ying Wang, Jiawei Liang, Haoyong Li, Yishan Su
{"title":"Energy-efficient Nonuniform Cluster-based Routing Protocol with Q-Learning for UASNs","authors":"Zhigang Jin, Ying Wang, Jiawei Liang, Haoyong Li, Yishan Su","doi":"10.1016/j.adhoc.2025.103797","DOIUrl":"10.1016/j.adhoc.2025.103797","url":null,"abstract":"<div><div>Underwater Acoustic Sensor Networks (UASNs) are widely used in various fields. The limited energy of underwater nodes and the difficulty of replenishment constrain the lifetime of UASNs. Thus, it is important to effectively balance energy consumption and design a routing protocol that ensures efficient data transmission and extends network lifetime. Cluster routing protocol is widely recognized as an energy efficient strategy for UASNs. However, it faces challenges including “hotspot” issues caused by nodes frequently acting as cluster heads (CHs) and forwarding packets, as well as energy inefficiency resulting from packet conflicts and redundant transmissions. Therefore, we propose an Energy-efficient Nonuniform Cluster-based Routing Protocol with Q-Learning (ENCRQ) to balance energy consumption and improve packet forwarding efficiency. In the CH election phase, a “CH competitiveness” function is created based on node weighted density and residual energy. Nodes outside the sink neighborhood adaptively compete for CHs based on this function, aiming to achieve an uneven distribution of CHs and balance energy consumption. Meanwhile, nodes within the sink neighborhood remain sleeping to further reduce energy consumption. In the inter-cluster routing phase, the forwarding area is hierarchically divided based on node depth and distance to the sink node. The optimal forwarding area is adaptively adjusted to form the next-hop candidate set. On this basis, holding time is designed for candidate nodes based on Q-Learning technique to prioritize forwarding, minimizing packet conflicts and redundant transmissions, thereby enhancing network transmission efficiency. Simulation results show that compared with LEACH, QELAR and QHUC, ENCRQ has significant improvement in terms of network lifetime, energy balance and energy efficiency.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"173 ","pages":"Article 103797"},"PeriodicalIF":4.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577564","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 : 2025-03-05DOI: 10.1016/j.adhoc.2025.103815
Mauricio González-Palacio , Liliana González-Palacio , José Aguilar , Long Bao Le
{"title":"WSN-based wildlife localization framework in dense forests through optimization techniques","authors":"Mauricio González-Palacio , Liliana González-Palacio , José Aguilar , Long Bao Le","doi":"10.1016/j.adhoc.2025.103815","DOIUrl":"10.1016/j.adhoc.2025.103815","url":null,"abstract":"<div><div>Wildlife in forests is threatened by land use changes, requiring tracking to characterize movement patterns and propose preservation policies. The positioning uses GPS-based collars (End Nodes (ENs)), which are energy-consuming and require a line of sight with the satellites, a condition rarely fulfilled in forests. It motivates using Wireless Sensor Networks, which rely on the Received Signal Strength Indicator (RSSI) and Time of Flight (ToF) to determine the distance between the EN and Anchor Nodes (ANs) with known positions and, subsequently, apply trilateration. However, existing approaches may have significant errors due to multipath and shadow fading caused by dense canopies. Thus, this paper proposes a three-step framework to address these limitations. First, it optimizes the ANs positions, increasing the redundancy of trilateration and coverage, enhancing the likelihood of accurate localization, and ensuring sufficient data to mitigate adverse channel effects. Second, it presents an optimization problem that minimizes the variance of distance estimation since the associated errors can increase exponentially. Finally, it scores the ANs with the most reliable position estimations to mitigate the effects of outliers. Numerical studies show that our optimized AN placement improves coverage by 25% compared to random or equispaced strategies. The distance estimator achieves a Mean Average Percentage Error (MAPE) below 7%, outperforming the Wiener-based estimator at 20%. Finally, our scoring method reduced MAPE to 5.53% with a standard deviation of 7.15% compared with the median strategy that achieved 9.66% and a standard deviation of 15.87% when ten ANs are placed in a region of 100 km<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"173 ","pages":"Article 103815"},"PeriodicalIF":4.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577685","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}