Ad Hoc Networks最新文献

{"title":"A survey on massive IoT for water distribution systems: Challenges, simulation tools, and guidelines for large-scale deployment","authors":"Antonino Pagano ,&nbsp;Domenico Garlisi ,&nbsp;Ilenia Tinnirello ,&nbsp;Fabrizio Giuliano ,&nbsp;Giovanni Garbo ,&nbsp;Mariana Falco ,&nbsp;Francesca Cuomo","doi":"10.1016/j.adhoc.2024.103714","DOIUrl":"10.1016/j.adhoc.2024.103714","url":null,"abstract":"<div><div>This survey explores the convergence of Internet of Things (IoT) technologies with Water Distribution Systems (WDSs), focusing on large-scale deployments and the role of edge computing (EC). Effective water management increasingly relies on IoT monitoring, resulting in massive deployments and the generation of Big Data. While previous research has examined these topics individually, this work integrates them into a comprehensive analysis. We systematically reviewed 255 studies on IoT in WDS, identifying key challenges such as interoperability, scalability, energy efficiency, network coverage, and reliability. We also examined technologies like LPWAN and the growing use of EC for real-time data processing. In large-scale WDS scenarios, where vast amounts of data are generated, we highlighted the importance of technologies like NB-IoT, SigFox, and LoRaWAN due to their low power consumption and wide coverage. Based on our findings, we provide guidelines for sustainable, large-scale IoT deployment in WDS, emphasizing the need for edge data processing to reduce cloud dependency, improve scalability, and enable smarter cities and digital twins.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"168 ","pages":"Article 103714"},"PeriodicalIF":4.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142719626","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}

{"title":"RIS-assisted D2D communication in the presence of interference: Outage performance analysis and DNN-based prediction","authors":"Hamid Amiriara ,&nbsp;Farid Ashtiani ,&nbsp;Mahtab Mirmohseni ,&nbsp;Masoumeh Nasiri-Kenari ,&nbsp;Behrouz Maham","doi":"10.1016/j.adhoc.2024.103703","DOIUrl":"10.1016/j.adhoc.2024.103703","url":null,"abstract":"<div><div>This paper analyzes the performance of reconfigurable intelligent surface (RIS)-assisted device-to-device (D2D) communication systems, focusing on addressing co-channel interference, a prevalent issue due to the frequency reuse of sidelink in the underlay in-band D2D communications. In contrast to previous studies that either neglect interference or consider it only at the user, our research investigates a performance analysis in terms of outage probability (OP) for RIS-assisted D2D communication systems considering the presence of interference at both the user and the RIS. More specifically, we introduce a novel integral-form expression for an exact analysis of OP. Additionally, we present a new accurate approximation expression for OP, using the gamma distributions to approximate the fading of both desired and interference links, thereby yielding a closed-form expression. Nevertheless, both derived expressions, i.e., the exact integral-form and the approximate closed-form, contain special functions, such as Meijer’s G-function and the parabolic cylinder function, which complicate real-time OP analysis. To circumvent this, we employ a deep neural network (DNN) for real-time OP prediction, trained with data generated by the exact expression. Moreover, we present a tight upper bound that quantifies the impact of interference on achievable diversity order and coding gain. We validate the derived expressions through Monte Carlo simulations. Our analysis reveals that while interference does not affect the system’s diversity order, it significantly degrades the performance by reducing the coding gain. The results further demonstrate that increasing the number of RIS’s reflecting elements is an effective strategy to mitigate the adverse effects of the interference on the system performance.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"167 ","pages":"Article 103703"},"PeriodicalIF":4.4,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702560","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":"Age and energy aware data collection scheme for urban flood monitoring in UAV-assisted Wireless Sensor Networks","authors":"Mekala Ratna Raju ,&nbsp;Sai Krishna Mothku ,&nbsp;Manoj Kumar Somesula ,&nbsp;Srilatha Chebrolu","doi":"10.1016/j.adhoc.2024.103704","DOIUrl":"10.1016/j.adhoc.2024.103704","url":null,"abstract":"<div><div>Wireless Sensor Networks (WSNs) have become pivotal in numerous applications, including environmental monitoring, precision agriculture, and disaster response. In the context of urban flood monitoring, utilizing unmanned aerial vehicles (UAVs) presents unique challenges due to the dynamic and unpredictable nature of the environment. The primary challenges involve designing strategies that maximize data collection while minimizing the Age of Information (AoI) to ensure timely and accurate decision-making. Efficient data collection is crucial to capturing all relevant information and providing a comprehensive understanding of flood dynamics. Simultaneously, reducing AoI is essential, as outdated data can lead to delayed or incorrect responses, potentially worsening the situation. Addressing these challenges is critical for the effective use of WSNs in urban flood monitoring. Initially, we formulate the problem as a mixed integer non-linear programming (MINLP) problem. Further, it is solved using a Lagrangian-based branch and bound technique by converting it into an unconstrained problem. Then, for large-scale WSN, we propose a hybrid optimization technique which combines a genetic algorithm with a particle swarm optimization technique to simultaneously maximize the data collection and reduce the AoI of the collected data with the constraint of energy consumption of the UAVs. Simulation results demonstrate that our proposed algorithm outperforms existing approaches in terms of both data collection and AoI.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"168 ","pages":"Article 103704"},"PeriodicalIF":4.4,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142719624","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":"Cross-layer UAV network routing protocol for spectrum denial environments","authors":"Siyue Zheng ,&nbsp;Xiaojun Zhu ,&nbsp;Zhengrui Qin ,&nbsp;Chao Dong","doi":"10.1016/j.adhoc.2024.103702","DOIUrl":"10.1016/j.adhoc.2024.103702","url":null,"abstract":"<div><div>Unmanned Aerial Vehicles (UAVs), which connect to one another over wireless networks, are being used in warfare more frequently. Nevertheless, adversarial interference has the potential to disrupt wireless communication, and the UAV routing methods in use today struggle to handle interference. In this paper, we propose a Cross-Layer UAV Link State Routing protocol, CLUN-LSR, to combat against jamming attacks. CLUN-LSR features three designs. First, it obtains real-time spectrum status from the link layer. Such capabilities are provided by many existing radios, especially the ones in military applications, but are ignored by traditional routing protocols. Second, based on the cross-layer information, CLUN-LSR adds efficient routing functions during routing, including the use of the number of two-hop neighbor nodes as a metric for route selection. Third, CLUN-LSR selects nodes that are not in the interference area, thereby reducing network interruptions and improving data transmission efficiency. All table-driven routing protocols can apply CLUN-LSR for better performance. We apply CLUN-LSR to the existing routing protocol MP-OLSR and simulate it using a commercial network simulator. Simulation results show that our innovative routing protocol demonstrates superior performance compared to existing table-driven routing methods, particularly in terms of packet transmission rate and overall throughput.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"167 ","pages":"Article 103702"},"PeriodicalIF":4.4,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656957","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":"JamBIT: RL-based framework for disrupting adversarial information in battlefields","authors":"Muhammad Salman ,&nbsp;Taehong Lee ,&nbsp;Ali Hassan ,&nbsp;Muhammad Yasin ,&nbsp;Kiran Khurshid ,&nbsp;Youngtae Noh","doi":"10.1016/j.adhoc.2024.103697","DOIUrl":"10.1016/j.adhoc.2024.103697","url":null,"abstract":"<div><div>During battlefield operations, military radios (hereafter nodes) exchange information among various units using a mobile ad-hoc network (MANET) due to its infrastructure-less and self-healing capabilities. Adversarial cyberwarfare plays a crucial role in modern combat by disrupting communication between critical nodes (i.e., nodes mainly responsible for propagating important information) to gain dominance over the opposing side. However, determining critical nodes within a complex network is an NP-hard problem. This paper formulates a mathematical model to identify important links and their connected nodes, and presents JamBIT, a reinforcement learning-based framework with an encoder–decoder architecture, for efficiently detecting and jamming critical nodes. The encoder transforms network structures into embedding vectors, while the decoder assigns a score to the embedding vector with the highest reward. Our framework is trained and tested on custom-built MANET topologies using the Named Data Networking (NDN) protocol. JamBIT has been evaluated across various scales and weighting methods for both connected node and network dismantling problems. Our proposed method outperformed existing RL-based baselines, with a 24% performance gain for smaller topologies (50–100 nodes) and 8% for larger ones (400–500 nodes) in connected node problems, and a 7% gain for smaller topologies and 15% for larger ones in network dismantling problems.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"167 ","pages":"Article 103697"},"PeriodicalIF":4.4,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656956","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":"Wireless sensor networks and machine learning centric resource management schemes: A survey","authors":"Gururaj S. Kori ,&nbsp;Mahabaleshwar S. Kakkasageri ,&nbsp;Poornima M. Chanal ,&nbsp;Rajani S. Pujar ,&nbsp;Vinayak A. Telsang","doi":"10.1016/j.adhoc.2024.103698","DOIUrl":"10.1016/j.adhoc.2024.103698","url":null,"abstract":"<div><div>Wireless Sensor Network (WSN) is a heterogeneous, distributed network composed of tiny cognitive, autonomous sensor nodes integrated with processor, sensors, transceivers, and software. WSNs offer much to the sensing world and are deployed in predefined geographical areas that are out of human interventions to perform multiple applications. Sensing, computing, and communication are the main functions of the sensor node. However, WSNs are mainly constrained by limited resources such as power, computational speed, memory, sensing capability, communication range, and bandwidth. WSNs when shared for multiple tasks and applications, resource management becomes a challenging task. Hence, effective utilization of available resources is a critical issue to prolong the life span of sensor network. Current research has explored various methods for resources management in WSNs, but most of these approaches are traditional and often fall short in addressing the resource management issues during real-time applications. Resource management schemes involves in resource identification, resource scheduling, resource allocation, resource utilization and monitoring, etc. This paper aims to fill the gap by reviewing and analysing the latest Computational Intelligence (CI) techniques, particularly Machine Learning (ML) and Artificial Intelligence (AI). AIML has been applied to countless humdrum and complex problems arising in WSN operation and resource management. AIML algorithms increase the efficiency of the network and speed up the computational time with optimized utilization of the available resources. Therefore, this is a timely perspective on the ramifications of machine learning algorithms for autonomous WSN establishment, operation, and resource management.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"167 ","pages":"Article 103698"},"PeriodicalIF":4.4,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656955","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":"V2X application server and vehicle centric distribution of commitments for V2V message authentication","authors":"Mujahid Muhammad ,&nbsp;Ghazanfar Ali Safdar","doi":"10.1016/j.adhoc.2024.103701","DOIUrl":"10.1016/j.adhoc.2024.103701","url":null,"abstract":"<div><div>Safety applications, such as intersection collision warnings and emergency brake warnings, enhance road safety and traffic efficiency through periodic broadcast messages by vehicles and roadside infrastructure. While the Elliptic Curve Digital Signature Algorithm (ECDSA) is a widely used security approach, its performance limitations make it unsuitable for time-critical safety applications. As such, a symmetric cryptography-based technique called Timed Efficient Stream Loss-tolerant Authentication (TESLA) offers a viable alternative. However, applying standard TESLA in the context of vehicle-to-vehicle (V2V) communications has its own challenges. One challenge is the difficulty of distributing authentication information called commitments in the highly dynamic V2V environment. In this paper, we propose two novel solutions to this problem, namely, V2X Application Server (VAS)-centric and vehicle-centric. The former is an application-level solution that involves selective unicasting of commitments to vehicles by a central server, the VAS, and the latter is a reactive scheme that involves the periodic broadcast of commitments by the vehicles themselves. Extensive simulations are conducted using representatives of the real V2V environment to evaluate the performance of these approaches under different traffic situations; as well as performance comparison with a state-of-the-art distribution solution. The simulation results indicate that the VAS-centric solution is preferable for use in a TESLA-like V2V security scheme. It demonstrates desirable features, including timely delivery of commitments and high distribution efficiency, with over 95 % of commitments sent by the VAS are associated with relevant safety messages when compared with the vehicle-centric and state-of-the-art solutions. Formal security analysis, conducted using the Random Oracle Model (ROM), proves the correctness of our proposed distribution schemes. Additionally, an informal security analysis shows the resilience of the proposed schemes against various attacks, including impersonation, replay, and bogus commitment messages.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"167 ","pages":"Article 103701"},"PeriodicalIF":4.4,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656959","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":"Deep learning with synthetic data for wireless NLOS positioning with a single base station","authors":"Hrant Khachatrian ,&nbsp;Rafayel Mkrtchyan ,&nbsp;Theofanis P. Raptis","doi":"10.1016/j.adhoc.2024.103696","DOIUrl":"10.1016/j.adhoc.2024.103696","url":null,"abstract":"<div><div>Traditional wireless positioning methods exhibit limitations in the face of signal distortions prevalent in non-line-of-sight (NLOS) conditions, especially in the case of a single base station (BS). Moreover, the adoption of deep learning (DL) methodologies has lagged behind, largely due to the challenges associated with generating real-world datasets. In this paper, we present a comprehensive approach leveraging DL over large-scale synthetic wireless datasets (the recent WAIR-D in this case, which was co-produced by Huawei) to overcome such challenges and address the case of single-BS NLOS positioning. The aim of the paper is to practically explore the extent to which synthetic wireless datasets can help to achieve the positioning objectives. Towards this direction, we develop a map-based representation of a radio link, demonstrating its synergistic effect with feature-based representations in MLPs. Furthermore, we introduce a UNet-based neural model which incorporates input maps and radio link representations and generates as output a heatmap of potential device positions. This model achieves an 11.3-meter RMSE and 76.5% prediction accuracy on NLOS examples (1.5-meter, 99.9% for LOS) assuming perfect information, surpassing the MLP baseline by 47%. Finally, we provide further insights into the model’s ability to predict top device positions, the characteristics of predicted heatmaps as indicators of confidence, and the crucial role of map availability and radio path angles in model performance, thus revealing an unconventional perspective on incorrect predictions.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"167 ","pages":"Article 103696"},"PeriodicalIF":4.4,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593051","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}

{"title":"Transitive reasoning: A high-performance computing model for significant pattern discovery in cognitive IoT sensor network","authors":"Vidyapati Jha,&nbsp;Priyanka Tripathi","doi":"10.1016/j.adhoc.2024.103700","DOIUrl":"10.1016/j.adhoc.2024.103700","url":null,"abstract":"<div><div>Current research on the Internet of Things (IoT) has given rise to a new field of study called cognitive IoT (CIoT), which aims to incorporate cognition into the designs of IoT systems. Consequently, the CIoT inherits specific attributes and challenges from IoT. The CIoT applications generate vast, diverse, constantly changing, and time-dependent data due to the billions of devices involved. The efficient operation of these CIoT systems requires the extraction of valuable insights from vast data sources in a computationally efficient manner. Therefore, this study proposes transitive reasoning to glean significant concepts and patterns from a 21.25-year environmental dataset. To reduce the effects of missing entries, the proposed methodology includes a grouping of data using probabilistic clustering and applying total variance regularization in the alternate direction method of multipliers (ADMM) to regularize the sensory data. As a result, noisy entries will be less conspicuous. Afterward, it calculates the transitional plausibility value for each cluster using the transited value and then turns it into binary data to create concept lattices. In addition, each concept that is formed is assigned a weight, and the concept with the largest transitive strength value is chosen, followed by calculating the mean value. Therefore, this pattern is seen as significant. Experimental results on 21.25-year environmental data show an accuracy of over 99.5%, outperforming competing methods, as shown by cross-validation using multiple metrics.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"167 ","pages":"Article 103700"},"PeriodicalIF":4.4,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577912","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":"BLE-based sensors for privacy-enabled contagious disease monitoring with zero trust architecture","authors":"Akshay Madan ,&nbsp;David Tipper ,&nbsp;Balaji Palanisamy ,&nbsp;Mai Abdelhakim ,&nbsp;Prashant Krishnamurthy ,&nbsp;Vinay Chamola","doi":"10.1016/j.adhoc.2024.103693","DOIUrl":"10.1016/j.adhoc.2024.103693","url":null,"abstract":"<div><div>Digital contact tracing is an important technique to stop the spread of infectious diseases. Due to data integrity, and privacy problems, smartphone apps suffer from low adoption rates. Also, these apps excessively drain batteries and sometimes give false alarms. They are also not able to detect <em>fomite-based</em> contacts or <em>indirect</em> contacts. BEacon-based Contact Tracing or BECT is a contact tracing framework that uses Bluetooth beacon sensors that periodically broadcast “tokens” to close users. Users who are positively diagnosed voluntarily provide their tokens to the health authority-maintained server for tracing contacts. We target environments like campuses like companies, colleges, and prisons, where use can be mandated thus mitigating low adoption rate issues. This approach detects indirect contacts and preserves the device’s battery. We create a simulation to examine the proposed framework’s performance in detecting indirect contacts and compare it with the existing apps’ framework. We also analyze the cost and power consumption for our technique and assess the placement strategies for beacons. Incorporating Zero Trust Architecture enhances the framework’s security and privacy.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"167 ","pages":"Article 103693"},"PeriodicalIF":4.4,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577911","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}