Ad Hoc NetworksPub Date : 2024-08-13DOI: 10.1016/j.adhoc.2024.103630
{"title":"A multi-objective Roadside Units deployment strategy based on reliable coverage analysis in Internet of Vehicles","authors":"","doi":"10.1016/j.adhoc.2024.103630","DOIUrl":"10.1016/j.adhoc.2024.103630","url":null,"abstract":"<div><p>The deployment of Roadside Units (RSUs) in the Cellular-Vehicle to Everything enabled Internet of Vehicles is crucial for the transition from individual intelligence of vehicles to collective intelligence of vehicle-road collaboration. In this paper, we focus on improving the adaptability of RSU deployment to real scenarios, and optimizing deployment costs and vehicle-oriented service performance. The RSU deployment problem is modeled as a Multi-objective Optimization Problem (MOP), with a cost model integrating the purchase and installation costs, and a service-oriented Quality of Service (QoS) model adopting the total time the RSUs cover the vehicles as the evaluation metric. Specifically, we propose an RSU reliable coverage analysis method based on Packet Delivery Ratio model to estimate the coverage distances in different scenarios, which will be used in QoS calculation. Then, an evolutionary RSU deployment algorithm is designed to solve the MOP. The performance of the proposed method is simulated and discussed in real road network and dynamic scenarios. The results prove that our method outperforms the baseline method in terms of significant cost reduction and total coverage time improvement.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142049636","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 : 2024-08-12DOI: 10.1016/j.adhoc.2024.103599
{"title":"Exploiting stream scheduling in QUIC: Performance assessment over wireless connectivity scenarios","authors":"","doi":"10.1016/j.adhoc.2024.103599","DOIUrl":"10.1016/j.adhoc.2024.103599","url":null,"abstract":"<div><p>The advent of wireless technologies has led to the development of novel services for end-users, with stringent needs and requirements. High availability, very high throughput, low latency, and reliability are all of them crucial performance parameters. To address these demands, emerging technologies, such as non-terrestrial networks or millimeter wave (mmWave), are being included in 5G and Beyond 5G (B5G) specifications. mmWave enables massive data transmissions, at the expense of a more hostile propagation, typical for high frequency bands. Consequently, the inherent instability of the physical channel significantly affects the upper layers of the protocol stack, resulting in congestion and data losses, which might strongly hinder the overall communication performance. These challenges can be addressed not only at the link layer, but at any affected layer. QUIC is a new transport protocol designed to reduce communications latency in many ways. Among other features, it enables the use of multiple streams to effectively manage data flows sent through its underlying UDP socket. This paper introduces an implementation of priority-based stream schedulers along with the design of a flexible interface. Exploiting the proposed approach, applications are able to set the required scheduling scheme, as well as the stream priorities. The feasibility of the proposed approach is validated through an extensive experiment campaign, which combines Docker containers, the ns-3 simulator and the Mahimahi framework, which is exploited to introduce realistic mmWave channel traces. The results evince that an appropriate stream scheduler can indeed yield lower delays for time-sensitive applications by up to 36% under unreliable conditions.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1570870524002105/pdfft?md5=460c9f73b298581eb5c0a0504f183755&pid=1-s2.0-S1570870524002105-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141978838","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 : 2024-08-10DOI: 10.1016/j.adhoc.2024.103629
{"title":"ECMSH: An Energy-efficient and Cost-effective data harvesting protocol for Mobile Sink-based Heterogeneous WSNs using PSO-TVAC","authors":"","doi":"10.1016/j.adhoc.2024.103629","DOIUrl":"10.1016/j.adhoc.2024.103629","url":null,"abstract":"<div><p>Efficient energy consumption is crucial in Wireless Sensor Networks (WSNs). Uncontrolled energy usage can lead to the hotspot issue, hindering network lifetime and successful packet delivery. Sink mobility has been suggested as a solution, but it comes with challenges such as high data gathering delay and poor packet reception. These problems stem from the short contact time of nodes with the Mobile Sink (MS). To tackle these issues, we present an MS-based heterogeneous WSN with super and normal nodes. Most previous studies only considered the energy heterogeneity of sensors. These methods also suffered from different issues such as fixed MS tours, including inappropriate criteria in cluster construction, proposing greedy schemes, and employing basic metaheuristic algorithms. In our proposed model, super nodes are richer in initial energy and transmission range than normal sensors. In each round, the nodes are organized into clusters, and the MS visits the Cluster Heads (CHs) to gather data packets. Super nodes, owing to their elevated initial energy, are more adept at executing energy-sensitive tasks compared to normal sensors. Additionally, as CH, super nodes extend the contact time with the MS due to their longer transmission range, delivering more packets. The clusters are constructed using a variant of Particle Swarm Optimization (PSO), namely PSO-TVAC. We empower this method with effective initialization and decoding methods. Furthermore, we propose a heuristic intra-cluster multi-hop routing algorithm to enhance network lifetime. Our other contribution is to propose an efficient algorithm to determine the time to reconfigure the network, while the other algorithms mainly reconfigure the WSN periodically. Simulation results demonstrate superior performance compared to state-of-the-art algorithms, showcasing lower energy consumption, higher energy efficiency, higher lifetime, reduced packet delivery delay, and higher number of received packets by 30%, 38.2%, four times, 20.6%, and 22.6%, respectively.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141990906","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 : 2024-08-10DOI: 10.1016/j.adhoc.2024.103624
{"title":"Corrigendum to “Federated Learning assisted framework to periodically identify user communities in urban space” [Ad Hoc Networks 163 (2024) pp. 1-21/103589]","authors":"","doi":"10.1016/j.adhoc.2024.103624","DOIUrl":"10.1016/j.adhoc.2024.103624","url":null,"abstract":"","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S157087052400235X/pdfft?md5=770a0dc2de0a497c0572d54beb2b7660&pid=1-s2.0-S157087052400235X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142167575","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 : 2024-08-08DOI: 10.1016/j.adhoc.2024.103626
{"title":"Exploring model transferability in ML-integrated RPL routing for smart grid communication: A comparative analysis across urban scenarios","authors":"","doi":"10.1016/j.adhoc.2024.103626","DOIUrl":"10.1016/j.adhoc.2024.103626","url":null,"abstract":"<div><p>Machine learning (ML) techniques have demonstrated considerable effectiveness when integrated into routing protocols to enhance the performance of Smart Grid Networks. However, their performance across diverse real-world scenarios remains a topic of exploration. In this study, we evaluate the performance and transferability of four ML models—Long Short-Term Memory (LSTM), Feedforward Neural Network (FF), Decision Trees, and Naive Bayes—across three distinct scenarios: Barcelona, Montreal, and Rome. Through rigorous experimentation and analysis, we analyze the varying efficacy of these models in different scenarios. Our results demonstrate that LSTM outperforms other models in the Montreal and Rome scenarios, highlighting its effectiveness in predicting the optimal forwarding node for packet transmission. In contrast, Ensemble of Bagged Decision Trees emerge as the optimal model for the Barcelona scenario, exhibiting strong performance in selecting the most suitable forwarding node for packet transmission. However, the transferability of these models to scenarios where they were not trained is notably limited, as evidenced by their decreased performance on datasets from other scenarios. This observation underscores the importance of considering the data characteristics when selecting ML models for real-world applications. Furthermore, we identify that the distribution of nodes within datasets significantly influences model performance, highlighting its critical role in determining model efficacy. These insights contribute to a deeper understanding of the challenges inherent in transferring ML models between real-world scenarios, providing valuable guidance for practitioners and researchers alike in optimizing ML applications in Smart Grid Networks.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141954046","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 : 2024-08-07DOI: 10.1016/j.adhoc.2024.103628
{"title":"AI-enhanced multi-stage learning-to-learning approach for secure smart cities load management in IoT networks","authors":"","doi":"10.1016/j.adhoc.2024.103628","DOIUrl":"10.1016/j.adhoc.2024.103628","url":null,"abstract":"<div><p>In the context of rapidly urbanizing smart cities reliant on IoT networks, efficient load management is critical for sustainable energy use. This paper proposes an AI-enhanced Multi-Stage Learning-to-Learning (MSLL) approach tailored for secure load management in IoT networks. The proposed approach leverages MMStransformer, a transformer-based model designed to handle multivariate, correlated data, and to capture long-range dependencies inherent in load forecasting. MMStransformer employs a multi-mask learning-to-learning strategy, optimizing computational efficiency without compromising prediction accuracy. The study addresses the dynamic and complex nature of smart city data by integrating diverse environmental and operational variables. Security and privacy concerns inherent in IoT networks are also addressed, ensuring secure data handling and communication. Experimental results demonstrate the efficacy of the proposed approach, achieving competitive performance compared to traditional methods and baseline models. The findings highlight the potential of AI-driven solutions in enhancing load forecasting accuracy while ensuring robust security measures in smart city infrastructures. This research contributes to advancing the state-of-the-art in AI applications for sustainable urban development and energy management.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141998142","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 : 2024-08-04DOI: 10.1016/j.adhoc.2024.103627
{"title":"A mobile data collection method for balancing energy consumption and delay in strip-shaped wireless sensor networks with branches","authors":"","doi":"10.1016/j.adhoc.2024.103627","DOIUrl":"10.1016/j.adhoc.2024.103627","url":null,"abstract":"<div><p>Strip-shaped Wireless Sensor Networks (WSNs) with branches are commonly used in various long and narrow applications, such as mines, factories, subways, and pipelines, and they face serious energy hole problems caused by multi-hop communication. The Mobile Data Collector (MDC) can alleviate the energy hole problem. Current solutions have two limitations: one is the balance between energy consumption and delay, and the other is the overly ideal network model, e.g., the square region or circular area. This paper focuses on strip-shaped networks and proposes a novel mobile data collection method to find a trade-off between energy preservation and data delivery delay. Firstly, the MDC path is planned by solving the diameter of the tree in the network, resulting in reduced delay. Secondly, the network energy consumption is further reduced by clustering and optimal transmission distance adjustment. Then, a network lifetime balancing mechanism is designed to balance network energy between backbone and branches. Finally, the performance of the algorithm proposed in this paper has been studied in four types of strip-shaped WSNs and compared with four existing MDC methods with evaluation metrics of maximum node energy consumption, network delay and weighted sum of both. The simulation results demonstrate that the proposed algorithm is applicable to different types of strip-shaped WSNs with branches and achieves excellent network performance, which can effectively balance network energy consumption and data collection delay.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142012354","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 : 2024-08-03DOI: 10.1016/j.adhoc.2024.103623
{"title":"Bleach: From WiFi probe-request signatures to MAC association","authors":"","doi":"10.1016/j.adhoc.2024.103623","DOIUrl":"10.1016/j.adhoc.2024.103623","url":null,"abstract":"<div><p>Smartphones or similar WiFi-enabled devices regularly discover nearby access points by broadcasting management frames known as probe-requests. Probe-request frames relay, as information, the MAC addresses of sending devices, which act as the device identifiers. To protect the user’s privacy and location, probe-requests use a randomized MAC address generated according to the MAC address randomization protocol. Unfortunately, MAC randomization greatly limits any studies on trajectory inference, flow estimation, crowd counting, etc. To overcome this limitation while respecting users’ privacy, we propose <span>Bleach</span>, a novel, efficient, and comprehensive approach allowing randomized MAC addresses to device association from probe-requests. <span>Bleach</span> models the frame association as a resolution of MAC conflicts in small time intervals. We use time and frame content-based signatures to resolve and associate MACs inside a conflict. We propose a novel MAC association algorithm involving logistic regression using signatures and our introduced time metric. To the best of our knowledge, this is the first work that formulates the probe-request association problem as a generic resolution of conflicts and benchmarks the association concerning several datasets. Our results show that <span>Bleach</span> outperforms the state-of-the-art schemes in terms of accuracy (as high as 99%) and robustness to a wide range of input probe-request datasets.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1570870524002348/pdfft?md5=02e4cd50b7a3e4de4614a97c87b80c13&pid=1-s2.0-S1570870524002348-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141933611","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 : 2024-08-02DOI: 10.1016/j.adhoc.2024.103613
{"title":"A digital twin-based traffic light management system using BIRCH algorithm","authors":"","doi":"10.1016/j.adhoc.2024.103613","DOIUrl":"10.1016/j.adhoc.2024.103613","url":null,"abstract":"<div><p>Urban transportation networks are vital for the economic and environmental well-being of cities and they are faced with the integration of Human-Driven Vehicles (HVs) and Connected and Autonomous Vehicles (CAVs) challenge. Most of the traditional traffic management systems fail to effectively manage the dynamic and complex flows of mixed traffic, mainly because of large computational requirements and the restrictions that control models of traffic lights directly based on extensive and continuous training data. Most of the times, the operational flexibility of CAVs is severely compromised for the safety of HVs, or CAVs are given high priority without taking into account the efficiency of HVs leading to lower performance, especially at low CAV penetration rates. On the other hand, the existing adaptive traffic light approaches were usually partial and could not adapt to the real-time behaviors of the traffic system. Some systems operate with inflexible temporal control plans that cannot react to variations in traffic flow or use adaptive control strategies that are based on a limited set of static traffic conditions. This paper presents a novel traffic light control approach utilizing the BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies) clustering algorithm combined with digital twins for a more adaptive and efficient system. The BIRCH is effective in processing large datasets because it clusters data points incrementally and dynamically into a small set of representatives. The suggested method does not only enable better simulation and prediction of traffic patterns but also makes possible the real-time adaptive control of traffic signals at signalized intersections. It also improves traffic flow, reduces congestion, and minimizes vehicle idling time by adjusting the green and red light durations dynamically based on both real-time and historical traffic data. This approach is assessed under different traffic intensities, which include low, moderate, and high, while efficiency, fuel consumption, and the number of stops are being compared with the traditional and the existing adaptive traffic management systems.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141933614","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 : 2024-08-02DOI: 10.1016/j.adhoc.2024.103612
{"title":"Towards an optimal 3-D design and deployment of 6G UAVs for interference mitigation under terrestrial networks","authors":"","doi":"10.1016/j.adhoc.2024.103612","DOIUrl":"10.1016/j.adhoc.2024.103612","url":null,"abstract":"<div><p>Unmanned aerial vehicles (UAVs) have opened new communication possibilities by being able to access remote areas. Their ability to serve a large number of users based on demand and adaptability is a key strength. In Sixth Generation (6G) networks, UAVs are highly valued for their cost-efficiency and versatile deployment. However, the mobility of UAVs introduces different types of interference issues, resulting in a decrease in network performance and quality of service (QoS) for edge users. To address these challenges, this paper introduces a clustering-based solution involving three main steps. Firstly, UAVs are deployed in three-dimension (3D) space based on user requests using mini-batch K-mean clustering Subsequently, re-clustering is explored to tackle load balancing within clusters. Finally, outliers and boundary users are classified to enhance QoS for edge users. This model effectively reduces interference and boosts UAV reliability in terrestrial networks. Also, a case study is presented to show how UAVs can mitigate interference in maritime communication within terrestrial networks. Numerical results demonstrated that the proposed scheme increases throughput by 33.06% and reduces energy consumption and time delay by 73.15% and 9.15%, respectively, as compared to the existing baseline schemes.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141933626","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}