Ad Hoc Networks最新文献

{"title":"An online energy-saving offloading algorithm in mobile edge computing with Lyapunov optimization","authors":"Xiaoyan Zhao,&nbsp;Ming Li,&nbsp;Peiyan Yuan","doi":"10.1016/j.adhoc.2024.103580","DOIUrl":"https://doi.org/10.1016/j.adhoc.2024.103580","url":null,"abstract":"<div><p>Online computing offloading is an effective method to enhance the performance of mobile edge computing (MEC). However, existing research ignores the impact of system stability and device priority on system performance during task processing.To address the problem of computing offloading for computing-intensive tasks, an online partial offloading algorithm combining task queue length and energy consumption is proposed without any prior information. Firstly, a queue model of IoT devices is created to describe their workload backlogs and reflect the system stability. Then, using Lyapunov optimization, computing offloading problem is decoupled into two sub-problems by calculating the optimal CPU computing rate and device priority, which can determine the task offloading amount and offloading location to complete resource allocation. Finally, the online partial offloading algorithm based on devices priority is solved by minimizing the value of the drift-plus-penalty function’s upper bound to ensure system stability and reduce energy consumption. Theoretical analysis and the outcomes of numerous experiments demonstrate the effectiveness of the proposed algorithm in minimizing system energy consumption while adhering to system constraints, even in dealing with dynamically varying task arrival rates.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141487028","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":"Machine learning attack detection based-on stochastic classifier methods for enhancing of routing security in wireless sensor networks","authors":"Anselme R. Affane M.,&nbsp;Hassan Satori","doi":"10.1016/j.adhoc.2024.103581","DOIUrl":"https://doi.org/10.1016/j.adhoc.2024.103581","url":null,"abstract":"<div><p>Wireless Sensor Networks (WSNs) are vulnerable to attacks during data transmission, and many techniques have been proposed to detect and secure routing data. In this paper, we introduce a novel stochastic predictive machine learning approach designed to discern untrustworthy events and unreliable routing attributes, aiming to establish an artificial intelligence-based attack detection system for WSNs. Our methodology leverages real-time analysis of the features of simulated WSN routing data. By integrating Hidden Markov Models (HMM) with Gaussian Mixture Models (GMM), we develop a robust classification framework. This framework effectively identifies outliers, pinpoints malicious network behaviors from their origins, and categorizes them as either trusted or untrusted network activities. In addition, dimensionality reduction techniques are used to improve interpretability, reduce computation and processing time, extract uncorrelated features from network data, and optimize performances. The main advantage of our approach is to establish an efficient stochastic machine learning method capable of analyzing and filtering WSN traffic to prevent suspicious and unsafe data, reduce the large dissimilarity in the collected routing features, and rapidly detect attacks before they occur. In this work, we exploit a well-tuned data set that provides a lot of routing information without losing any data. The experimental results show that the proposed stochastic attack detection system can effectively identify and categorize anomalies in wireless sensor networks with high accuracy. The classification rates of the system were found to be around 83.65%, 84.94% and 94.55%, which is significantly better than the existing classification approaches. Furthermore, the proposed system showed a positive prediction value of 11.84% higher than the existing approaches.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141444320","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":"Comparative study of novel packet loss analysis and recovery capability between hybrid TLI-µTESLA and other variant TESLA protocols","authors":"Khouloud Eledlebi ,&nbsp;Ahmed Alzubaidi ,&nbsp;Ernesto Damiani ,&nbsp;Victor Mateu ,&nbsp;Yousof Al-Hammadi ,&nbsp;Deepak Puthal ,&nbsp;Chan Yeob Yeun","doi":"10.1016/j.adhoc.2024.103579","DOIUrl":"https://doi.org/10.1016/j.adhoc.2024.103579","url":null,"abstract":"<div><p>Analyzing packet loss, whether resulting from communication challenges or malicious attacks, is vital for broadcast authentication protocols. It ensures legitimate and continuous authentication across networks. While previous studies have mainly focused on countering Denial of Service (DoS) attacks' impact on packet loss, our research introduces an innovative investigation into packet loss and develops data recovery within variant TESLA protocols. We highlight the efficacy of our proposed hybrid TLI-µTESLA protocol in maintaining continuous and robust connections among network members, while maximizing data recovery in adverse communication conditions. The study examines the unique packet structures associated with each TESLA protocol variant, emphasizing the implications of losing each type on the network performance. We also introduce modifications to variant TESLA protocols to improve data recovery and alleviate the effects of packet loss. Using Java programming language, we conducted simulation analyses that illustrate the adaptability of variant TESLA protocols in recovering lost packet keys and authenticating previously buffered packets, all while maintaining continuous and robust authentication between network members. Our findings also underscore the superiority of the hybrid TLI-µTESLA protocol in terms of packet loss performance and data recovery, alongside its robust cybersecurity features, including confidentiality, integrity, availability, and accessibility. Additionally, we demonstrated the efficiency of our proposed protocol in terms of low computational and communication requirements compared to earlier TESLA protocol variants, as outlined in previous publications.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141434833","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":"LETM-IoT: A lightweight and efficient trust mechanism for Sybil attacks in Internet of Things networks","authors":"Jawad Hassan ,&nbsp;Adnan Sohail ,&nbsp;Ali Ismail Awad ,&nbsp;M. Ahmed Zaka","doi":"10.1016/j.adhoc.2024.103576","DOIUrl":"10.1016/j.adhoc.2024.103576","url":null,"abstract":"<div><p>The Internet of Things (IoT) has recently gained significance as a means of connecting various physical devices to the Internet, enabling various innovative applications. However, the security of IoT networks is a significant concern due to the large volume of data generated and transmitted over them. The limited resources of IoT devices, along with their mobility and diverse characteristics, pose significant challenges for maintaining security in routing protocols, such as the Routing Protocol for Low-Power and Lossy Networks (RPL). This lacks effective defense mechanisms against routing attacks, including Sybil and rank attacks. Various techniques have been proposed to address this issue, including cryptography and intrusion-detection systems. The use of these techniques on IoT nodes is limited by their low power and lossy nature, primarily due to the significant computational overhead they involve. In addition, conventional trust-management systems for addressing security concerns need to be improved due to their high computation, memory, and energy costs. Therefore, this paper presents a novel, Lightweight, and Efficient Trust-based Mechanism (LETM-IoT) for resource-limited IoT networks to mitigate Sybil attacks. We conducted extensive simulations in Cooja, the Contiki OS simulator, to assess the efficacy of the proposed LETM-IoT against three types of Sybil attack (A, B, and C). A comparison was also made with standard RPL and state-of-the-art approaches. The experimental findings show that LETM-IoT outperforms both of these in terms of average packet-delivery ratio by 0.20 percentage points, true-positive ratio by 1.34 percentage points, energy consumption by 2.5%, and memory utilization by 19.42%. The obtained results also show that LETM-IoT consumes increased storage by 5.02% compared to the standard RPL due to the existence of an embedded security module.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1570870524001872/pdfft?md5=76ec8ae4462665d30ce03fddc3ecca3b&pid=1-s2.0-S1570870524001872-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141404107","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":"BPS-V: A blockchain-based trust model for the Internet of Vehicles with privacy-preserving","authors":"Chuanhua Wang ,&nbsp;Quan Zhang ,&nbsp;Xin Xu ,&nbsp;Huimin Wang ,&nbsp;ZhenYu Luo","doi":"10.1016/j.adhoc.2024.103566","DOIUrl":"10.1016/j.adhoc.2024.103566","url":null,"abstract":"<div><p>The trust system is widely used to prevent malicious behaviors, and it is a key element for vehicles to establish interactions in the Internet of Vehicles (IoV). Nevertheless, trust and privacy remain unresolved concerns stemming from the distinctive features of the IoV. The IoV must thwart malicious attackers from spreading false data while ensuring that the vehicle’s evaluation data is not leaked, which is of utmost importance. In this paper, we propose a blockchain-based trust model (BPS-V), which supports ciphertext computation of trust evaluation data submitted by different vehicles. Design a cooperative update method for vehicle trust, which utilizes an improved distributed two-trapdoor public-key cryptography algorithm to achieve cooperative computing of trust and reduce the risk of privacy leakage of evaluation data. On this basis, BPS-V introduces blockchain sharding technology to realize cross-domain storage and sharing of the trust. Simulation results show that our scheme can effectively protect the privacy of evaluation data and maintain a high detection rate and low false alarm rate in different road environments. Compared with traditional schemes, BPS-V can improve the efficiency of trust updates and the detection of malicious vehicles by 9.5% and 32%.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141401676","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":"Local search resource allocation algorithm for space-based backbone network in Deep Reinforcement Learning method","authors":"Peiying Zhang ,&nbsp;Zixuan Cui ,&nbsp;Neeraj Kumar ,&nbsp;Jian Wang ,&nbsp;Wei Zhang ,&nbsp;Lizhuang Tan","doi":"10.1016/j.adhoc.2024.103575","DOIUrl":"https://doi.org/10.1016/j.adhoc.2024.103575","url":null,"abstract":"<div><p>With the evolution of Space-based backbone networks, the demand for enhanced efficiency and stability in network resource allocation has become increasingly critical, presenting a substantial challenge to conventional allocation methods. In response, we introduce an innovative resource allocation algorithm for space-based backbone networks. This algorithm represents a synergistic fusion of Deep Reinforcement Learning (DRL) and Local Search (LS) methodologies. It is specifically designed to reduce the extensive training duration associated with traditional policy networks, a crucial aspect in assuring optimal service quality. Our algorithm is structured within a two-stage framework that seamlessly integrates DRL and LS. A distinctive feature of our approach is the incorporation of link reliability into the algorithmic design. This element is meticulously tailored to address the dynamic and heterogeneous nature of space-based networks, ensuring effective resource management. The effectiveness of our approach is substantiated through extensive simulation results. These results demonstrate that the integration of DRL with LS not only enhances training efficiency but also exhibits significant improvements in resource allocation outcomes. Our work represents a noteworthy contribution to the development of practical optimization strategies in space-based networks, merging DRL with traditional methodologies for improved performance.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141323070","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":"Hyper-graph matching D2D offloading scheme for enhanced computation and communication capacity","authors":"Pan Zhao ,&nbsp;Liuyuan Chen ,&nbsp;Zhiliang Jiang ,&nbsp;Datong Xu ,&nbsp;Jianli Yang ,&nbsp;Mingyang Cui ,&nbsp;Tianfei Chen","doi":"10.1016/j.adhoc.2024.103526","DOIUrl":"10.1016/j.adhoc.2024.103526","url":null,"abstract":"<div><p>As the Internet of Things(IoT) and its intelligent applications continue to proliferate, forthcoming 6G networks will confront the dual challenge of heightened communication and computing capacity demands. To address this, D2D collaborative computing is being explored. However, the current D2D collaborative computing ignores the integrity of computing and communication. For a single-task device, offloading operations intertwine computing and communication, internal coupling causes due to parallel executed between local and D2D offloading. In addition, external coupling arises among devices competing for limited radio and computing resources. Worse, internal coupling and external coupling interact, exacerbating the situation. To address these challenges, a novel D2D offloading framework is proposed based on hyper-graph matching in this paper. Our goal is to minimize both delay and energy costs while ensuring service quality for all users by jointly optimizing task scheduling, offload policies and resource allocation. The original problem is formulated as a nonlinear integer programming problem. Then, by three-stage strategy optimization decomposition, it is separated into several sub-problems. In the first stage, a polynomial-time algorithm has been developed to optimize the task offloading ratio, taking into account both its upper and lower bounds. In the second stage, a geometric programming algorithm has been created to address power allocation. In the third stage, a three-dimensional hyper-graph matching model is employed to derive the optimal offloading and channel allocation policies. This is based on analyzing the conflict graph and applying the claw theorem. Simulation results demonstrate that the proposed scheme outperforms other algorithms by approximately 12%, 20%, 28%, 40%, respectively. Moreover, it enhances both spectral efficiency and computational efficiency.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1570870524001379/pdfft?md5=14b146ffd1942df62525be5b45777af4&pid=1-s2.0-S1570870524001379-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141391607","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":"Protect your data and I’ll rank its utility: A framework for utility analysis of anonymized mobility data for smart city applications","authors":"Ekler Paulino de Mattos ,&nbsp;Augusto C.S.A. Domingues ,&nbsp;Fabrício A. Silva ,&nbsp;Heitor S. Ramos ,&nbsp;Antonio A.F. Loureiro","doi":"10.1016/j.adhoc.2024.103567","DOIUrl":"10.1016/j.adhoc.2024.103567","url":null,"abstract":"<div><p>When designing smart cities’ building blocks, mobility data plays a fundamental role in applications and services. However, mobility data usually comes with unrestricted location of its corresponding entities (e.g., citizens and vehicles) and poses privacy concerns, among them recovering the identity of those entities with linking attacks. Location Privacy Protection Mechanisms (LPPMs) based on anonymization, such as mix-zones, have been proposed to address the privacy of users’ identity. Once the data is protected, a comprehensive discussion about the trade-off between privacy and utility happens. However, issues still arise about the application of anonymized data to smart city development: what are the smart cities applications and services that can best leverage mobility data anonymized by mix-zones? To answer this question, we propose the Utility Analysis Framework of Anonymized Trajectories for Smart Cities-Application Domains (UAFAT). This characterization framework measures the utility through twelve metrics related to privacy, mobility, and social, including mix-zones performance metrics from anonymized trajectories produced by mix-zones. This framework aims to identify applications and services where the anonymized data will provide more or less utility in various aspects. The results evaluated with cabs and privacy cars datasets showed that further characterizing it by distortion level, UAFAT ranked the smart cities application domains that best leverage mobility data anonymized by mix-zones. Also, it identified which one of the four case studies of smart city applications had more utility. Additionally, different datasets present different behaviors in terms of utility. These insights can contribute significantly to the utility of both open and private data markets for smart cities.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141408608","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":"Whale optimization-orchestrated Federated Learning-based resource allocation scheme for D2D communication","authors":"Nilesh Kumar Jadav,&nbsp;Sudeep Tanwar","doi":"10.1016/j.adhoc.2024.103565","DOIUrl":"https://doi.org/10.1016/j.adhoc.2024.103565","url":null,"abstract":"<div><p>Device-to-Device (D2D) communication plays a prominent role in mobile data offloading from the cellular infrastructure (e.g., base station). This paradigm empowers user equipment to communicate with each other directly, offering an efficient resort for data communication that eliminates the need for the base station. However, significant challenges, such as interference, resource allocation, and energy efficiency, impede the performance of D2D communication. In the context of resource allocation, most of the existing work primarily focuses on game and graph theoretical models, which raises the computational complexity as the number of D2D users increases. In this article, we formulated a sum rate maximization problem, which is solved using a combinatorial scheme comprised of Whale Optimization Algorithm (WOA) and Federated Learning (FL). First, we discover the optimal CUs-D2D Groups (D2DGs) pairs by utilizing the social behavior of whales in the WOA. Only these optimal links are permitted to participate in the FL-based resource allocation, ensuring a physical layer access control. Next, we generated a dataset from the WOA-based optimal CU-D2DG links, which is employed by the Convolutional Neural Network (CNN) model for decentralized learning. FL offers a proactive decision for resource assignment, i.e., whose CU resources will be used by the D2DG. The proposed scheme is evaluated by considering different performance parameters, such as convergence rate, statistical measure (accuracy, loss), fairness (0.72), and overall sum rate (<span><math><mrow><mo>≈</mo><mn>25</mn><mspace></mspace><mtext>Mbps</mtext></mrow></math></span>).</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141291972","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":"A deep learning framework for blockage mitigation and duration prediction in mmWave wireless networks","authors":"Ahmed Almutairi ,&nbsp;Alireza Keshavarz-Haddad ,&nbsp;Ehsan Aryafar","doi":"10.1016/j.adhoc.2024.103562","DOIUrl":"https://doi.org/10.1016/j.adhoc.2024.103562","url":null,"abstract":"<div><p>Millimeter-Wave (mmWave) communication can be highly affected by blockages, which can drastically decrease the signal strength at the receiver side. To overcome the impact of blockages, predicting the optimal mitigation technique and accurately estimating the duration of the blockage events are crucial for maintaining reliable and high-performance mmWave communication systems. Prior works on mitigating blockages have proposed a variety of model and protocol-based blockage mitigation solutions that concentrate on a singular technique at a time, like switching the current beam to an alternative beam at the current base station or client. In this paper, we tackle the overarching question: <em>what blockage mitigation technique should be employed?</em> and <em>what is the optimal sub-selection within that technique?</em> We also address the blockage duration estimation problem. We solve these problems by developing a Gated Recurrent Unit (GRU) model, trained on data from periodic message exchanges in mmWave systems. We tested our neural network models by utilizing a mmWave simulator that is commercially available and widely used in wireless communication to compile a large amount of dataset for this purpose. Our findings reveal that our proposed method introduces no extra communication overhead, while achieving remarkable accuracy, exceeding 91%, in predicting the optimal blockage mitigation technique. Moreover, the blockage duration estimation model achieves a very high accuracy with a residual mean error of less than 0.04 s. Finally, we demonstrate that our proposed blockage mitigation method substantially boosts the volume of data transferred in comparison to various other blockage mitigation strategies.</p></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141241624","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}