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IEEE Conference on Vehicular Technology (VTC)

作者： Abhijeet Manoj Varma Nikumani Choudhury Jay Dave Anakhi Hazarika Moustafa M. Nasralla Dept. of Computer Science & Information Systems Birla Institute of Technology & Science Pilani Hyderabad India Dept. of Electrical & Electronics Engineering Birla Institute of Technology & Science Pilani Hyderabad India Dept. of Communications & Networks Engineering Smart Systems Engineering Lab Prince Sultan University Riyadh Saudi Arabia

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

As the Internet of Things (IoT) is poised to become a global phenomenon, it is imperative to schedule the transmissions of IoT devices effectively and in a fair way. Leveraging Long Range (LoRa) technology, we can achieve transmissions that consume minimal power while covering vast distances, aligning with the requirements of IoT devices. However, the proximity of multiple devices within the same area often leads to packet interference and collisions. To address this, our study introduces a pioneering scheduling method utilizing a constellation of Low Earth Orbit (LEO) satellites to manage and streamline the transmission of data from End Devices (EDs). This method employs two LEO satellites: the first satellite assigns the sequence for EDs to dispatch their packets, and the second collects these packets in the predetermined sequence before forwarding them to the LoRa Network Server (LNS). For urgent (URG) communications, EDs can alert the first satellite, which then coordinates with the LNS to schedule these priority transmissions. The LNS generates a schedule that is relayed to the second satellite, informing EDs with URG packets of their specific transmission times and channels. This scheduling approach is designed to optimize channel usage effectively while accommodating the transmission of urgent data.

关键词： 6G mobile communication Schedules Vehicular and wireless technologies Satellites Scheduling algorithms Low earth orbit satellites LoRaWAN

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Software-Defined Networking Applied in Tactical networks: Problems, Solutions and Open Issues

Software-Defined Networking Applied in Tactical Networks: Pr...

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2021 International Conference on Military communication and Information systems, ICMCIS 2021

作者： Von Rechenberg, Merlin Rettore, Paulo H. L. Lopes, Roberto Rigolin F. Sevenich, Peter Fraunhofer FKIE Dept. of Communication Systems Bonn Germany Institute of Computer Science 4 University of Bonn Bonn Germany

ISBN: (纸本)9781665445863

Robust and secure communication systems are essential for military operations but the ever-changing scenarios, heterogeneous devices and dense environment of Tactical networks (TN) make it challenging to fulfill the requirements. Currently, the literature has shown that Software-defined Networking (SDN) has the potential to improve network management and control, helping to overcome some of these issues. But the application of SDN in TNs is not trivial. Therefore, in order to understand the current problems faced in Software-defined Tactical networks (SDTN), we conducted a literature review focused on the current problems and solutions, aiming to identify open issues in SDTN. Therefore, we created four main problem categories (i.e. performance, availability, security, and robustness), describing the proposed solutions to handle these issues as well as discussing the approaches, test environments, and the reproducibility of these solutions. © 2021 IEEE.

关键词： Software defined networking

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Decentralized Spectrum Sharing networks Based on Blockchains

Decentralized Spectrum Sharing Networks Based on Blockchains

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International Wireless communications and Mobile Computing Conference, IWCMC

作者： Shuyue Ai Yuna Jiang Qiang Li Xiaohu Ge Aduwati Sali School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan China Dept. of Computer and Communication Systems Engineering Faculty of EngineeringUPM WiPNET Research Centre

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

The dynamic spectrum sharing technology in cognitive radio can effectively improve the utilization rate of spectrum and relieve the current spectrum pressure. To realize spectrum sharing without trust between SUs and PUs belonging to various operators, a decentralized spectrum sharing scheme based on blockchain is proposed in this paper. A latency model and a decentralization degree model of blockchain-enabled spectrum sharing network are formulated. Network scale law in this paper is defined as the change law of structure and scale in a network. Based on the proposed decentralization degree and latency model, the scale law of blockchain networks under the constraints of latency and decentralization is studied. The simulation analyzes the change of the proportion of consensus nodes in the blockchain network with different requirements for latency and decentralization. The results show that when blockchain networks have both low latency and decentralization characteristics, the upper limit of the total number of nodes is 390, and the value range of the proportion of consensus nodes is between 0.13 and 0.56.

关键词： Blockchains Cognitive radio Low latency communication Mobile computing

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RELIABILITY ANALYSIS OF MONITORING SYSTEM FOR EXTRATERRESTRIAL HABITAT USING CTMC AND EMPIRICAL EVALUATION

arXiv

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arXiv 2023年

作者： Band, Saurabh Stechmann, Florian Unnikrishnan, Malavika Attarha, Shadi Heinicke, Christiane Willig, Andreas Förster, Anna Dept. Sustainable Communication Networks University of Bremen Germany Center of Applied Space Technology and Microgravity University of Bremen Germany Dept. Computer Science and Software Engineering University of Canterbury New Zealand

Much research has been done to settle a civilization on Mars in recent years. Among the various required resources for this civilization, the habitat is one of the crucial resources to live on Mars. Such an extraterrestrial habitat is designed to provide a safe place to live during the initial missions. It is equipped with monitoring and life support systems to ensure the astronauts’ safety. In this work, we present a robust monitoring system with a use case for extraterrestrial habitats. Similar to a typical monitoring system, it consists of sensor nodes and a gateway connected through a wireless communication channel. In our system, we introduce robustness to various failures that can occur after deployment, namely, board, sensor and gateway failure, in the form of redundancy. For each failure, the problem is tackled differently. For the first two types, we use additional hardware as backup, while for the last type, we use neighbouring devices as backups. The backup devices function as replacements for the failed component, which helps the system to collect the data which would otherwise be lost. We evaluate how much the performance of the system improves by using backup devices. We use a Continuous-Time Markov chain for the theoretical evaluation and an experimental setup that includes the hardware prototype for the empirical evaluation. We also analyze the effect of a simple medium access mechanism on the system’s performance in the presence of heavy noise on the channel. Based on our requirements, we use a simple custom medium access control (MAC) algorithm called Slotted-ALOHA with Random Back-off (SARB) to make communication reliable. We demonstrate that around 30 - 34% of the packets are recovered, with the use of backup devices (redundancy), which would otherwise be lost in case of failures. We also demonstrate that the system’s performance improves by 3.8 - 13.2% with the use of a simple medium access technique (SARB). © 2023, CC BY.

关键词： Sensor nodes

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IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW

作者： Felix Dobslaw Robert Feldt Dept. of Communication Quality Mngmt. and Inf. Systems Mid Sweden University Östersund Sweden Dept. of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden

This study examines to what extent the testing of traditional software components and machine learning (ML) models fundamentally differs or not. While some researchers argue that ML software requires new concepts and perspectives for testing, our analysis highlights that, at a fundamental level, the specification and testing of a software component are not dependent on the development process used or on implementation details. Although the software engineering/computer science (SE/CS) and Data science/ML (DS/ML) communities have developed different expectations, unique perspectives, and varying testing methods, they share clear commonalities that can be leveraged. We argue that both areas can learn from each other, and a non-dual perspective could provide novel insights not only for testing ML but also for testing traditional software. Therefore, we call upon researchers from both communities to collaborate more closely and develop testing methods and tools that can address both traditional and ML software components. While acknowledging their differences has merits, we believe there is great potential in working on unified methods and tools that can address both types of software.

关键词： Software testing Conferences Machine learning Software Testing

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Improving Robustness and Reducing Control Overhead via Dynamic Clustering in Tactical SDN

Improving Robustness and Reducing Control Overhead via Dynam...

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MILCOM, Military communications Conference

作者： Philipp Zißner Paulo H. L. Rettore Bruno P. Santos Roberto Rigolin F. Lopes Johannes F. Loevenich Peter Sevenich Dept. of Communication Systems Fraunhofer FKIE Bonn Germany Dept. of Computer Science Federal University of Bahia Salvador Brazil Secure Communications & Information (SIX) Thales Deutschland Ditzingen Germany

This study presents a dynamic clustering approach to address the challenges of managing modern and dynamic tactical communication using diverse radio links in Software-Defined Tactical networks (SDTNs). State-of-the-art conventional Software-Defined Networking (SDN) protocols, which rely on centralized controllers, are unsuitable for tactical scenarios due to their inherent demands for high-throughput, low-latency control planes, and static nodes. To enable SDTN, we propose a clustering solution designed to distribute network nodes across multiple remote controllers, thereby reducing the control message overhead created by the OpenFlow protocol. Moreover, we propose a flexible controller assignment strategy to dynamically balance the network load during runtime and improve network robustness using backup controllers. Our comparative analysis suggests a significant reduction of control overhead across heterogeneous topologies with VHF and UHF links using our clustering solution. Furthermore, we replicate a real-world scenario by emulating a convoy of military vehicles demonstrating the effective distribution of low control overhead among the controllers and maintaining robust network connectivity, even in the event of a controller failure.

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Leveraging Artificial Intelligence for Enhanced Data Generation in Addressing Imbalance in Binary Classification System

Leveraging Artificial Intelligence for Enhanced Data Generat...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Srijita Bandopadhyay Srimonti Dutta Imran Haider Bhavaraju Anuraag Jerry Zhu Saad Ahmed Bazaz Dept. of Electronics and Communication Engineering University of Engg. & Management Kolkata India School of Agro and Rural Technology Indian Institute of Technology Guwahati Guwahati India Dept. of Industrial and Systems Engineering Indian Institute of Technology Kharagpur Kharagpur India Dept. of Electronics and Communication Engineering Vellore Institute of Technology Vellore India Faculty of Mathematics University of Waterloo Ontario Canada Dept. of Computer Science National University of Computer & Emerging Sciences Islamabad Pakistan

This paper delves into the challenges of binary classification using imbalanced datasets, particularly when instances of interest are infrequent. It explores a comprehensive approach that integrates Synthetic Minority Over-sampling Technique (SMOTE), Generative Adversarial networks (GANs), and Variational Autoencoders (VAEs) to enhance classification outcomes. Traditional classification models tend to favor the majority class, while the impact of imbalanced misclassification costs is often overlooked. The integration of SMOTE, GANs, and VAEs in binary classification, or SMOTE-GAN-VAE, addresses these challenges by generating synthetic instances, refining data representations, and capturing latent features. To evaluate the effectiveness of various data generation methods, a credit card fraud dataset is used. The performance metrics considered include F0.5-score, F1-score, and F2-score, which account for both precision and recall. The results indicate that SMOTE-GAN-VAE outperforms individual methods, such as SMOTE, GANs, and VAEs, demonstrating its potential to enhance data representation and classification accuracy, and outperformed the β- VAE filtered approach employed in previous literature.

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Extended Adaptive Data-Rate (X-ADR) Technique for Optimal Resource Allocation in Smart City Applications

Extended Adaptive Data-Rate (X-ADR) Technique for Optimal Re...

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IEEE International Symposium on World of Wireless Mobile and Multimedia networks (WoWMoM)

作者： Nikumani Choudhury Manik Gupta Moustafa M. Nasralla Satoshi Fujita Dept. of Computer Science and Information Systems Birla Institute of Technology & Science Pilani Hyderabad India Dept. of Communications & Networks Engineering Prince Sultan University Riyadh Saudi Arabia Graduate School of Advanced Science and Engineering Hiroshima University Japan

With the rapid growth of urbanization, the need for sustainable, energy-efficient, and smart solutions for home, industry, governance, traffic, and in general, the need for improved quality of life and health has risen. As an enabling technology, the Internet of Things (IoT) must facilitate several advanced applications with varied QoS requirements for smart cities. In this regard, Long Range (LoRa) technologies can be an ideal communication protocol for resource-constrained IoT devices. The LoRa Wide Area Network (LoRaWAN) defines physical layer options and the medium access control (MAC) sub-layer protocols for facilitating low-power, low-rate communications among battery-operated wireless IoT devices. With the enormous number of IoT devices and growing QoS requirements, it is imperative to optimally allocate resources (bandwidth, spreading factor, and transmit power) to these constrained devices so that network lifetime can be improved. The Adaptive Data-Rate (ADR) technique is used by the Network Servers (NS) to adapt the transmission parameters of the devices optimally. This is based on several received parameters from the end devices as well as the network settings. In this work, we extend the ADR technique to the LoRa gateways to consider the class of LoRa devices and the frequency of transmissions further to extend the energy efficiency and lifespan of IoT devices. Additionally, there is a considerable delay in adapting to optimal settings for the end-devices resulting in excess power dissipation. Further, a novel mechanism is proposed to address the congestion issue in the network using the Spreading Factor parameter (SF).

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Network-based Intrusion Detection Datasets: A Survey

Network-based Intrusion Detection Datasets: A Survey

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Information Technology (ACIT)

作者： Lubna Ali Hassan Ahmed Yahia Abdalla Mohamed Hamad Ahmed Abdallah Mohamed Ali Abdalla Dept. of Electronics Engineering Sudan University of Science and Technology Khartoum Sudan Dept. of Computer Networks and Systems Sudan University of Science and Technology Khartoum Sudan

ISBN: (数字)9798350320244

ISBN: (纸本)9798350320251

The increasing reliance on computers and the internet has increased the need for protection against attacks and security threats. A network-based intrusion detection system (NIDS) is one of the promising research fields that could highly contribute to cyber-attacks detection and mitigation. Datasets are necessary for NIDS training and evaluation. This paper provides a comprehensive survey of publicly available NIDS datasets. The study covers the most used NIDS datasets, each dataset is briefly described along with its main properties and shortcomings. Moreover, the paper highlights the most important dataset characteristics and provides a clear datasets comparison accordingly. Finally, the paper discusses observations and provides some recommendations to help researchers identify future work.

关键词： Training computers Intrusion detection Security Information technology Cyberattack

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AI-Driven Traffic-Aware Dynamic TDD Configuration in B5G networks

AI-Driven Traffic-Aware Dynamic TDD Configuration in B5G Net...

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IEEE Symposium on Network Operations and Management

作者： Sanguk Jeong Dahyun Mok Gyurin Byun Lusungu J. Mwasinga Hyunseung Choo R&D Team Networks Samsung Electronics Suwon S. Korea Dept. of Digital Media and Communications Engineering Sungkyunkwan University Suwon South Korea Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea Dept. of AI Systems Engineering Sungkyunkwan University Suwon South Korea Dept. of Computer Science and Engineering Sungkyunkwan University Suwon South Korea

ISBN: (数字)9798350327939

ISBN: (纸本)9798350327946

The advent and anticipated evolution of Beyond Fifth Generation (B5G) networks raise critical issues for the static Time Division Duplex (TDD) radio resource allocation technique. In Static TDD, the fixed allocation of uplink and downlink resources leads to poor resource utilization, with uplink channels often congested and downlink channels underutilized. This study addresses static TDD limitations by proposing a novel TDD configuration called Traffic-Aware Dynamic TDD (TA-TDD), aiming to satisfy the high-speed and low-latency communication requirements of various applications. Specifically, the proposed TA-TDD utilizes Convolutional Long Short-Term Memory (ConvLSTM) model to predict traffic before allocation of uplink and downlink resource. This method effectively manages uplink-centric traffic in wireless networks, to improve both network quality and user experience. Compared to static TDD, the proposed TA-TDD notably improves network throughput by as much as 20% in scenarios with high uplink demand. The findings demonstrate that dynamic TDD configurations significantly enhance network throughput compared to static setups, which offers an effective solution for network management.

关键词： Wireless networks Predictive models Downlink Throughput User experience Resource management Uplink

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