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16th International Conference on Communication Software and Networks, ICCSN 2024

作者： Sun, Weijie Jin, Ming Jiang, Tao Li, Zhaoteng Chen, Guo Li, Wenjuan Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China

ISBN: (纸本)9798331506322

Discontinuous reception (DRX) is one of the important power-saving mechanisms for 5G/B5G cognitive radio systems. Conventional DRX methods improve the power-saving performance at the cost of data transmission delay. To address this issue, a deep reinforcement learning based DRX method is proposed. An adaptive time-slot DRX structure is propsed and the DRX mechanism is modeled as a Markov decision process. The state set, action space and reward expressions are jointly designed for the DRX mechanism. A DRX decision strategy is obtained by deep reinforcement learning, which adaptively adjusts the window length of wake-up period. Simulation results are provided to demonstrate that the proposed DRX method improves the power-saving performance while the average transmission delay of data packages closes to the lower bound. © 2024 IEEE.

关键词： Deep reinforcement learning

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Closed form Solution of Moving Source Localization Using TDOA and FDOA Measurements Under Sensor Location Errors 16

Closed form Solution of Moving Source Localization Using TDO...

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16th International Conference on Communication Software and Networks, ICCSN 2024

作者： Sheng, Menglei Li, Youming Zhou, Yapeng Cai, Wanyuan Qi, Qinke Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China

ISBN: (纸本)9798331506322

The moving source localization is very sensitive to the knowledge of sensor locations. In this paper, we propose a two-stage closed-form method for locating a moving source by using Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) measurements in the presence of random errors in sensor locations. In the first stage, we establish a series of pseudo-linear equations by introducing the auxiliary variables and obtain an initial location estimation based on the bias reduced criteria and the Lagrange multiplier theory. In the second stage,we propose a modified weighted least squares method to obtain the final estimation by exploring the relationship between the auxiliary variables and the moving source location and velocity. The proposed method is in closed form and therefore computationally efficient as well as free from the divergence problem unlike iterative techniques. Simulations show the better performance of the proposed method. © 2024 IEEE.

关键词： Iterative methods

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A Review of Anonymization Algorithms and Methods in Big Data

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Annals of Data science 2025年第1期12卷 253-279页

作者： Shamsinejad, Elham Banirostam, Touraj Pedram, Mir Mohsen Rahmani, Amir Masoud Department of Computer Engineering Central Tehran Branch Islamic Azad University Tehran Iran Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran Department of Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran

In the era of big data, with the increase in volume and complexity of data, the main challenge is how to use big data while preserving the privacy of users. This study was conducted with the aim of finding a solution to this challenge. In this study, we examined various data anonymization methods, including differential privacy, advanced encryption, and strong access controls. In addition, the operation, advantages, disadvantages, and use of these methods, the challenges of adapting these methods to big data, and possible solutions for them were also examined. Our results show that traditional data anonymization methods lack scalability, leading to privacy breaches and data loss. When faced with large volumes of data, these methods may not be able to fully process the data. Also, these methods may be ineffective against re-identification attacks, linkage attacks, and inference attacks. We introduced emerging methods that are capable of providing improved privacy with minimal data loss. These methods have scalability for big data. Finally, we examined future research works and raised important questions that can help improve existing algorithms or develop new methods, better manage the complexity and scale of unstructured data. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Big data

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Performance Gain Analysis for Introducing Relays to Rigid Body Localization Using TOAs and AOAs 16

Performance Gain Analysis for Introducing Relays to Rigid Bo...

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16th International Conference on Communication Software and Networks, ICCSN 2024

作者： Chen, Tianye Wang, Gang Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China

ISBN: (纸本)9798331506322

This paper analyzes the performance gain of rigid body localization (RBL) using time-of-arrival (TOA) and angle-of-arrival (AOA) measurements, when introducing non-regenerative relays having unknown positions. Although the introduction of the relays can generate more measurements, more unknown parameters are also introduces since the relay positions are not known. Hence, it is not clear whether the additional non-regenerative relays can improve the localization performance of the rigid body. To answer this question, we conduct the Cramer-Rao lower bound (CRLB) analysis and show theoretically that the answer to this question is affirmative. Simulation results confirm the correctness of the theoretical result. © 2024 IEEE.

关键词： Cramer-Rao bounds

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Deployment of a security solution for cloud 15

Deployment of a security solution for cloud

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15th International Conference on Communications, COMM 2024

作者： Chis, Alexandru Balan, Titus-Constantin Cotfas, Petru-Adrian Cotfas, Daniel-Tudor Transylvania University Faculty Electrical Engineering and Computer Science Braov Romania

ISBN: (纸本)9798350355956

Cloud computing offers benefits in the digital world, such as scalability and agility, but securing these environments requires a high level of knowledge and have the potential for misconfiguration. While cloud platforms offer user-friendly interfaces, ensuring robust cloud security requires a balance between user experience and technical expertise to avoid security vulnerabilities that arise from misconfiguration. This paper proposes a fundamental framework for improving the security posture while using the cloud. The framework uses a configurable building block approach to simplify migration and development efforts for cloud-based solutions. The framework focuses on Amazon Web Services (AWS) and automates deployment with infrastructure-as-code (IaC) principles, minimizing the need for deep infrastructure knowledge. This allows users to develop and deploy secure cloud solutions with built-in security tools and monitoring, minimizing the need for extensive infrastructure knowledge on the user's part. This framework aims to provide a hardened environment suited for cloud appropriation. The framework is leveraging security best practices and monitoring tools, harnessing a more secure approach to the use of public cloud environments. © 2024 IEEE.

关键词： Cloud security

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Robust Covert and Secure Transmission for ISAC System With Transceiver Hardware Impairments 16

Robust Covert and Secure Transmission for ISAC System With T...

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16th International Conference on Communication Software and Networks, ICCSN 2024

作者： Li, Yaming Jin, Ming Jiang, Tao Chen, Chaodi Yin, Lei Zhang, Huifang Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China

ISBN: (纸本)9798331506322

In integrated sensing and communication (ISAC) systems, communication signals can easily be wiretapped by targets (potential eavesdroppers) or detected by wardens. Different from previous works that address a single security problem, we investigate a covert and secure beamforming design in the ISAC system to address this issue. Meanwhile, we also consider the hardware impairments (HWI) of transceiver, the angle and distance estimation errors of the eavesdroppers, and the imperfect warden channel. We formulate a secure beamforming optimization problem under sensing integrated sidelobe to mainlobe ratio (ISMR), communication rate, and covert communication constraints. To solve the non-convex optimization problem, we adopt semidefinite relaxation (SDR) and S-procedure techniques to transform it into a convex problem and solve it. The simulation results demonstrate the effectiveness of the designed scheme and reveal a trade-off between the communication and sensing performance of the system. © 2024 IEEE.

关键词： Convex optimization

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Representing a Model for the Anonymization of Big Data Stream Using In-Memory Processing

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Annals of Data science 2025年第1期12卷 223-252页

In light of the escalating privacy risks in the big data era, this paper introduces an innovative model for the anonymization of big data streams, leveraging in-memory processing within the Spark framework. The approach is founded on the principle of K-anonymity and propels the field forward by critically evaluating various anonymization methods and algorithms, benchmarking their performance with respect to time and space complexities. A distinctive formula for optimized cluster determination in the K-means algorithm is presented, along with a novel tuple expiration time strategy for the efficient purging of clusters. The integration of these components into Spark’s RDD and MLlib modules results in a significant decrease in execution time and data loss rates, even with increasing data volumes. The paper’s notable contributions are its methodological advancements that offer a robust, scalable solution for data anonymization, safeguarding user privacy without sacrificing data utility or processing efficiency. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Big data

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Improving TRISAT-R Satellite Attitude Prediction by Incorporating a High-Resolution Optical Sensor to Kalman Filtering 15

Improving TRISAT-R Satellite Attitude Prediction by Incorpor...

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15th International Conference Elektro, ELEKTRO 2024

作者： Kramberger, Iztok Kosanic, Nejc University of Maribor Faculty of Electrical Engineering and Computer Science Maribor Slovenia

ISBN: (纸本)9798350372359

When flying a satellite, various operations on-board the satellite require determining quite a precise orientation to properly function, such as Earth or Sun observation, downlink communication and similar. This results in satellite attitude estimation posing a crucial problem to be solved, using a wide array of spacecraft control systems and sensor readings. Due to the noise in magnetic sensor measurements and drift in gyro meters, auxiliary (optical) subsystems are widely used to add reference measurements and correct the noise and the drift. Since the star-trackers, most widely used optical subsystem for attitude estimation, can be relatively large and high energy consuming, a smaller alternative is found in photodiodes and small CMOS cameras, both of which are being currently used on board TRISAT-R. Even with additional optical filters, there is error present in all measurements and error estimation is necessary. Recently the development and use of Unscented Kalman Filter (UKF) has shown greater potential for use in space related estimation, due to UKF not using classic Kalman linearization but employing a set of sigma points to calculate the systems mean and covariance more accurately. TRISAT-R use of on-board systems to tackle the problem of attitude estimation is described. UKF filtering is briefly discussed, and the simulation model for UKF of TRISAT-R orbiting is proposed. The results show an increase in accuracy of attitude prediction when using CMOS cameras for prediction instead of photodiodes, which confirms the idea that small cameras can be used for in-orbit photodiode calibration. © 2024 IEEE.

关键词： Photodiodes

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Genetic algorithm for optimizing meteorological sensors placement using airborne LiDAR data 24

Genetic algorithm for optimizing meteorological sensors plac...

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24th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2024

作者： Lukač, Niko Kavran, Domen Ovčjak, Monika Ferk Bizjak, Marko Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia

ISBN: (纸本)9798350353433

This paper presents a novel method for optimizing meteorological sensor placement over large geographic areas, leveraging genetic algorithm (GA) and classified Light Detection And Ranging (LiDAR) data. The airborne LiDAR data provides detailed surface information necessary for finding the optimal locations for sensor placement. By considering semantic segmentation of surface, relative Sky View Factor (SVF), and surface slope, the method significantly reduces the search space to find suitable locations for sensors placement. The considered GA then uniformly and optimally positions a user-specified number of sensors, guided by optimization constraints within the fitness function. This approach enhances dense meteorological data collection efficiency, ensuring better data quality and coverage in areas such as weather forecasting, climate studies, and pollution monitoring. It reduces redundancy and deployment costs while maximizing sensors exposure to environmental physical processes such as solar radiation and wind. © 2024 IEEE.

关键词： Semantic Segmentation

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Ternary Memory Composed of Ferroelectric Field-Effect Transistor Based on Dynamic Logic 3

Ternary Memory Composed of Ferroelectric Field-Effect Transi...

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3rd International Conference on Electronics and Information Technology, EIT 2024

作者： Dong, Zhichao Xia, Yinshui Li, Yang Yang, Zhaohui Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China

ISBN: (纸本)9798350369151

Ternary Content Addressable Memory (TCAM) is widely used in development areas such as network routers and machine learning, which are receiving significant attention. Ferroelectric field-effect transistors (FeFETs) are among the most promising devices currently being researched in the field of advanced complementary metal-oxide-semiconductor (CMOS) technology. FeFETs also possess a unique hysteresis in the Ids-Vgs characteristics, which allows the device to function as both a switch and a non-volatile (NV) memory element. Traditional TCAM has the problems of VTH drop or search disturbance. We leverage FeFET property to construct a novel TCAM based on dynamic logic that can be integrated as efficient and compact logic elements into various levels of the memory hierarchy. Due to the slow trend of performance scaling based on Moore's Law and the fact that many computational tasks are now more data-centric than compute-centric, it is highly necessary to design efficient and compact logic elements based on emerging technologies to enhance performance and conserve energy consumption. © 2024 IEEE.

关键词： MOS devices

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