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Analysis and Design of Mobile Model for DTN

Chinese Journal of Electronics 2023年第4期18卷 635-638页

作者： Zhiting Lin Yugui Qu Yusheng Ji Baohua Zhao Department of Computer Science University of Science and Technology of China Hefei China Province Key Laboratory of Software in Computing and Communication Hefei China Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Japan

Delay tolerant networks may become unexpectedly partitioned due to node mobility or variation in signal strength. However, most widely used models in some relative works are generally very simplistic. In order to exploit intelligent forwarding algorithms, a novel nodal mobile model of delay tolerant networks is presented to map reality with more accuracy. And several approaches are introduced to analyze the network structure, such as n-cliques, n-clans, degree, closeness and betweenness. Our research results showed that the centralizations became smaller when the wireless connections were concerned. It meant that quite a number of nodes became potential relays because of the new structure of networks.

关键词： Wireless communication Analytical models Wireless sensor networks Protocols Social networking (online) Sensitivity analysis Social network theory

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Transferring fashion to surveillance with weak labels

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Neural Computing and Applications 2023年第18期35卷 13021-13035页

作者： Zheng, Qi He, Zheng Liang, Chao Chen, Jun Lin, Chia-Wen Tao, Dapeng National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan430072 China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Wuhan430072 China Collaborative Innovation Center of Geospatial Technology Wuhan430079 China Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan School of Information Science and Engineering Yunnan University Yunnan Kunming650504 China

In this paper, we address the problem of automatic clothing parsing in surveillance images using the information from user-generated tags, such as "jeans" and "T-shirt." Although clothing parsing has achieved great success in the fashion domain, it is quite challenging to parse target under practical surveillance conditions due to the presence of complex environmental interference, such as that from low resolution, viewpoint variations and lighting changes. Our method is developed to capture target information from the fashion domain and apply this information to a surveillance domain by weakly supervised transfer learning. Most target tags convey strong location information (e.g., "T-shirt" is always shown in the upper region), which can be used as weak labels for our transfer method. Both quantitative and qualitative experiments conducted on practical surveillance datasets demonstrate the effectiveness of the proposed surveillance data enhancing method. © 2020, Springer-Verlag London Ltd., part of Springer Nature.

关键词： Monitoring

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Cooperative Task Offloading for Internet of Vehicles in Cloud-edge Computing 23

Cooperative Task Offloading for Internet of Vehicles in Clou...

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23rd IEEE International Conference on High Performance Computing and communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Gu, Linjie Xu, Xiaolong Qi, Lianyong Zhang, Yiwen Zhang, Xuyun Dou, Wanchun Changwang School of Honors Nanjing University of Information Science and Technology Nanjing China School of Computer and Software Nanjing University of Information Science and Technology Nanjing China School of Information Science and Engineering Qufu Normal University China School of Computer Science and Technology Anhui University Anhui China Macquarie University The Department of Computing Sydney Australia Nanjing University State Key Laboratory for Novel Software Technology Nanjing China

ISBN: (纸本)9781665494571

In order to support computing-intensive and service-sensitive Internet of Vehicles (IoV) applications, Digital Twin and edge computing are attractive solutions. Most of the existing IoV service offloading solutions only consider edge-cloud collaboration, but the cooperation between small cell eNodeB(SCeNB) nodes should not be ignored. Through reasonable cooperative computing between nodes, service delays far lower than offloading tasks to the cloud can be obtained. We generate and maintain the simulation of cooperation between SCeNB nodes by constructing a Digital twin to simulate SCeNB nodes in the small cell manager (SCM), thereby realizing user task offloading positions, sub-channel allocation and computing resource allocation. After that, we proposed an algorithm AUC-AC based on the dominant actor critic network and the auction-mechanism. In the DT of each SCeNB node, the global strategy is learned via deep reinforcement learning model. Numerical results show that our proposed experimental scheme is better than several baseline algorithms in terms of service delay. © 2021 IEEE.

关键词： Cloud computing Smart cities Computational modeling Reinforcement learning Digital twins Delays Numerical models

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A Lightweight Authentication Protocol for Mobile RFID

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International Journal of Network Security 2024年第2期26卷 190-199页

作者： Pan, Tao Zuo, Kai-Zhong Wang, Tao-Chun Deng, Chun-Hong College of Internet and Communication Anhui Technical College of Mechanical and Electrical Engineering No.16 Wenjin West Rd. Yijiang Dist. Anhui Province Wuhu City241002 China College of Computer and Information Anhui Normal University China Anhui Key Laboratory of Network and Information Security No.1 Beijing East Rd. Jinghu Dist. Anhui Province Wuhu City241000 China

Recently, Radio Frequency Identification (RFID) has been widely used. A lightweight security authentication protocol for mobile RFID is proposed to aim at the problems of high complexity and system security in existing mobile RFID authentication protocols. The tag identity is encrypted by the matrix’s arrangement and combination of column vectors based on column pseudonyms, which can effectively reduce tag computational complexity. The tag is required to mainly store its identity and shared keys, which can effectively reduce tag storage complexity. During the authentication process, the proposed protocol generates dynamic authentication keys without changing shared keys, which are different in each session. The protocol uses XOR operation to transfer privacy data based on the dynamic authentication keys. This method can effectively reduce the computational complexity of the protocol while protecting privacy data. The protocol requires the receiver to verify the random number in time after receiving information, which can effectively solve the system security problem. Formal proof and analysis results show that the proposed protocol has good security and can resist attacks. The experimental results indicate that the protocol has low complexity, which can effectively reduce the burden of tag operation and storage. It has good value for mobile RFID systems. © (2023), (Femto Technique Co.). All Rights Reserved.

关键词： Authentication

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Delay-Oriented Transaction Packaging Ordering in Sharded Blockchains

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IEEE Transactions on Network Science and Engineering 2025年

作者： Fan, Yuqi Wang, Xiaoyu Wu, Weili Du, Dingzhu Hefei University of Technology School of Computer Science and Information Engineering Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei230601 China University of Texas at Dallas Department of Computer Science RichardsonTX75080 United States

In blockchain, miners make profits by packaging transactions. There are a large number of pending transactions in the blockchain, and users often assign high transaction fees to reduce the delay in transaction packaging. However, in sharded blockchains, it requires more computational and communication resources to process cross-shard transactions than intra-shardtransactions. As a result, miners are inclined to package intra-shard transactions to maximize their profits when packaging transactions, and cross-shard transactions with higher transaction fees are unable to be processed in time, which degrades the quality of service (QoS) of users. That is, the existing transaction packaging methods lack a clear mechanism to ensure that the QoS of users is directly related to the transaction fees they pay. In this paper, we design a new incentive mechanism, such that the block reward is not a fixed value but is related to the transaction processing delay and the number of cross-shard communications involved. The block reward can encourage miners to process transactions in time. We then study how to maximize the total miners’ profit by determining the appropriate transaction packaging order to provide QoS to users. Specifically, we model the problem of transaction packaging ordering in each shard as a delay-oriented transaction processing problem and propose a Transaction Delay Optimization algorithm(TDO). Theoretical analysis proves that TDO is an approximation algorithm for the transaction packaging ordering problem with the approximation ratio of (Formula presented) , given block capacity C and maximum transaction size Smax. We conduct experiments through simulations. Simulation results show that TDO can effectively provide QoS to users and maximize the profits of miners. © 2013 IEEE.

关键词： Labels

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An Effective and Real-time Time-Slot Power Detection Method 23

An Effective and Real-time Time-Slot Power Detection Method

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Proceedings of the 3rd International Conference on Electronic Information Technology and Smart Agriculture

作者： Xian Zhang Xinhui Luo Taiguo Qu Dong Yin School of Computer and Artificial Intelligence (School of Software) Huaihua University China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua University China and Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua University China Department of Art Design Huaihua Tourism School China School of Computer and Artificial Intelligence (School of Software) Huaihua University China

ISBN: (纸本)9798400716775

To efficiently detect the time-slot power of the Time Division Multiple Access (TDMA) communication systems such as repeaters and base stations in real-time. This article designs a signal-sampling hardware circuit based on the Advanced RISC Machine (ARM) platform and proposes a comprehensive method to calculate the time-slot power values. The signal sampling circuit uses the ADC108S052 chip with an 8-channel linked to the ARM via the Serial Peripheral Interface (SPI), and the time-slot power detection approach consists of a signal timing sampling module, sampling data reading module, and sampling data processing module to compute the detected time-slot power comprehensively. We design experiments to evaluate the efficacy of the approach to detect the time-slot power with the system power-on and normality running condition, the detection of the system CPU resource consumption for the time-slot power, the detection of the error value for the time-slot power, etc. The experimental results demonstrate that the approach can be efficient, and real-time detection of the time-slot power of the TDMA system, the system of repeaters and base stations and other systems of signal coverage, optimization and so on is of great significance.

关键词： ARM Analog-to-Digital Converter (ADC) Signal sampling Time division multiple access Time slot power

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Target-Oriented WiFi Sensing for Respiratory Healthcare: from Indiscriminate Perception to In-Area Sensing

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IEEE Network 2024年

作者： Wang, Meng Huang, Jinyang Zhang, Xiang Liu, Zhi Li, Meng Zhao, Peng Yan, Huan Sun, Xiao Dong, Mianxiong Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligence Machine School of Computer and Information Hefei230601 China University of Science and Technology of China CAS Key Laboratory of Electromagnetic Space Information Hefei230026 China The University of Electro-Communications Department of Computer and Network Engineering Tokyo1828585 Japan Guizhou Normal University School of Big Data and Computer Science Guiyang550025 China Muroran Institute of Technology Department of Sciences and Informatics 0508585 Japan

Driven by the vision of integrated sensing and communication (ISAC) toward 6G technology, the WiFi-based respiration sensing approach has emerged as a highly competitive candidate for advanced healthcare services. Nevertheless, the indiscriminate perception of all the moving objects within the sensing area raises challenges for system stability and robustness for real-world deployment, especially for the susceptibility to motion interference from other people. Meanwhile, thanks to the emerging in-area wireless sensing technologies, i.e., beamforming, the dynamic environment tolerance of these technologies gives crucial opportunities for target-oriented WiFi-based healthcare services. This article discusses the compelling intersection of in-area WiFi sensing and the future of target-oriented intelligent respiratory healthcare network services. We first present a novel WiFi-based healthcare-assisting framework tailored for inter-user motion interference-tolerable (IMIT) sensing. The detailed components of low-level signal preprocessing, target-direction signal extraction, and healthcare-related services are discussed. By utilizing CSI beamforming technology, which adjusts a directional beam toward the desired direction and adaptively places beam nulls in noisy directions, we can mitigate motion interference and achieve target-oriented healthcare sensing. Finally, we discuss open challenges and potential solutions for target-oriented WiFi healthcare sensing. © 1986-2012 IEEE.

关键词： Wireless local area networks (WLAN)

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A CPK-Based Identity Authentication Scheme for IoT

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computer Systems Science & Engineering 2022年第3期40卷 1217-1231页

作者： Mingming Zhang Jiaming Mao Yuanyuan Ma Liangjie Xu Chuanjun Wang Ran Zhao Zhihao Li Lu Chen Wenbing Zhao State Grid Jiangsu Electric Power Co. Ltd.Information&Telecommunication BranchNanjing210008China State Grid Key Laboratory of Information&Network Security Institute of Information and CommunicationGlobal Energy Interconnection Research InstituteNanjing210003China Anhui Jiyuan Software Co.Ltd SGITGHefei230088China Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province Research and Development Center of Post Industry Technology of the State Posts Bureau(Internet of Things Technology)Engineering Research Center of Broadband Wireless Communication Technology of the Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing210003China Department of Electrical Engineering and Computer Science Cleveland State UniversityCleveland44115USA

As the power Internet of Things(IoT)enters the security construction stage,the massive use of perception layer devices urgently requires an identity authentication scheme that considers both security and *** existing public key infrastructure(PKI)-based security authentication scheme is currently difficult to apply in many terminals in *** key distribution and management costs are high,which hinders the development of power IoT security *** Public key(CPK)technology uses a small number of seeds to generate unlimited public *** is very suitable for identity authentication in the power Internet of *** this paper,we propose a novel identity authentication scheme for power *** scheme combines the physical unclonable function(PUF)with improved CPK technology to achieve mutual identity authentication between power IoT terminals and *** proposed scheme does not require third-party authentication and improves the security of identity authentication for power ***,the scheme reduces the resource consumption of power IoT *** improved CPK algorithm solves the key collision problem,and the third party only needs to save the private key and the public key *** results show that the amount of storage resources occupied in our scheme is *** proposed scheme is more suitable for the power IoT.

关键词： Power Internet of Things terminal equipment identity authentication CPK PUF

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Secure and Efficient Data Storage and Sharing Scheme Based on Double Blockchain

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computers, Materials & Continua 2021年第1期66卷 499-515页

作者： Lejun Zhang Minghui Peng Weizheng Wang Yansen Su Shuna Cui Seokhoon Kim College of Information Engineering Yangzhou UniversityYangzhou225127China School Math&Computer Science Quanzhou Normal UniversityQuanzhou362000China Division of Computer Science University of AizuAizu–Wakamatsu9658580Japan Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei230601China Medical College of Yangzhou University Yangzhou225001China Department of Gynecology and Obstetrics Affiliated Hospital of Yangzhou UniversityYangzhouChina Department of Computer Software Engineering Soonchunhyang UniversityAsanKorea

In the digital era,electronic medical record(EMR)has been a major way for hospitals to store patients’medical *** traditional centralized medical system and semi-trusted cloud storage are difficult to achieve dynamic balance between privacy protection and data *** storage capacity of blockchain is limited and single blockchain schemes have poor scalability and low *** address these issues,we propose a secure and efficient medical data storage and sharing scheme based on double *** our scheme,we encrypt the original EMR and store it in the *** storage blockchain stores the index of the complete EMR,and the shared blockchain stores the index of the shared part of the *** with different attributes can make requests to different blockchains to share different parts according to their own *** experiments,it was found that cloud storage combined with blockchain not only solved the problem of limited storage capacity of blockchain,but also greatly reduced the risk of leakage of the original *** Extraction Signature(CES)combined with the double blockchain technology realized the separation of the privacy part and the shared part of the original *** symmetric encryption technology combined with Ciphertext-Policy Attribute-Based Encryption(CP–ABE)not only ensures the safe storage of data in the cloud,but also achieves the consistency and convenience of data update,avoiding redundant backup of *** analysis and performance analysis verified the feasibility and effectiveness of our scheme.

关键词： Cloud storage blockchain electronic medical records access control data sharing privacy

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Adaptive Student Inference Network for Efficient Single Image Super-Resolution

Adaptive Student Inference Network for Efficient Single Imag...

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IEEE International Conference on Data Mining (ICDM)

作者： Kang Miao Zhao Zhang Jiahuan Ren Mingbo Zhao Haijun Zhang Richang Hong School of Computer Science and Information Engineering Hefei University of Technology Hefei China Key Laboratory of Knowledge Engineering with Big Data (Ministry of Education) & Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Hefei China Yunnan Key Laboratory of Software Engineering Kunming China School of Information Science and Technology Donghua University Shanghai China Department of Computer Science Harbin Institute of Technology (Shenzhen) Shenzhen China

Recent advances in single image super-resolution (SISR) have achieved remarkable performance through deep learning. However, the high computational cost hinders the deployment of SISR models on edge devices. Instead of proposing new SISR models, a new trend is emerging to improve network efficiency by reducing parameters, FLOPs, and inference time through slight modifications to the original models. However, recent methods usually focus on reducing only one of three metrics, i.e., FLOPs, parameters and inference time, which inevitably increases the other two metrics. In this paper, we propose a novel Adaptive Student Inference Network (ASIN) on popular SISR models, which aims at reducing FLOPs and inference time while maintaining the number of parameters and restoring clearer high-resolution images. Specifically, our ASIN divides a SISR model into three components (head, body and tail) and adopts various strategies for each part. For head and tail parts, to ensure the restored images contain more detailed information, a novel auxiliary Enhanced Teacher Network (ETNet) is designed, which is trained with the ground-truth images to obtain more prior knowledge to guide student network to extract more accurate textures using a new knowledge distillation method. For the body part, owing to the varying difficulties of the reconstructions in different regions, we propose an Adaptive Depth Predicted Module (ADPM) to dynamically shorten average depth of network to reduce the computational cost of overall network. Extensive experiments on two datasets demonstrate the effectiveness and state-of-the-art performance of our ASIN compared to its counterparts.

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