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IEEE 802.16 Mesh Network SA Management Mechanism Based on Multi-hops Mutual Authentication

Wang Xingjian,Hu Aiqun,Huang Yuhua

Strategic Study of CAE 2006, Volume 8, Issue 9,   Pages 69-73

Abstract:

Mesh network supported by IEEE802.16-2004 wireless-MAN standard is a fresh network combining tree

Keywords： IEEE 802.16     mesh     node     multi-hops mutual authentication     self-modified routing    

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Minimum Reserved Traffic Rate Based Fair Scheduling Algorithm in IEEE 802.16e

Shi Juncai,Hu Aiqun,Guan Yanfeng

Strategic Study of CAE 2008, Volume 10, Issue 2,   Pages 54-59

Abstract:

According to the characteristics of IEEE 802.16-2005, a minimum reserved traffic rate based fair scheduling algorithm in IEEE 802.16-2005 is proposed in this paper.The algorithm pro posed in this paper is in accordance with IEEE 802-16-2005 and has gre at value.

Keywords： IEEE 802-16-2005     scheduling algorithm     QoS     fairness    

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Maximizing power saving with state transition overhead for multiple mobile subscriber stations in WiMAX Article

Bo LI,Sung-kwon PARK

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 10,   Pages 1085-1094 doi: 10.1631/FITEE.1500314

Abstract: In the IEEE 802.16e/m standard, three power saving classes (PSCs) are defined to save the energy of aThus, many algorithms were proposed to set the PSCs in IEEE 802.16 networks.

Keywords： Power saving class     State transition overhead     IEEE 802.16e/m     Quality of service    

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Transactive Demand Response Operation at the Grid Edge using the IEEE 2030.5 Standard Article

Javad Fattahi, Mikhak Samadi, Melike Erol-Kantarci, Henry Schriemer

Engineering 2020, Volume 6, Issue 7,   Pages 801-811 doi: 10.1016/j.eng.2020.06.005

Abstract: comprehensive TDR use case that is fully compliant with the Institute of Electrical and Electronics Engineers (IEEEextended time period, we engage in multiple TDR scenarios, and demonstrate with a fully-functional IEEE

Keywords： Transactive demand response     IEEE 2030.5     Smart grid     Multi-agent system     Neighborhood coordination    

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A novel method to investigate voltage stability of IEEE-14 bus wind integrated system using PSAT

Satish KUMAR,Ashwani KUMAR,N. K. SHARMA

Frontiers in Energy 2020, Volume 14, Issue 2,   Pages 410-418 doi: 10.1007/s11708-016-0440-8

Abstract: The PF and load flow results are used to calculate line indices for the IEEE-14 bus test system which

Keywords： voltage stability     line indices     power system analysis tool box (PSAT)     wind system     line loading     power flow (PF)    

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The Security Analysis for Enhanced Data Encryption Schemes in IEEE802.11/11b WLAN

Song Yubo,Hu Aiqun,Cai Tianyou

Strategic Study of CAE 2004, Volume 6, Issue 10,   Pages 32-38

Abstract:

As an expansion of LAN, the WLAN reduce the cost of building a network infrastructure, to enjoy the mobile, high-quality, multimedia services. The 802.11 standard for wireless networks includes a Wired Equivalent Privacy (WEP) protocol, which is used to protect link-layer communications from eavesdropping and other attacks. Several serious security flaws in this protocol have been discovered and some solutions have been proposed to enhance WEP security. However, it is doubtful whether they can provide enough security as these solutions lack precisely security analysis. In this paper, concrete security analyses of various enhancing mechanisms are given. Results show that these mechanisms indeed increase security and bring significant, provable security gains in WLAN environment. The authors quantify the security as a function of the security of the primitives used, thereby enabling a user to decide how to construct an enhanced mechanism for desired demands.

Keywords： WLAN     encryption     WEP     rekey    

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IEEE第三届电子技术(IEEE ICET 2020)

Conference Date: 8 May 2020

Conference Place: 四川成都

Administered by: ICET 2020

Capacity of VoIP in IEEE 802.11 Wireless LAN

Chen Liquan,Hu Aiqun,Zhou Xueli

Strategic Study of CAE 2005, Volume 7, Issue 7,   Pages 81-85

Abstract: calculate the upper bound number of simultaneous VoIP calls that can be supported in a single cell of an IEEE

Keywords： wireless LAN     voice over IP     capacity     Markov chain    

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IEEE第三届电路、系统与器件（ICCSD 2019）

Conference Date: 23 Aug 2019

Conference Place: 四川成都

Administered by: ICCSD 2019

Impact evaluation of large scale integration of electric vehicles on power grid

Rabah BOUDINA, Jie WANG, Mohamed BENBOUZID, Farid KHOUCHA, Mohamed BOUDOUR

Frontiers in Energy 2020, Volume 14, Issue 2,   Pages 337-346 doi: 10.1007/s11708-018-0550-6

Abstract: power flow analysis and the dynamic response of the grid parameters variation are presented, taking the IEEE

Keywords： PHEV     vehicle-to-grid (V2G)     technical impact     IEEE 14 bus     power flow analysis    

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Artificial intelligence in impact damage evaluation of space debris for spacecraft Editorial

BAO, Chun YIN, Xuegang HUANG, Wei YI, Sara DADRAS,chunyin@uestc.edu.cn,kusso@uestc.edu.cn,s_dadras@ieee.org

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 4,   Pages 511-514 doi: 10.1631/FITEE.2220000

Abstract: Since the first artificial satellite was launched in 1957, increasing human space activities have led to a deteriorating space debris environment. A huge amount of tiny space debris (from millimeter to micron level) appears in the Earth’s orbit, and its hypervelocity impact will cause serious damage to the structure and functional units of the spacecraft, including cabin’s outer surface, thermal barrier materials, thermal control coatings, solar panels, pipes, and cables. To ensure the safe operation of spacecraft and the completion of space missions, it is necessary to detect and evaluate the impact damage caused by space debris to provide risk warning and timely repair. Due to the complex outer surface materials of spacecraft and the unpredictability of impact damage events, the collected damage detection data present various complex characteristic information. Traditional damage identification and evaluation methods based on manual extraction of feature parameters have difficulty in accurately describing the above complex feature information. In recent years, the application of artificial intelligence (AI) technology in space debris impact perception, damage detection, risk assessment, etc. has begun to receive extensive attention from scholars and engineers, and some breakthroughs have been made in solving such very difficult engineering and technical problems. However, there are still many difficult problems to be solved in the application of AI technology to deal with the issue of space debris. With this background, several important tendencies have emerged in the use of AI methods for spacecraft damage detection and evaluation. 1. Various AI learning algorithms (such as neural networks and deep learning) are used and combined to effectively detect and classify damage features. AI learns in a variety of ways, and each learning algorithm is good at solving different problems. Combining multiple AI learning algorithms in different scenarios can improve detection efficiency and classify damage features. 2. Modifications and enhancements to the learning algorithm are explored to perform damage pattern recognition and evaluation more accurately and effectively. To improve the performance of the learning algorithm, modifications and enhancements are essential. Modifications and enhancements to the algorithm itself, including the setting of the loss function, optimization of iterative steps, and judgment of termination conditions, will have a significant impact on the performance of the learning algorithm. In addition, the complex learning algorithm network itself has a large number of parameters that need to be optimized. In fact, the optimization method of network parameters has become one of the core factors that determine the performance of the learning algorithm. 3. AI learning algorithms and models should preferably be extended to suit spacecraft damage detection and evaluation systems. In combination with specific spacecraft damage detection and assessment systems, existing learning algorithms and models can be extended by, e.g., preprocessing the actual input test data to obtain better algorithm iterative calculation results, classifying different damage detection scenarios, applying different optimization modules to obtain better performance comparison test results, and giving reasonable classification criteria for damage assessment results. 4. AI technology is used to analyze the data characteristics of various spacecraft impact damage samples to guide the space debris protection design of spacecraft. The advantage of AI technology is that it can analyze typical characteristics from a large number of data samples. By analyzing the impact damage samples of various types of spacecraft and according to the detection data characteristics under different impact conditions, researchers can obtain the damage type and damage degree of the spacecraft’s space debris protection structure. Therefore, engineers can improve the safety of spacecraft in orbit by optimizing the protective structure of the spacecraft. 5. AI technology is used to model and analyze space debris to realize the monitoring, early warning, mitigation, and removal of space debris to reduce the impact of space debris on spacecraft. Using AI technology to model and analyze space debris has a stronger expressive ability, which can express complex and qualitative empirical knowledge that is difficult to describe with mathematical formulas. AI modeling can be modified and expanded according to the new understanding of space debris model knowledge, and the system can be more flexible to adapt to new needs. The clearer the modeling and analysis results of space debris are, the more accurate the monitoring, early warning, mitigation, and removal of debris impacts are, thereby greatly reducing the impact of space debris on spacecraft. In short, spacecraft damage feature extraction and damage assessment are critical to the development of the aerospace industry, and these challenges call for new methods and techniques to stimulate the continuous efforts of aerospace equipment research, pattern recognition, and AI. In this context, the journal has organized a special feature on the application of AI in the space environment and spacecraft. This special feature focuses on spacecraft damage detection and assessment methods based on AI learning from detection data, including the hierarchical correlation analysis of spacecraft damage characteristics and detection data, and the construction of spacecraft damage assessment models based on AI analysis methods. After a rigorous review process, five research articles were selected for this feature.
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第6届 IEEE 产业经济系统与产业安全工程国际学术会议

Conference Date: 26 Jul 2019

Conference Place: 北京

Administered by: IEEE 物流信息化和产业安全系统专业委员会

Developing a power monitoring and protection system for the junction boxes of an experimental seafloor observatory network

Jun WANG,De-jun LI,Can-jun YANG,Zhi-feng ZHANG,Bo JIN,Yan-hu CHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 12,   Pages 1034-1045 doi: 10.1631/FITEE.1500099

Abstract: , which is necessary for synchronizing the times within and across nodes, was generated through the IEEE

Keywords： Power monitoring and protection     Embedded processor     Seafloor observatory network     IEEE 1588     Junction    

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第19届IEEE通信技术国际会议(ICCT 2019)

Conference Date: 16 Oct 2019

Conference Place: 陕西西安

Administered by: ICCT 2019

IEEE SENSORS 2019

Conference Date: 27 Oct 2019

Conference Place: 加拿大/蒙特利尔

Administered by: Institute of Electrical and Electronics Engineers

Title Author Date Type Operation

IEEE 802.16 Mesh Network SA Management Mechanism Based on Multi-hops Mutual Authentication

Wang Xingjian,Hu Aiqun,Huang Yuhua

Journal Article

Minimum Reserved Traffic Rate Based Fair Scheduling Algorithm in IEEE 802.16e

Shi Juncai,Hu Aiqun,Guan Yanfeng

Journal Article

Maximizing power saving with state transition overhead for multiple mobile subscriber stations in WiMAX

Bo LI,Sung-kwon PARK

Journal Article

Transactive Demand Response Operation at the Grid Edge using the IEEE 2030.5 Standard

Javad Fattahi, Mikhak Samadi, Melike Erol-Kantarci, Henry Schriemer

Journal Article

A novel method to investigate voltage stability of IEEE-14 bus wind integrated system using PSAT

Satish KUMAR,Ashwani KUMAR,N. K. SHARMA

Journal Article

The Security Analysis for Enhanced Data Encryption Schemes in IEEE802.11/11b WLAN

Song Yubo,Hu Aiqun,Cai Tianyou

Journal Article

IEEE第三届电子技术(IEEE ICET 2020)

8 May 2020

Conference Information

Capacity of VoIP in IEEE 802.11 Wireless LAN

Chen Liquan,Hu Aiqun,Zhou Xueli

Journal Article

IEEE第三届电路、系统与器件（ICCSD 2019）

23 Aug 2019

Conference Information

Impact evaluation of large scale integration of electric vehicles on power grid

Rabah BOUDINA, Jie WANG, Mohamed BENBOUZID, Farid KHOUCHA, Mohamed BOUDOUR

Journal Article

Artificial intelligence in impact damage evaluation of space debris for spacecraft

BAO, Chun YIN, Xuegang HUANG, Wei YI, Sara DADRAS,chunyin@uestc.edu.cn,kusso@uestc.edu.cn,s_dadras@ieee.org

Journal Article

第6届 IEEE 产业经济系统与产业安全工程国际学术会议

26 Jul 2019

Conference Information

Developing a power monitoring and protection system for the junction boxes of an experimental seafloor observatory network

Jun WANG,De-jun LI,Can-jun YANG,Zhi-feng ZHANG,Bo JIN,Yan-hu CHEN

Journal Article

第19届IEEE通信技术国际会议(ICCT 2019)

16 Oct 2019

Conference Information

IEEE SENSORS 2019

27 Oct 2019

Conference Information