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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 IEEE1588 (precision clock synchronization protocol for networked measurement and control systems) time synchronization

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

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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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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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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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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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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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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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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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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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Theory and techniques for "intellicise" wireless networks Editorial

QUEK, Bo RONG,pzhang@bupt.edu.cn,pmg@bupt.edu.cn,shuguangcui@cuhk.edu.cn,ning_ming@zju.edu.cn,g.mao@ieee.org

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 1,   Pages 1-4 doi: 10.1631/FITEE.2210000

Abstract: With the acceleration of a new round of global scientific, technological, and industrial revolution, the next generation of information and communication technology, i.e., 6G, will inject new momentum into industry transformation and upgrad-ing, as well as into economic innovation and development. This will subsequently promote a global industrial integration. Wireless communication will be ubiquitous in all areas of future society, supporting novel applications with various performance requirements, such as immersive- or interactive-experience applications requiring a large bandwidth, autonomous driving and vehicle-to-everything applications requiring ultra-high reliability and ultra-low latency, and applications for industrial Internet requiring massive machine-type connectivity. Facing the challenges of the post-Moore and post-pandemic era, wireless communication needs breakthroughs in network architecture to improve the intelligence, security, robustness, bandwidth, and heterogeneity. With this background, several important tendencies have emerged in the development of 6G wireless communications: 1. Future wireless networks will evolve from “human-to-human” communications into intelligent “human-to-machine” communications. In addition to enabling communications among humans, future wireless networks will be able to support close connections among humans and machines. The behavior and intent of humans will be sensed and communicated to machines that will accordingly adjust their operations. Typical scenarios include smart building, intelligent transportation, mixed reality (MR), and others. 2. Network nodes will evolve from carrying out only traditional communications to carrying out communication, sensing, computation, management, and caching in an integrated manner. To meet the diverse service requirements of mobile MR, intelligent transportation, industrial Internet of Things, and other areas, future networks will possess multiple functionalities. For example, by sensing human head position, pre-caching necessary content, and rendering high-quality images, network nodes can provide fully immersive MR experiences. In addition, with artificial intelligence (AI), network nodes can manage multi-dimensional resources in an on-demand fashion, where intent-driven network management and control can be realized. 3. Network architecture will focus on collaborations between the cloud and the network edge, which will become more heterogenous. To shorten latency and alleviate the backhaul/fronthaul burden, the network edge must collaborate with the cloud. The first method of collaboration is that the cloud finishes AI model training and then deploys AI models into the network edge, which supports the so-called edge intelligence. In the second method, users demanding high throughput are served via a cloud radio access mode, while users requiring ultra-low latency can benefit from edge computation and caching. As for architecture heterogeneity, future networks are envisioned to incorporate unmanned aerial vehicle (UAV) networks, satellite communica-tion networks, and dense cellular networks, bringing three-dimensional and hierarchical network coverage. In short, the evolution of existing 5G technolo-gies and the development of 6G need to address more stringent and diverse application scenarios, a more strict energy constraint, and the orchestration of multi-dimensional resources. These challenges call for an intellicise wireless network operation paradigm, where “intellicise” is a new adjective that we coin, standing for intelligence-endogenous and primitive-concise. Built upon the integration of AI and next-generation networking technologies, an intellicise wireless network continually explores and exploits new intelligent primitives, e.g., semantic base (Seb) in semantic communications, proactively takes sys-tematic entropy reduction as the global optimization objective, adaptively reshapes the core models of information systems, and ultimately endows itself with endogenous intelligence and primitive conciseness. In this context, the journal has organized a special feature on the theory and techniques for intellicise wireless networks. This special feature covers information theory, architecture design, and intellicise wireless networks for achieving air-space-ground-sea integration, resource management, hardware testbeds and platforms, as well as related applications. In addition, this feature is intended to provide a review of advancements and future research directions in the research field of intellicise wireless networks. After a rigorous review process, six papers have been selected for this feature, including one review article and five research articles.
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Vector soliton and noise-like pulse generation using a Ti3C2 MXene material in a fiber laser Research

Shuai Wang, Lei Li, Yu-feng Song, Ding-yuan Tang, De-yuan Shen, Lu-ming Zhao,sdulilei@gmail.com,lmzhao@ieee.org

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 3,   Pages 287-436 doi: 10.1631/FITEE.2000033

Abstract: We built a Tm:Ho co-doped fiber laser using a TiC material as a saturable absorber (SA). The formation of s (VSs) and s (NLPs) was observed. The SA was prepared by dripping a TiC solution on a side-polished D-shaped fiber and then naturally vaporized. The VS is characterized by two coexisting sets of Kelly sidebands. By modulating the polarization controller in the fiber laser, NLPs with about 3.3 nm bandwidth can be switched from the VS. To the best of our knowledge, this is the first time that VSs have been generated in a fiber laser using a TiC material as the SA.

Keywords： 矢量孤子；类噪声脉冲；MXene；光纤激光器    

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Networks Innovation Institute, China A preliminary version was presented at the IEEE Article

Peng XIAO,Zhi-yang LI,Song GUO,Heng QI,Wen-yu QU,Hai-sheng YU

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 7,   Pages 620-633 doi: 10.1631/FITEE.1500350

Abstract: As a novel architecture, software-defined networking (SDN) is viewed as the key technology of future networking. The core idea of SDN is to decouple the control plane and the data plane, enabling centralized, flexible, and programmable network control. Although local area networks like data center networks have benefited from SDN, it is still a problem to deploy SDN in wide area networks (WANs) or large-scale networks. Existing works show that multiple controllers are required in WANs with each covering one small SDN domain. However, the problems of SDN domain partition and controller placement should be further addressed. Therefore, we propose the spectral clustering based partition and placement algorithms, by which we can partition a large network into several small SDN domains efficiently and effectively. In our algorithms, the matrix perturbation theory and eigengap are used to discover the stability of SDN domains and decide the optimal number of SDN domains automatically. To evaluate our algorithms, we develop a new experimental framework with the Internet2 topology and other available WAN topologies. The results show the effectiveness of our algorithm for the SDN domain partition and controller placement problems.

Keywords： Software-defined networking (SDN)     Controller placement     K self-adaptive method    

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Title Author Date Type Operation

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

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

Shi Juncai,Hu Aiqun,Guan Yanfeng

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

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

Wang Xingjian,Hu Aiqun,Huang Yuhua

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

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

Bo LI,Sung-kwon PARK

Journal Article

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

Song Yubo,Hu Aiqun,Cai Tianyou

Journal Article

Capacity of VoIP in IEEE 802.11 Wireless LAN

Chen Liquan,Hu Aiqun,Zhou Xueli

Journal Article

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

Theory and techniques for "intellicise" wireless networks

QUEK, Bo RONG,pzhang@bupt.edu.cn,pmg@bupt.edu.cn,shuguangcui@cuhk.edu.cn,ning_ming@zju.edu.cn,g.mao@ieee.org

Journal Article

Vector soliton and noise-like pulse generation using a Ti3C2 MXene material in a fiber laser

Shuai Wang, Lei Li, Yu-feng Song, Ding-yuan Tang, De-yuan Shen, Lu-ming Zhao,sdulilei@gmail.com,lmzhao@ieee.org

Journal Article

Networks Innovation Institute, China A preliminary version was presented at the IEEE

Peng XIAO,Zhi-yang LI,Song GUO,Heng QI,Wen-yu QU,Hai-sheng YU

Journal Article