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A Novel Wideband CPW-Fed 5.8GHz RFID Tag Antenna

电子学报(英文版) 2012年第2期21卷 202-208页

作者： LI Huihui MOU Xuanqin JI Zhen YU Hang LI Yan Institute of Image Processing and Pattern Recognition Xi'an Jiaotong University Xi'an 710049 China College of Computer Science and Software Engineering Shenzhen University Shenzhen 518060 China Shenzhen Key Laboratory of Embedded System Design Shenzhen 518060 China

A novel wideband 5.8GHz CPW-fed an- tenna is presented for Radio frequency identification (RFID) tag. Four U-shaped and four L-shaped branches are used as additional resonators to achieve wideband operation. The proposed antenna was analyzed numeri- cally using the Method of moment (MOM) and the Fi- nite element method (FEM). With the antenna size lim- ited to 30 × 30mm2, the ?10dB bandwidth obtained by MOM is 3.235GHz (5.765～9GHz) and the ?9.5dB band- width obtained by FEM is 2.74GHz (5.32～8.06GHz), cor- responding to 55.7% and 47.2% of the center frequency 5.8GHz respectively. Moreover, the simulated results show that the proposed antenna has gain of more than 4.8dBi and the radiation pattern is nearly omnidirectional in the H-plane. The measured ?10dB bandwidth is 2.68GHz (5.63GHz～8.31GHz), 46.2% of the 5.8GHz frequency. Fur- thermore, there are three measured resonant frequencies at 1.34GHz, 3.23GHz and 5.8GHz with lower than ?10dB return loss respectively. The measurement result achieves a wideband RFID tag antenna performance and is in good agreement with the calculated results.

关键词： RFID标签天线尺寸共面波导宽带无线电频率识别有限元分析网络连接数值分析

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Description and verification of dynamic software architectures for distributed systems

Journal of Software

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Journal of Software 2010年第7期5卷 721-728页

作者： Xu, Hongzhen Zeng, Guosun Chen, Bo Department of computer Science and Technology Tongji University Shanghai 201804 China Department of Computer Science and Technology East China Institute of Technology Fuzhou Jiangxi Province 344000 China Embedded System and Service Computing Key Lab of Ministry of Education Shanghai 201804 China

Continuing growth and increasing complexity of distributed software systems make them be more flexible, adaptive and easily extensible. Dynamic evolution or reconfiguration of distributed software systems is one possible solution to meet these demands. However, there are some challenges for building dynamically evolving distributed software systems at runtime, where dynamic software architectures for them is one of the most crucial problems. In this paper, we proposed a formal method of describing and verifying dynamic software architectures for distributed systems using hypergraph grammars. We firstly gave out reconfiguration production rules and operations for software architectures based on hypergraph grammars, and then described dynamic reconfiguration of software architectures for distributed systems according to those rules. At last we verified the invariant property of dynamic software architectures for those systems using model checking, and gave out corresponding verification algorithms. © 2010 ACADEMY PUBLISHER.

关键词： Dynamic models

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A hybrid differential evolution algorithm for meta-task scheduling in grids

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High Technology Letters 2009年第3期15卷 261-266页

作者：康钦马 Jiang Changiun He Hong Huang Qiangsheng The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 P.R. China School of Infomlation Engineering Shandong University at Weihai Weihai 264209 P.R. China

Task scheduling is one of the core steps to effectively exploit the capabilities of heterogeneous re-sources in the *** paper presents a new hybrid differential evolution(HDE)algorithm for findingan optimal or near-optimal schedule within reasonable *** encoding scheme and the adaptation ofclassical differential evolution algorithm for dealing with discrete variables are discussed.A simple but ef-fective local search is incorporated into differential evolution to stress *** performance of theproposed HDE algorithm is showed by being compared with a genetic algorithm(GA)on a known staticbenchmark for the *** results indicate that the proposed algorithm has better perfor-mance than GA in terms of both solution quality and computational time,and thus it can be used to de-sign efficient dynamic schedulers in batch mode for real grid systems.

关键词： Hybrid differential evolution grid computing task scheduling genetic algorithm

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Estimating posterior inference quality of the relational infinite latent feature model for overlapping community detection

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Frontiers of computer Science 2020年第6期14卷 55-69页

作者： Qianchen YU Zhiwen YU Zhu WANG Xiaofeng WANG Yongzhi WANG School of Computer Science and Engineering Northwestern Polytechnical UniversityXi’an 710072China Shanxi Provincial Key Laboratory for Embedded System Xi'an 710072China College of Computer Science and Engineering North Minzu UniversityYinchuan 750021China College of Earth Exploration Science and Technology Jilin UniversityChangchun 130025China

Overlapping community detection has become a very hot research topic in recent decades,and a plethora of methods have been ***,a common challenge in many existing overlapping community detection approaches is that the number of communities K must be predefined *** propose a flexible nonparametric Bayesian generative model for count-value networks,which can allow K to increase as more and more data are encountered instead of to be fixed in *** Indian buffet process was used to model the community assignment matrix Z,and an uncol-lapsed Gibbs sampler has been ***,as the community assignment matrix Zis a structured multi-variable parameter,how to summarize the posterior inference results andestimate the inference quality about Z,is still a considerable challenge in the *** this paper,a graph convolutional neural network based graph classifier was utilized to help tosummarize the results and to estimate the inference qualityabout *** conduct extensive experiments on synthetic data and real data,and find that empirically,the traditional posterior summarization strategy is reliable.

关键词： graph convolutional neural network graph classification overlapping community detection nonparametric Bayesian generative model relational infinite latent feature model Indian buffet process uncollapsed Gibbs sampler posterior inference quality estimation

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Low-rate non-intrusive appliance load monitoring based on graph signal processing

Low-rate non-intrusive appliance load monitoring based on gr...

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2019 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2019

作者： Zhang, Bing Zhao, Shengjie Shi, Qingjiang Zhang, Rongqing Tongji University Key Laboratory of Embedded System and Service Computing of Ministry of Education Shanghai China Tongji University Sch. of Software Eng. the Key Lab. of Embedded System and Service Computing of Ministry of Education Shanghai China Tongji University School of Software Engineering Shanghai China

ISBN: (纸本)9781728159287

Thanks to the large-scale smart meters deployments around the world, non-intrusive appliance load monitoring (NILM) is receiving popularity. It aims to disaggregate the total electricity load of a home into individual appliances without resorting to any specific appliance power monitors. NILM is worthy of broad attention owing to its facilitation in energy savings. This paper regards NILM as a classification task and proposes a two-step method based on graph signal processing (GSP). In the first step, a smoothest solution is obtained by minimizing the regularization term. In the second step, gradient projection method, which uses the obtained minimizer as a start point, is adopted to optimize the while objective function, where NILM is regarded as a constrained nonlinear programming problem. The experiment results based on the open-access data set REDD clearly demonstrate that the proposed GSP-based method achieves improved performance compared with other state-of-the-art low-rate NILM approaches. © 2019 IEEE.

关键词： Signal processing

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Reader activation scheduling in multi-reader RFID systems: A study of general case

Reader activation scheduling in multi-reader RFID systems: A...

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25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011

作者： Tang, Shaojie Wang, Cheng Li, Xiang-Yang Jiang, Changjun Department of Computer Science Illinois Institute of Technology Chicago IL 60616 United States Department of Computer Science Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

ISBN: (纸本)9780769543857

Radio frequency identification (RFID) is a technology where a reader device can "sense" the presence of a close by object by reading a tag device attached to the object. To guarantee the coverage quality, multiple RFID readers can be deployed in the given region. In this paper, we consider the problem of activation schedule for readers in a multi-reader environment. In particular, we try to design a schedule for readers to maximize the number of served tags per time-slot while avoiding various interferences. We first develop a centralized algorithm under the assumption that different readers may have different interference and interrogation radius. Next, we propose a novel algorithm which does not need any location information of the readers. Finally, we extend the previous algorithm in distributed manner in order to suit the case where no central entity exists. We conduct extensive simulations to study the performances of our proposed algorithm. And our evaluation results corroborate our theoretical analysis. © 2011 IEEE.

关键词： Graph theory

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KNOB particle swarm optimizer 1

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1st International Conference on Advances in Swarm Intelligence, ICSI 2010

作者： Zhang, Junqi Liu, Kun Tan, Ying Key Laboratory of Embedded System and Service Computing Department of Computer Science and Technology Tongji University Shanghai 200092 China Department of Machine Intelligence School of Electronics Engineering and Computer Science Peking University Beijing 100871 China

ISBN: (数字)9783642134951

ISBN: (纸本)3642134947

It is not trivial to tune the swarm behavior just by parameter setting because of the randomness, complexity and dynamic involved in particle swarm optimizer (PSO). Hundreds of variants in the literature of last decade, brought various mechanism or ideas, sometimes also from outside of the traditional metaheuristics field, to tune the swarm behavior. While, in the same time, additional parameters have to be afforded. This paper proposes a new mechanism, named KNOB, to directly tune the swarm behavior through parameter setting of PSO. KNOB is defined as the first principal component of the statistical probability sequence of exploration and exploitation allocation along the search process. The using of the KNOB to tune PSO by parameter setting is realized through a statistical mapping, between the parameter set and the KNOB, learned by a radial basis function neural network (RBFNN) simulation model. In this way, KNOB provides an easy way to tune PSO directly by its parameter setting. A simple application of KNOB to promote is presented to verify the mechanism of KNOB. © 2010 Springer-Verlag.

关键词： Particle swarm optimization (PSO)

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A Better Cardinality Estimator with Fewer Bits, Constant Update Time, and Mergeability 42

A Better Cardinality Estimator with Fewer Bits, Constant Upd...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Du, Yang Huang, He Sun, Yu-E Li, Kejian Zhang, Boyu Gao, Guoju Soochow University School of Computer Science and Technology Suzhou China Soochow University School of Rail Transportation Suzhou China Ministry of Education Key Laboratory of Embedded System and Service Computing Shanghai China

ISBN: (纸本)9798350334142

Cardinality estimation is a fundamental problem with diverse practical applications. HyperLogLog (HLL) has become a standard in practice because it offers good memory efficiency, constant update time, and mergeability. Some recent work achieved better memory efficiency, but typically at the cost of impractical update time or losing mergeability, making them incompatible with applications like network-wide traffic measurement. This work presents SpikeSketch, a better cardinality estimator that reduces memory usage of HLL by 37% without sacrificing other crucial metrics. We adopt a bucket-based data structure to promise constant update time, design a smoothed log4 ranking and a spike coding scheme to compress cardinality observables into buckets, and propose a lightweight mergeable lossy compression to balance memory usage, information loss, and mergeability. Then we derive an unbiased estimator for recovering cardinality from the lossy-compressed sketch. Theoretical and empirical results show that SpikeSketch can work as a drop-in replacement for HLL because it achieves a near-optimal MVP (memory-variance-product) of 4.08 (37% smaller than HLL) with constant update time and mergeability. Its memory efficiency even defeats ACPC and HLLL, the state-of-the-art lossless-compressed sketches using linear-time compression to reduce memory usage. © 2023 IEEE.

关键词： Efficiency

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Meta-Heuristic Based Multipath Joint Routing and Scheduling of Time-Triggered Traffic for Time-Sensitive Networking in IIoT 2

Meta-Heuristic Based Multipath Joint Routing and Scheduling ...

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2nd International Conference on Green Communication, Network, and Internet of Things, CNIoT 2022

作者： Chen, Chen Li, Zhong The College of Information Science and Technology Donghua University Shanghai201620 China The Key Laboratory of the Ministry of Education for Embedded System and Service Computing Department of Computer Science Tongji University Shanghai201804 China

ISBN: (纸本)9781510662940

Time-Sensitive networking (TSN) meets the needs of industrial internet of things (IIoT). It solves the challenges of deterministic transmission and reliable communication of time sensitive data streams. Traffic scheduling is the core mechanism of time-sensitive networks. Many excellent researches have explored and optimized the method of scheduling time-triggered streams in TSN. However, the existing time-triggered streams scheduling in TSN mostly separates routing and scheduling, which limits the scalability of scheduling. Many researches are based on fixed routing to schedule streams. Due to the interaction between scheduling and routing, the quality of fixed route solution is inferior to that of joint routing and scheduling. In this paper, we propose a meta-heuristic based multipath joint routing and scheduling method for time-triggered traffic in TSN, named MMRS. We set path selection as a variable and consider multipath routing for fault tolerance. At the same time, we establish the integer linear programming formulation and use meta-heuristic to obtain high-quality solutions. The evaluations show that compared with other excellent routing and scheduling methods, the runtime of 60 streams of MMRS method is reduced by 65.6%, and the schedulability is improved by 21% on average. The experiments verify that our proposed scheduling method can obtain high-quality solutions in an acceptable solution time. © 2023 SPIE.

关键词： Internet of things

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The behavioral sign of account theft: Realizing online payment fraud alert 29

The behavioral sign of account theft: Realizing online payme...

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29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Wang, Cheng Department of Computer Science Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Shanghai Institute of Intelligent Science and Technology Tongji University China

ISBN: (纸本)9780999241165

As a matter of fact, it is usually taken for granted that the occurrence of unauthorized behaviors is necessary for the fraud detection in online payment services. However, we seek to break this stereotype in this work. We strive to design an ex-ante anti-fraud method that can work before unauthorized behaviors occur. The feasibility of our solution is supported by the cooperation of a characteristic and a finding in online payment fraud scenarios: The well-recognized characteristic is that online payment frauds are mostly caused by account compromise. Our finding is that account theft is indeed predictable based on users' high-risk behaviors, without relying on the behaviors of thieves. Accordingly, we propose an account risk prediction scheme to realize the ex-ante fraud detection. It takes in an account's historical transaction sequence, and outputs its risk score. The risk score is then used as an early evidence of whether a new transaction is fraudulent or not, before the occurrence of the new transaction. We examine our method on a real-world B2C transaction dataset from a commercial bank. Experimental results show that the ex-ante detection method can prevent more than 80% of the fraudulent transactions before they actually occur. When the proposed method is combined with an interim detection to form a real-time anti-fraud system, it can detect more than 94% of fraudulent transactions while maintaining a very low false alarm rate (less than 0.1%). © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Crime

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