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Online Spectrum partitioning for LTE-U and WLAN Coexistence in Unlicensed Spectrum

IEEE TRANSACTIONS ON COMMUNICATIONS 2020年第1期68卷 506-520页

作者： Wu, Weihua Yang, Qinghai Liu, Runzi Quek, Tony Q. S. Kwak, Kyung Sup Xidian Univ Sch Telecommun Engn State Key Lab ISN Xian 710071 Peoples R China Xian Univ Architecture & Technol Sch Informat & Control Engn Xian 710055 Peoples R China Singapore Univ Technol & Design Informat Syst Technol & Design Pillar Singapore 487372 Singapore Inha Univ Dept Informat & Commun Engn Incheon 22212 South Korea

Long-term evolution (LTE) and wireless local area network (WLAN) are often presented as opposing technologies. Hence, efficient partitioning of the spectrum resources carries critical importance for achieving the coexistence of these on the unlicensed spectrum band. In this paper, we firstly develop an online spectrum partitioning algorithm, which needs little signal transmission and exchange between coordination manager and networks. Then, we focus on the convergence analysis of the online spectrum partitioning algorithm, which is difficult due to the time-varying wireless channels. To overcome this challenge, we model the algorithm and network dynamics as the stochastic differential equations (SDE) and show that the algorithm convergence is equivalent to the stochastic stability of a virtual stochastic dynamic system constructed by the SDEs. Then, we give the sufficient condition about the algorithm convergence and the upper bound on the tracking error of the spectrum partitioning algorithm under exogenous variations of time-varying channel state information (CSI). Based on the insights of the impact of time-varying CSI on algorithm convergence, an online compensative spectrum partitioning algorithm is developed to offset the tracking error caused by the disturbance of time-varying CSI. Through performance evaluation, we show that the coexistence performance efficiency will come at low expense of algorithm complexity and signal overhead.

关键词： partitioning algorithms Wireless LAN Heuristic algorithms Convergence Long Term Evolution Stochastic processes Wireless communication Unlicensed spectrum spectrum partitioning continuous-time Lyapunov drift

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Uniform partitioning of Data Grid for Association Detection

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2022年第2期44卷 1098-1107页

作者： Mousavi, Ali Baraniuk, Richard G. Google Res Kirkland WA 98033 USA Rice Univ Dept Elect & Comp Engn Houston TX 77005 USA

Inferring appropriate information from large datasets has become important. In particular, identifying relationships among variables in these datasets has far-reaching impacts. In this article, we introduce the uniform information coefficient (UIC), which measures the amount of dependence between two multidimensional variables and is able to detect both linear and non-linear associations. Our proposed UIC is inspired by the maximal information coefficient (MIC) [1].;however, the MIC was originally designed to measure dependence between two one-dimensional variables. Unlike the MIC calculation that depends on the type of association between two variables, we show that the UIC calculation is less computationally expensive and more robust to the type of association between two variables. The UIC achieves this by replacing the dynamic programming step in the MIC calculation with a simpler technique based on the uniform partitioning of the data grid. This computational efficiency comes at the cost of not maximizing the information coefficient as done by the MIC algorithm. We present theoretical guarantees for the performance of the UIC and a variety of experiments to demonstrate its quality in detecting associations.

关键词： Microwave integrated circuits Mutual information partitioning algorithms Heuristic algorithms Dynamic programming Extraterrestrial measurements Correlation Detection estimation correlation mutual information k-nearest neighbor

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Multiway VLSI circuit partitioning based on dual net representation

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 1996年第4期15卷 396-409页

作者： Cong, J Labio, WJ Shivakumar, N Department of Computer Science University of California Los Angeles CA USA Department of Computer Science University of Stanford Stanford CA USA

In this paper, we study the area-balanced multiway partitioning problem of VLSI circuits based on a new dual netlist representation named the hybrid dual netlist (HDN), and propose a general paradigm for multiway circuit partitioning based on dual net transformation, Given a netlist, we first compute a K-way partitioning of nets based on the HDN representation, and then transform the K-way net partition into a K-way module partitioning solution, The main contribution of our paper is in the formulation and solution of the ii-way module contention (K-MC) problem, which determines the best assignment of the modules in contention to partitions while maintaining user-specified area requirements when we transform the net partition into a module partition. Under a natural definition of binding function between nets and modules, and preference function between partitions and modules, we show that the ii-MG problem can be reduced to a min-cost max-flow problem, We present an efficient solution to the ii-MG problem based on network flow computation, We apply our dual. transformation paradigm to the well-known ii-way Fiduccia-Mattheyses (FM) partitioning algorithm (K-FM) and show that the new algorithm, named K-DualFM, reduces the net cutsize by 20% to 31% compared with the K-FM algorithm, We also apply the same paradigm to the ii-maximum fanout-free cone (MFFC)-FM algorithm, a K-FM algorithm based on MFFC clustering, and show that the resulting algorithm, K-DualMFFC-FM reduces the net cutsize by 15% to 26% compared with K-MFFC-FM. Furthermore, we compare the K-DualFM algorithm with EIG1 and Paraboli, two recently proposed spectral-based bipartitioning algorithms, We showed that K-DualFM reduces the net cutsize by 56% on average when compared with EIG1 and produces comparable results with Paraboli.

关键词： Very large scale integration Circuits partitioning algorithms Clustering algorithms Iterative algorithms Computer networks Computational modeling Computer science Iterative methods

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Simultaneous Optimization of Optical Communication Link Placement and partitioning of Wide-Area Protection System in Smart Grids

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IEEE TRANSACTIONS ON POWER DELIVERY 2021年第5期36卷 3140-3149页

作者： Jia, Huibin Liu, Chuan Gai, Yonghe Ma, Jing North China Elect Power Univ Dept Elect & Commun Engn Baoding 071000 Peoples R China Global Energy Interconnect Res Inst Co Ltd Beijing Peoples R China North China Elect Power Univ Dept Elect & Commun Engn Beijing Peoples R China State Key Lab Alternate Elect Power Syst Renewabl Beijing Peoples R China

Based on modern sensors, communication networks and computing technologies, wide-area protection system (WAPS) can acquire electrical quantities to precisely locate faults in smart grids. In WAPS, the communication network is responsible for rapidly and reliably transmitting data between a regional master station and its slave stations. The real-time data transmission is heavily dependent on the communication link (CL) placement. In addition to the rational partitioning of WAPS, the CL placement should be chosen so as to ensure the good performance of WAPS. The aim of this study is to extend the traditional partitioning of WAPS to the simultaneous optimization problem of partitioning and optical CL placement. The simultaneous optimization problem is formalized so as to minimize the construction cost of WAPS. Besides the optical CL placement and partitioning, to ensure the reliable and real-time transmission of data, the link bandwidth and cost of each optical CL is also captured in the optimization problem. Finally, numerical simulations are carried out on the IEEE 39-bus, 57-bus and 118-bus standard testing cases. The simulation results illustrate that the optical CL scheme can be non-negligible and that it will significantly influence the partitioning of WAPS.

关键词： Optimization Substations Bandwidth Optical fiber communication Communication networks Smart grids partitioning algorithms Communication link partitioning placement smart grid wide-area protection

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3-D partitioning for Large-Scale Graph Processing

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IEEE TRANSACTIONS ON COMPUTERS 2021年第1期70卷 111-127页

作者： Li, Xue Zhang, Mingxing Chen, Kang Wu, Yongwei Qian, Xuehai Zheng, Weiming Tsinghua Univ Dept Comp Sci & Technol Beijing Natl Res Ctr Informat Sci & Technol BNRis Beijing 100084 Peoples R China Tsinghua Univ Grad Sch Shenzhen Beijing 100084 Peoples R China Sangfor Inc Shenzhen Peoples R China Univ Southern Calif Ming Hsieh Dept Elect Engn Dept Comp Sci Los Angeles CA 90007 USA

Disk I/O is the major performance bottleneck of existing out-of-core graph processing systems. We found that the total I/O amount can be reduced by loading more vertices into memory every time. Although task partitioning of a graph processing system is traditionally considered equivalent to the graph partition problem, this assumption is untrue for many Machine Learning and Data Mining (MLDM) problems: instead of a single value, a vector of data elements is defined as the property for each vertex/edge. By dividing each vertex into multiple sub-vertices, more vertices can be loaded into memory every time, leading to less amount of disk I/O. To explore this new opportunity, we propose a category of 3-D partitioning algorithm that considers the hidden dimension to partition the property vector. The 3-D partitioning algorithm provides a new tradeoff to reduce communication costs, which is adaptive to both distributed and out-of-core scenarios. Based on it, we build a distributed graph processing system CubeSingleCube. Since network traffic is significantly reduced, Cube outperforms state-of-the-art graph-parallel system PowerLyra by up to 4.7x. By largely reducing the disk I/O amount, the performance of SingleCube is significantly better than state-of-the-art out-of-core system GridGraph (up to 4.5x).

关键词： partitioning algorithms Task analysis Programming Loading Memory management Microsoft Windows Computational efficiency Graph processing task partitioning distributed systems disk I/O big data

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RATIO CUT partitioning FOR HIERARCHICAL DESIGNS

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 1991年第7期10卷 911-921页

作者： WEI, YC CHENG, CK Department of Computer Science and Engineering University of California San Diego La Jolla CA USA

Circuit partitioning is an important process for hierarchical designs. A good partitioning can significantly improve circuit performance and reduce layout costs. This paper proposes a partitioning approach called ratio cut. We demonstrate that the ratio cut algorithm can locate the clustering structures in the circuit. Finding the optimal ratio cut is NP-complete. However, in certain cases the ratio cut can be solved by linear programming techniques via the multicommodity flow formulation. We also propose a fast heuristic algorithm running in linear time with respect to the number of pins in the circuit. Experiments show good results in all tested cases.

关键词： Very large scale integration Costs Matrix decomposition partitioning algorithms Silicon Circuit optimization Clustering algorithms Linear programming Pins Circuit testing

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A non-centralized predictive control strategy for wind farm active power control: A wake-based partitioning approach

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RENEWABLE ENERGY 2020年 150卷 656-669页

作者： Siniscalchi-Minna, Sara Bianchi, Fernando D. Ocampo-Martinez, Carlos Luis Dominguez-Garcia, Jose De Schutter, Bart IREC Catalonia Inst Energy Res Jardins Dones Negre S-N Barcelona 08930 Spain Consejo Nacl Invest Cient & Tecn Av Eduardo Madero 399C1106ACD Buenos Aires DF Argentina ITBA Av Eduardo Madero 399C1106ACD Buenos Aires DF Argentina UPC CSIC Inst Robot & Informat Ind Automat Control Dept Llorens i Artigas 4-6 Barcelona 08028 Spain Delft Univ Technol Delft Ctr Syst & Control Delft Netherlands

Owing to wake effects, the power production of each turbine in a wind farm is highly coupled to the operating conditions of the other turbines. Wind farm control strategies must take into account these couplings and produce individual power commands for each turbine. In this case, centralized control approaches might be prone to failures due to the high computational burden and communication dependency. To overcome this problem, this paper proposes a non-centralized scheme based on splitting the wind farm into almost uncoupled sets of turbines by solving a mixed-integer partitioning problem. In each set of turbines, a model predictive control strategy seeks to optimize the distribution of the power set-points among turbines such that the impact of the power losses due to the wake effect is reduced. Then, a supervisory controller coordinates the generation of each group to satisfy the power demanded by the grid operator. The effectiveness of the proposed control scheme in terms of reduction of computational costs and power regulation is confirmed by simulations for a wind farm of 42 turbines. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Wind farm control Non-centralized control partitioning algorithms Model predictive control Wake effect

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Optimizing Vertex Pressure Dynamic Graph partitioning in Many-Core Systems

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IEEE TRANSACTIONS ON COMPUTERS 2021年第6期70卷 936-949页

作者： McCrabb, Andrew Bertacco, Valeria Univ Michigan Coll Engn Elect Engn & Comp Sci Ann Arbor MI 48109 USA

With the rise of graph-based algorithms in many applications, dynamic graphs have become critical for applications that work with real-time or time-series relationship data. Due to their large storage footprint, these applications require high parallelism and locality. Many-core architectures offer high parallelism for both static and dynamic graphs. However, systems operating on dynamic graphs must continuously repartition graph data across storage units to achieve good locality, load balancing, and performance. In this work, we examine the effectiveness and efficiency of different vertex-pressure repartitioning schemes, which move vertices so to co-locate them near their most relevant neighbors. We describe key repartitioning design choices and provide a thorough evaluation of the impact of a range of design features with different datasets. Our evaluation indicates that optimized dynamic repartitioning techniques can often provide over 2x performance speedup over state-of-the-art static solutions.

关键词： Heuristic algorithms Bandwidth Social networking (online) partitioning algorithms Market research Arrays Transportation Graphs and networks graph algorithms hardware

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Non-Euclidean Grid-partitioning to Mitigate Cascading Risk in Multi-Infeed HVDC System

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IEEE TRANSACTIONS ON POWER SYSTEMS 2024年第5期39卷 6426-6440页

作者： Wang, Xiaohui Song, Kaige Hao, Quanrui Gao, Feng Shandong Univ Sch Elect Engn Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China

The presence of multiple high voltage direct current (HVDC) systems in close proximity creates voltage-related cascading risks that are not adequately addressed by conventional grid-partitioning. This paper proposes an improved partitioning scheme to mitigate these new risks in addition to conventional objective of preventing parallel power flow from transferring adversely. Unlike classical partitioning approach, which relies solely on either optimization or clustering, our proposed bi-level architecture includes an additional HVDC clustering before optimization. However, this paper innovatively reveals that the distribution of correlation data to be used in clustering is non-Euclidean due to unusual equivalent reactance different from the normal operating condition, resulting from HVDC station's reactive power control. This non-Euclidean distribution makes heuristic clustering algorithms infeasible. To address this issue, an alternative solution is proposed to embed the correlation data into a dimension-reduced eigenspace spanned by selected eigenvectors, allowing clustering to be performed. The optimization implementing other objectives inherits the results of HVDC clustering as constraint, and the graphic betweenness weighted by power flows is presented to promote efficiency. Our proposed scheme is validated using cases studied in modified IEEE 118-bus benchmark system and practical regional grid, demonstrating its effectiveness in mitigating cascading risks in multi-infeed HVDC systems.

关键词： HVDC transmission Clustering algorithms Impedance Couplings Correlation Optimization partitioning algorithms Cascading failure clustering electromagnetic loop grid partitioning HVDC non-Euclidean parallel power flow reactive power control spectral embedding triangle inequality

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Fingerprint classification by directional image partitioning

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1999年第5期21卷 402-421页

作者： Cappelli, R Lumini, A Maio, D Maltoni, D Univ Bologna Corso Laurea Sci Informaz I-47023 Cesena Italy Univ Bologna DEIS CNR CSITE I-40136 Bologna Italy

In this work, we introduce a new approach to automatic fingerprint classification. The directional Image is partitioned into "homogeneous" connected regions according to the fingerprint topology, thus giving a synthetic representation which can be exploited as a basis for the classification. A set of dynamic masks, together with an optimization criterion, are used to guide the partitioning. The adaptation of the masks produces a numerical vector representing each fingerprint as a multidimensional point, which can be conceived as a continuous classification. Different search strategies are discussed to efficiently retrieve fingerprints both with continuous and exclusive classification. Experimental results have been given for the most commonly used fingerprint databases and the new method has been compared with other approaches known in the literature: As to fingerprint retrieval based on continuous classification, our method gives the best performance and exhibits a very high robustness.

关键词： fingerprint classification directional image partitioning algorithms continuous classification biometric systems

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