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Optimal retransmission allocation for EDF-based networked real-time applications 15

Optimal retransmission allocation for EDF-based networked re...

引用

15th IEEE International Workshop on Factory Communication Systems (WFCS)

作者： Cena, Gianluca Scanzio, Stefano Seno, Lucia Valenzano, Adriano CNR IEIIT Natl Res Council Italy Cso Duca Abruzzi 24 I-10129 Turin Italy

ISBN: (纸本)9781728112688

Medium access control mechanisms where data transmissions are driven according to their deadlines have proven to offer interesting performance in networked real-time applications. In case of lossy networks, allocating a budget of the available bandwidth, through worst-case schedulability analysis, to retransmission of failed data, permits to combine timeliness and reliability, as typically required by these applications. This paper tackles the problem of allocating retransmissions to a set of time-critical data so as to maximize some meaningful reward function while meeting the imposed deadlines. Few methods are proposed and evaluated, which are based on theoretical analysis, integer linear programming, and solution space exploration.

关键词： Delays Optimization Load management 5G mobile communication Resource management Software linear programming"

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Learning Discriminative Representations for Big Data Clustering using Similarity-based Dimensionality Reduction 13

Learning Discriminative Representations for Big Data Cluster...

引用

13th IEEE Image, Video, and Multidimensional Signal Processing Workshop (IVMSP)

作者： Passalis, Nikolaos Tefas, Anastasios Aristotle Univ Thessaloniki Dept Informat Thessaloniki Greece

ISBN: (纸本)9781538609514

Discriminative Clustering techniques simultaneously perform clustering and learn a representation that encourages the separability of the clusters. However, methods with high discriminative power tend to decrease clustering accuracy, since the cluster assignments are usually noisy. In this paper, a similarity-based dimensionality reduction method, that allows for learning regularized clustering-oriented representations and is able to efficiently scale to large datasets, is proposed. We avoid the pitfalls of highly discriminative methods, such as the linear Discriminant Analysis (LDA), by maintaining a small similarity between the inter-cluster samples and a small dissimilarity between the intra-cluster samples instead of collapsing the intra-cluster samples and pushing the clusters as far apart as possible. Three datasets are used to demonstrate the ability of the proposed method to learn robust representations that improve the quality of the obtained clustering solutions over other clustering techniques.

关键词： Task analysis Optimization Clustering algorithms Dimensionality reduction Robustness Clustering methods linear programming"

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Dancing PRM*: Simultaneous Planning of Sampling and Optimization with Configuration Free Space Approximation

Dancing PRM*: Simultaneous Planning of Sampling and Optimiza...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Kim, Donghyuk Kwon, Youngsun Yoon, Sung-Eui Korea Adv Inst Sci & Technol Sch Comp Daejeon 34141 South Korea

ISBN: (纸本)9781538630815

A recent trend in optimal motion planning has broadened the research area toward the hybridization of sampling, optimization and grid-based approaches. We can expect that synergy from such integrations leads to overall performance improvement, but seamless integration and generalization is still an open problem. In this paper, we suggest a hybrid motion planning algorithm utilizing a sampling-based and optimization-based planner while simultaneously approximating a configuration free space. Unlike conventional optimization-based approaches, the proposed algorithm does not depend on a priori information or resolution-complete factors, e.g., a distance field. Ours instead learns spatial information on the fly by exploiting empirical information during the execution, and decentralizes the information over the constructed graph for efficient access. With the help of the learned information, our optimization-based local planner exploits the local area to identify the connectivity of configuration free space without depending on the precomputed domain knowledge. To show the novelty of proposed algorithm, we evaluate it against other asymptotic optimal planners in both synthetic and complex benchmarks with varying degrees of freedom. We also discuss the performance improvement, properties and limitations we have observed.

关键词： Planning Approximation algorithms Trajectory Optimization Robots Probabilistic logic linear programming"

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Distributed Multi-Robot Cooperation for Information Gathering under Communication Constraints

Distributed Multi-Robot Cooperation for Information Gatherin...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Viseras, Alberto Xu, Zhe Merino, Luis German Aerosp Ctr DLR Inst Commun & Nav D-82234 Oberpfaffenhofen Wessling Germany Australian Ctr Field Robot Sydney BC Australia Univ Pablo Olavide Crta Utrera Km 1 Seville 41013 Spain

ISBN: (纸本)9781538630815

Many recent works have proposed algorithms for information gathering that benefit from multi-robot cooperation. However, most algorithms either employ discretization of the state and action spaces, which makes them computationally intractable for robotic systems with complex dynamics;or cannot deal with inter-robot restrictions like e.g. communication constraints. This paper presents an approach for multi-robot information gathering that tackles the two aforementioned issues. To this end we propose an algorithm that combines in an innovative manner Gaussian processes (GPs) to model the physical process of interest, RRT planners to plan paths in a continuous domain, and a distributed decision-making algorithm to achieve multi-robot cooperation. Specifically, we employ the Max-sum algorithm for distributed multi-robot cooperation by defining an information-theoretic utility function together with a path clustering approach. This function maximizes information gathering, subject to inter-robot communication constraints. We validate the proposed approach in simulations, and in a field experiment where three quadcopters explore a simulated wind field. Results demonstrate the effectiveness of the approach.

关键词： Clustering algorithms Robot kinematics Robot sensing systems Heuristic algorithms linear programming"

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On the Equivalence of Two Information Bottleneck-Based Routines Devised for Joint Source-Channel Coding 25

On the Equivalence of Two Information Bottleneck-Based Routi...

引用

25th International Conference on Telecommunications (ICT)

作者： Hassanpour, Shayan Wuebben, Dirk Dekorsy, Armin Univ Bremen Dept Commun Engn D-28359 Bremen Germany

ISBN: (纸本)9781538623213

Consider an extended version of noisy source coding in which the compressed data must be transmitted over an imperfect (forward) channel before being further processed. An interesting criterion for designing the quantizer in such cases is to maximize the end-to-end transmission rate. Since finding the globally optimal solution via the naive brute-force search is practically infeasible, a number of routines have been proposed aiming at providing complexity-wise tractable procedures at the expense of converging to local optima. In this paper, we study the relation between two particular devised heuristics appeared in totally different applications and prove their equivalence through an in-depth analytical investigation of their counterpart algorithmic steps. We further substantiate our presented line of argumentation by means of computer-generated simulations.

关键词： Noise measurement Optimization Encoding Distortion measurement Distortion Convex functions linear programming"

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The Design of Ortho-Planar Spring for a Normally-Closed Gate Valve 4

The Design of Ortho-Planar Spring for a Normally-Closed Gate...

引用

4th IEEE/IFToMM International Conference on Reconfigurable Mechanisms and Robots (ReMAR)

作者： Graipaspong, Ruetai Chanthasopeephan, Teeranoot King Mongkuts Univ Technol Thonburi Dept Mech Engn Bangkok 10140 Thailand

ISBN: (纸本)9781538663806

This paper presents the design of an Ortho-planar spring for a normally-closed gate valve using topology optimization. The Ortho-planar valve was designed through developing a MAT LAB code to perform a three-dimensional topology optimization. The optimization process was based on dual method, where the objective function was to minimize mass and the constraint was a defined set of displacement. The result of topology optimization process was a layout design of an Ortho-planar spring, which was later developed into a prototype. The behavior of the Ortho-planar spring was analyzed based on the collected force-displacement data. The force-displacement relationship presented the nonlinear characteristic of the Ortho-planar spring. The stiffness of spring increased as deflection increased. The prototype of the Ortho-planar valve was undergone a performance test to check the valve function whether it could prevent leak as a normally closed gate valve. The experimental results showed that the designed Ortho-planar spring could be applied as a normally closed gate valve at the pressure of 2 bars and above. Also, its surface must be thoroughly polished to best prevent leak.

关键词： Springs Valves Optimization Topology Force Prototypes linear programming"

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Enforcing Eigenvector Smoothness for a Compact DFT-based Polynomial Eigenvalue Decomposition 10

Enforcing Eigenvector Smoothness for a Compact DFT-based Pol...

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10th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)

作者： Coutts, Fraser K. Thompson, Keith Pestana, Jennifer Proudler, Ian K. Weiss, Stephan Univ Strathclyde Dept Elect & Elect Engn Glasgow Lanark Scotland Univ Strathclyde Dept Math & Stat Glasgow Lanark Scotland

ISBN: (纸本)9781538647523

A variety of algorithms have been developed to compute an approximate polynomial matrix eigenvalue decomposition (PEVD). As an extension of the ordinary EVD to polynomial matrices, the PEVD will generate paraunitary matrices that diagonalise a parahermitian matrix. While iterative PEVD algorithms that compute a decomposition in the time domain have received a great deal of focus and algorithmic improvements in recent years, there has been less research in the field of frequency-based PEVD algorithms. Such algorithms have shown promise for the decomposition of problems of finite order, but the state-of-the-art requires a priori knowledge of the length of the polynomial matrices required in the decomposition. This paper presents a novel frequency-based PEVD algorithm which can compute an accurate decomposition without requiring this information. Also presented is a new metric for measuring a function's smoothness on the unit circle, which is utilised within the algorithm to maximise eigenvector smoothness for a compact decomposition, such that the polynomial eigenvectors have low order. We demonstrate through the use of simulations that the algorithm can achieve superior levels of decomposition accuracy to a state-of-the-art frequency-based method.

关键词： Matrix decomposition Eigenvalues and eigenfunctions Signal processing algorithms Covariance matrices Approximation algorithms Measurement linear programming"

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Convergence Rate of Distributed Subgradient Methods under Communication Delays

Convergence Rate of Distributed Subgradient Methods under Co...

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American Control Conference

作者： Doan, Thinh T. Beck, Carolyn L. Srikant, R. Univ Illinois Coordinated Sci Lab Urbana IL 61801 USA

ISBN: (纸本)9781538654286

Motivated by broad applications in computer science and engineering, we study distributed algorithms for optimization problems over a network of nodes, where the goal is to optimize a global objective composed of a sum of local functions. In this paper, we consider a popular distributed gradient-based consensus algorithm, which only requires local computation and communication. A significant problem in this area is to analyze the convergence rate of such algorithms in the presence of communication delays that are inevitable in distributed systems. Our main contribution is to obtain an upper bound on the rate of convergence of the algorithm as a function of the network size, topology, and the inter-node communication delays.

关键词： Delays Convergence Gradient methods Distributed algorithms Program processors linear programming"

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Empirical Investigation of Non-Convexities in Optimal Power Flow Problems

Empirical Investigation of Non-Convexities in Optimal Power ...

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American Control Conference

作者： Narimani, Mohammad Rasoul Molzahn, Daniel K. Wu, Dan Crow, Mariesa L. Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO 65401 USA Argonne Natl Lab Energy Syst Div Argonne IL 60439 USA MIT Dept Mech Engn Cambridge MA 02139 USA

ISBN: (纸本)9781538654286

Optimal power now (OPE) is a central problem in the operation of electric power systems. An OFF problem optimizes a specified objective function subject to constraints imposed by both the non-linear power now equations and engineering limits. These constraints can yield non-convex feasible spaces that result in significant computational challenges. Despite these non-convexities, local solution algorithms actually find the global optima of some practical OPF problems. This suggests that Off problems have a range of difficulty: some problems appear to have convex or "nearly convex" feasible spaces in terms of the voltage magnitudes and power injections. while other problems can exhibit significant non-convexities. Understanding this range of problem difficulty is helpful for creating new test cases for algorithmic benchmarking purposes. Leveraging recently developed computational tools for exploring Off feasible spaces, this paper first describes an empirical study that aims to characterize non-convexities for small OFF problems. This paper then proposes and analyzes several medium-size test cases that challenge a variety of solution algorithms.

关键词： Tools Reactive power Generators programming Reliability linear programming"

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Joint Downlink/Uplink Power Optimization for Broadband Full-duplex Cellular Systems 25

Joint Downlink/Uplink Power Optimization for Broadband Full-...

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25th International Conference on Telecommunications (ICT)

作者： Wu, Peiran Xia, Minghua Tang, Chengpei Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538623213

In this paper, we consider a broadband cellular system with a full-duplex base station and half-duplex mobile stations, employing orthogonal frequency-division multiple access (OFDMA) in the downlink and single-carrier frequency-division multiple access (SC-FDMA) in the uplink. Our goal is to maximize the weighted network sum rate by jointly optimizing the downlink/uplink transmit power allocation, under a joint power constraint and per-user power constraints, respectively. Due to the non-convexity of the resulting problem, we propose a low-complexity suboptimal solution based on alternating optimization (AO), where in each alternating iteration, a difference of concave optimization problem is solved in an efficient manner. The final solution obtained is shown to be a stationary point solution to the original non-convex problem and the performance gain offered by the proposed joint power allocation design is verified by extensive simulations.

关键词： Optimization Resource management Decision feedback equalizers Broadband communication Interference OFDM linear programming"

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