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Analysis of Sparse Quasi-Newton Updates with Positive Definite Matrix Completion

Journal of the Operations Research Society of China 2014年第1期2卷 39-56页

作者： Yu-Hong Dai Nobuo Yamashita State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and Systems ScienceChinese Academy of SciencesP.O.Box 2719Beijing 100080People’s Republic of China Department of Applied Mathematics and Physics Graduate School of InformaticsKyoto UniversityKyoto 606-8501Japan

Based on the idea of maximum determinant positive definite matrix completion,Yamashita(Math Prog 115(1):1–30,2008)proposed a new sparse quasi-Newton update,called MCQN,for unconstrained optimization problems with sparse Hessian *** exchange of the relaxation of the secant equation,the MCQN update avoids solving difficult subproblems and overcomes the ill-conditioning of approximate Hessian ***,local and superlinear convergence results were only established for the MCQN update with the DFP *** this paper,we extend the convergence result to the MCQN update with the whole Broyden’s convex *** results are also reported,which suggest some efficient ways of choosing the parameter in the MCQN update the Broyden’s family.

关键词： Quasi-Newton method Large-scale problems Sparsity Positive definite matrix completion Superlinear convergence

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Online adaptation of dialog strategies based on probabilistic planning

Online adaptation of dialog strategies based on probabilisti...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Steffen Müller Sina Sprenger Horst-Michael Gross School of Computing Informatics and Decision System Engineering Arizona State University Tempe Arizona

In this paper, a dialog modeling approach for long-term interaction between a service robot and a single user is presented, which enables a user-adaptive interaction behavior of the robot. Central element of the dialog system is a probabilistic model of the user's reactions to the robot's behavior, which is learned online and used for a probabilistic planning process based on message passing in a dynamic factor graph. The suggested approach has been applied to implement a complex application on a mobile service robot, which has been tested in a 10 day evaluation study with 16 users in order to get a feedback on usability of the interaction design, adaptation skills, and feasibility of a rapid application development. Results and findings of that study are presented here briefly.

关键词： Planning Probabilistic logic Adaptation models Robot sensing systems decision trees Service robots

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Region based fault-tolerant distributed file storage system design under budget constraint

Region based fault-tolerant distributed file storage system ...

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International Workshop on Reliable Networks Design and Modeling (RNDM)

作者： Anisha Mazumder Arun Das Chenyang Zhou Arunabha Sen School of Computing Informatics and Decision System Engineering Arizona State University Tempe Arizona

Two independent lines of research, (i) erasure code based file storage system design, and (ii) fault-tolerant network design for spatially correlated (or region-based) failures, have received considerable attention in the networking research community in recent times. A recently proposed (N,K)-coding based distributed file storage scheme ensures complete reconstruction of a file after network fragmentation due to any single region-based fault. For every region of the network, it stores K distinct file segments in one of the largest connected component that results from the fragmentation of the network due to the failure of a region. This distribution scheme provides an all-region fault-tolerant storage system, in the sense that no matter which region of the network fails, a largest connected component of the fragmented network will still have enough distinct file segments with which to reconstruct the file. However, the storage requirement and the associated cost for such an all-region-fault-tolerant storage system may be quite high. As such, with a limited budget it may not be possible to realize such an all-region fault-tolerant storage system. We consider a budget constrained distributed file system design problem and provide solutions that maximizes the number of regions that can be made fault-tolerant, within the specified budget. We show that the problem is NP-complete, and provide an approximation algorithm for the problem. The performance of the approximation algorithm is evaluated through simulation on two real networks. The simulation results demonstrate that the worst case experimental performance is significantly better than the worst case theoretical bound. Moreover, the approximation algorithm almost always produce near optimal solution in a fraction of time needed to find the optimal solution.

关键词： Approximation algorithms Fault tolerance Fault tolerant systems Approximation methods Encoding Algorithm design and analysis Vectors

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New Logistical Issues in Using Electric Vehicle Fleets with Battery Exchange Infrastructure

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Procedia - Social and Behavioral Sciences 2014年 108卷 3-14页

作者： Pitu Mirchandani Jonathan Adler Oli B.G. Madsen School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe Arizona 85281 United States Department of Transport Technical University of Denmark 2800 Kgs Lyngby Denmark

There is much reason to believe that fleets of service vehicles of many organizations will transform their vehicles that utilize alternative fuels that are more sustainable. The electric vehicle (EV) is a good candidate for this transformation, especially which “refuels” by exchanging its spent batteries with charged ones. This paper discusses some new logistical issues that must be addressed by such EV fleets, principally the issues related to the limited driving range of each EV's set of charged batteries and the possible detouring for battery exchanges. In particular, the paper addresses (1) the routing and scheduling of the fleet, (2) the locations of battery-exchange stations, and (3) the sizing of each facility. An overview of the literature on the topic is provided and some initial results are presented.

关键词： Electric vehicles constrained shortest routes vehicle routing facility location facility sizing

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1

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BMC Neurosci 2017年第SUPPL 1期18卷 58-58页

作者： Sue Denham Panayiota Poirazi Erik De Schutter Karl Friston Ho Ka Chan Thomas Nowotny Dongqi Han Sungho Hong Sophie Rosay Tanja Wernle Alessandro Treves Sarah Goethals Romain Brette Tomas Van Pottelbergh Rodolphe Sepulchre Alex D. Bird Hermann Cuntz Pedro J. Gonçalves Jan-Matthis Lueckmann Giacomo Bassetto Marcel Nonnenmacher Jakob H. Macke Audrey J. Sederberg Jason N. MacLean Stephanie E. Palmer Ulisse Ferrari Christophe Gardella Olivier Marre Thierry Mora Emina Ibrahimovic Martin Müller Jean-Pascal Pfister Tushar Chauhan Timothée Masquelier Alexandre Montlibert Benoit R. Cottereau Moritz Helias Jannis Schuecker David Dahmen Sven Goedeke Alexandre Hyafil Ainhoa Hermoso-Mendizabal Pavel E. Rueda-Orozco Santiago Jaramillo David Robbe Jaime de la Rocha Marie Rooy Fani Koukouli David DiGregorio Uwe Maskos Boris Gutkin Andrey Yu Verisokin Darya V. Verveyko Dmitry E. Postnov Willy Wong Omid Talakoub Robert Chen Milos Popovic Dmitriy Lisitsyn Eric Drebitz Iris Grothe Sunita Mandon Andreas Kreiter Udo Ernst Peter A. Robinson Xuelong Zhao Kevin M. Aquino John D. Griffiths Grishma Mehta-Pandejee Natasha Gabay James MacLaurin Somwrita Sarkar Tim Kunze Jens Haueisen Thomas R. Knösche Subutai Ahmad Yuwei Cui Marcus Lewis Jeff Hawkins Simona Olmi Spase Petkoski Fabrice Bartolomei Maxime Guye Viktor Jirsa Hazem Toutounji Daniel Durstewitz Matteo Cantarelli Adrian Quintana Boris Marin Matt Earnshaw Padraig Gleeson Robert Court Robert McDougal R. Angus Silver Salvador Dura-Bernal Stephen Larson William W. Lytton Giovanni Idili Lorenzo Posani Simona Cocco Karel Ježek Rémi Monasson School of Psychology Faculty of Health & Human Sciences Plymouth University Plymouth Devon PL4 8AA UK Institute of Molecular Biology and Biotechnology (IMBB) Foundation for Research and Technology-Hellas (FORTH) Heraklion Crete Greece Okinawa Institute of Science and Technology Graduate University Okinawa Japan Wellcome Trust Centre for Neuroimaging Institute of Neurology UCL London WC1N 3BG UK School of Engineering and Informatics University of Sussex Brighton BN1 9QJ UK Graduate School Okinawa Institute of Science and Technology Okinawa 904-0495 Japan Computational Neuroscience Unit Okinawa Institute of Science and Technology Okinawa 904-0495 Japan Cognitive Neuroscience Area Scuola Internazionale Superiore di Studi Avanzati Trieste 34136 Italy Kavli Institute for Systems Neuroscience NTNU Trondheim 7030 Norway Institut de la Vision Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Paris 75012 France Department of Engineering University of Cambridge Cambridge Cambridgeshire CB2 1PZ UK Ernst Strüngmann Institute for Neuroscience Max Planck Society Frankfurt Germany Frankfurt Institute for Advanced Studies Frankfurt Germany Neural Systems Analysis Research Center Caesar An Associate of the Max Planck Society Bonn Germany Max Planck Institute for Biological Cybernetics Tübingen Germany Bernstein Center for Computational Neuroscience Tübingen Germany Present Address: Biomedical Engineering Department Georgia Institute of Technology Atlanta GA 30306 USA Department of Neurobiology University of Chicago Chicago IL 60637 USA Department of Organismal Biology and Anatomy University of Chicago Chicago IL 60637 USA Committee on Computational Neuroscience University of Chicago Chicago IL 60637 USA Institut de la Vision Sorbonne Universités INSERM Paris France Laboratoire de Physique Statistique Ecole Normale Supérieure Paris France Institute of Molecular Life Sciences University of Zürich 8057 Zürich Switzerland Institute of Neuroinformatics Univer

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Understanding Requirements Driven Architecture Evolution in Social Networking SaaS: An Industrial Case Study

Understanding Requirements Driven Architecture Evolution in ...

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2014 IEEE 8th International Symposium on Service Oriented System engineering

作者： Dong Sun Rong Peng Wei-Tek Tsai State Key Lab of Software Engineering Wuhan University Wuhan China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe USA

Recently many companies have featured their applications as SaaS (Software as a Service) applications where applications will be treated as services and provided online for thousands and millions of users. Social Networking SaaS (SNS) is one of the most popular kinds of SaaS. The key to the success of a SNS heavily relies on the scale of users. With the explosive growth of users, SNS's architecture should be able to change according to the demand. To better understand what kind of requirements influences SNS's architecture most, and learn the relationships between these requirements and the evolution progress of architecture, this paper carried out a dedicated analysis on a popular SNS application, Instagram. The lessons learned show that: 1) Demands on scalability and real-time are the main driven forces to architecture redesign, 2) Data coming from extensive monitoring is one of the most important sources of evolutionary requirements/issues, which drives different types of architecture evolution, 3) Reusing existing components is the key factor to evolve architecture rapidly and costly. The lessons learned can help engineers and researchers understand the co-evolution progress between requirements and architectures, and how to devise appropriate architectures to meet the possible evolution challenges for SNS.

关键词： Computer architecture Monitoring Servers Androids Humanoid robots Databases Scalability

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Identification of K most vulnerable nodes in multi-layered network using a new model of interdependency

Identification of K most vulnerable nodes in multi-layered n...

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IEEE Conference on Computer Communications Workshops, INFOCOM Wksps

作者： Arunabha Sen Anisha Mazumder Joydeep Banerjee Arun Das Randy Compton Computer Science and Engineering Program School of Computing Informatics and Decision System Engineering Arizona State University Tempe Arizona

The critical infrastructures of a nation including the power grid and the communication network are highly interdependent. Recognizing the need for a deeper understanding of the interdependency in a multi-layered network, significant efforts have been made by the research community in the last few years to achieve this goal. Accordingly a number of models have been proposed and analyzed. Unfortunately, most of the models are over simplified and, as such, they fail to capture the complex interdependency that exists between entities of the power grid and the communication networks involving a combination of conjunctive and disjunctive relations. To overcome the limitations of existing models, we propose a new model that is able to capture such complex interdependency relations. Utilizing this model, we provide techniques to identify the K most “vulnerable” nodes of an interdependent network. We show that the problem can be solved in polynomial time in some special cases, whereas for some others, the problem is NP-complete. We establish that this problem is equivalent to computation of a fixed point of a multilayered network system and we provide a technique for its computation utilizing Integer Linear Programming. Finally, we evaluate the efficacy of our technique using real data collected from the power grid and the communication network that span the Maricopa County of Arizona.

关键词： Equations Communication networks Mathematical model Power grids Power system faults Power system protection Nonhomogeneous media

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Root Cause Analysis of Failures in Interdependent Power-Communication Networks

Root Cause Analysis of Failures in Interdependent Power-Comm...

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MILCOM, Military Communications Conference

作者： Arun Das Joydeep Banerjee Arunabha Sen Computer Science and Engineering Program School of Computing Informatics and Decision System Engineering Arizona State University Tempe Arizona

ISBN: (纸本)9781479967711

Studies on communication network robustness, though extensive, have primarily focused on standalone networks. However, real world communication networks do not operate in isolation, but instead are part of complex interdependent ecosystems that function together as a comprehensive symbiotic unit. For instance, communication networks of today are highly dependent on the power infrastructure and hence, any efforts to improve the robustness of communication networks must necessarily take into account the vulnerabilities of the power infrastructure and their shared interdependencies. For example, event-induced failures (failures caused by natural disasters or terrorist attacks), on any of these two infrastructures can trigger further failures (triggered failures) into the system through a cascading process due to the interdependencies between the networks. In such an interdependent system where an event induced failure can cascade and result in a much larger combined (event-induced plus triggered) failure, it may be imperative to identify the original event-induced failure for the purpose of post fault diagnostics, or for pre-cascade network strengthening. This ascertainment of event-induced original failure, or the Root Cause of Failure, from combined failures in interdependent Power-Communication networks is the main focus of this paper. We model interdependencies between the two infrastructures using the recently proposed Implicative Interdependency Model. We introduce the Root Cause of Failure problem, and prove it to be NP-Complete. We also provide optimal solutions using ILP, and provide an O(ln(n)) approximation algorithm. Finally, we validate our analytical results through experiments in the power communication network of Maricopa County, Arizona.

关键词： Communication networks Silicon Approximation algorithms Computational modeling Power system faults Power system protection Approximation methods

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Statistical analysis of stochastic multi-robot boundary coverage

Statistical analysis of stochastic multi-robot boundary cove...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Ganesh P. Kumar Spring Berman School of Computing Informatics Decision Systems Engineering Arizona State University Tempe AZ USA School for Engineering of Matter Transport and Energy Arizona State University Tempe AZ USA

We present a novel analytical approach to computing the population and geometric parameters of a multi-robot system that will provably produce specified boundary coverage statistics. We consider scenarios in which robots with no global position information, communication, or prior environmental data have arrived at uniformly random locations along a simple closed or open boundary. This type of scenario can arise in a variety of multi-robot tasks, including surveillance, collective transport, disaster response, and therapeutic and imaging applications in nanomedicine. We derive the probability that a given point robot configuration is saturated, meaning that all pairs of adjacent robots are no farther apart than a specified distance. This derivation relies on a geometric interpretation of the saturation probability and an application of the Inclusion-Exclusion Principle, and it is easily extended to finite-sized robots. In the process, we obtain formulas for (a) an integral that is in general computationally expensive to compute directly, and (b) the volume of the intersection of a regular simplex with a hypercube. In addition, we use results from order statistics to compute the probability distributions of the robot positions along the boundary and the distances between adjacent robots. We validate our derivations of these probability distributions and the saturation probability using Monte Carlo simulations of scenarios with both point robots and finite-sized robots.

关键词： Equations Robot sensing systems Robot kinematics Tin Joints

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On the impact of coding parameters on storage requirement of region-based fault tolerant distributed file system design

On the impact of coding parameters on storage requirement of...

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International Conference on computing, Networking and Communications (ICNC)

作者： Sujogya Banerjee Arun Das Anisha Mazumder Zahra Derakhshandeh Arunabha Sen Computer Science and Engineering Program School of Computing Informatics and Decision System Engineering Arizona State University Tempe Arizona

Advances in technology have resulted in Internet-scale deployment of storage systems such as peer-to-peer storage and cloud storage, where data is distributed over multiple storage nodes in a networked environment. In these environments the storage nodes are often commodity machines and are susceptible to failure. The notion of fault domain, introduced by Microsoft Azure, captures the fault-tolerance aspects of a data center. A fault domain is defined as a set of servers all of which become inaccessible when a single fault (such as the failure of a switch or a router) occurs in the data center. As such a fault domain can be viewed as a spatially correlated or region based failure. In order to enhance reliability through redundancy, maximum distance separable (MDS) codes such as Reed-Solomon codes and (N, K) codings are utilized. In this paper we present analytical results demonstrating that the choice of the coding parameters N and K may have significant impact on storage that will be necessary to achieve reliability. We present a polynomial time algorithm for optimal storage allocation in a mesh network and we conduct extensive experimentation to evaluate the impact of the coding parameters N and K on the storage requirement to provide all region fault tolerance with varying size of the mesh and the fault region.

关键词： Color Image color analysis Encoding Silicon Peer-to-peer computing Fault tolerant systems Fault tolerance

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