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Fast-Lipschitz Optimization With Wireless Sensor Networks Applications

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2011年第10期56卷 2319-2331页

作者： Fischione, Carlo KTH Royal Inst Technol Automat Control Lab ACCESS Linnaeus Ctr S-10044 Stockholm Sweden

Motivated by the need for fast computations in wireless sensor networks, the new F-Lipschitz optimization theory is introduced for a novel class of optimization problems. These problems are defined by simple qualifying properties specified in terms of increasing objective function and contractive constraints. It is shown that feasible F-Lipschitz problems have always a unique optimal solution that satisfies the constraints at equality. The solution is obtained quickly by asynchronous algorithms of certified convergence. F-Lipschitz optimization can be applied to both centralized and distributed optimization. Compared to traditional Lagrangian methods, which often converge linearly, the convergence time of centralized F-Lipschitz problems is at least superlinear. distributed F-Lipschitz algorithms converge fast, as opposed to traditional Lagrangian decomposition and parallelization methods, which generally converge slowly and at the price of many message passings. In both cases, the computational complexity is much lower than traditional Lagrangian methods. Examples of application of the new optimization method are given for distributed estimation and radio power control in wireless sensor networks. The drawback of the F-Lipschitz optimization is that it might be difficult to check the qualifying properties. For more general optimization problems, it is suggested that it is convenient to have conditions ensuring that the solution satisfies the constraints at equality.

关键词： Convex and non-convex optimization distributed optimization interference function theory multi-objective optimization parallel and distributed computation wireless sensor networks

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TOSSIM simulation of wireless sensor network serving as hardware platform for Hopfield neural net configured for max independent set

TOSSIM simulation of wireless sensor network serving as hard...

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Conference of the Complex Adaptive Systems on Responding to Continuous Global Change in Systems Needs

作者： Li, Jiakai Serpen, Gursel Univ Toledo Toledo OH 43606 USA

This paper, the third one in a three-paper sequence, presents the result of TOSSIM simulation of a Hopfield neural network as a static optimizer and configured to solve the maximum independent set (MIS) problem using a wireless sensor network as a fully parallel and distributed computing hardware platform. TinyOS with its default protocol stack along with nesC were used to develop the simulation model. Simulations were realized for mote counts of 10, 50, 100, and 182;messaging complexity, memory and simulation time costs were measured. Results indicated, as the most prominent finding, that the neural optimization algorithm was able to compute solutions to the MIS problem. The memory footprint of the TOSSIM process in Windows XP environment was about 20 MB for the range of sensor networks considered. The messaging complexity as measured by the total number of messages transmitted and the simulation time increased rather quickly indicating a need to optimize and tune certain aspects of the simulation environment if wireless sensor networks with higher mote counts need to be simulated. (C) 2011 Published by Elsevier B.V.

关键词： TOSSIM nesC TinyOS wireless sensor network Hopfield neural network static optimization parallel and distributed computation message complexity scalability

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TOSSIM simulation of wireless sensor network serving as hardware platform for Hopfield neural net configured for max independent set

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Procedia Computer Science 2011年 6卷 408-412页

作者： Jiakai Li Gursel Serpen Electrical Engineering and Computer Science University of Toledo Toledo Ohio 43606 USA

This paper, the third one in a three-paper sequence, presents the result of TOSSIM simulation of a Hopfield neural network as a static optimizer and configured to solve the maximum independent set (MIS) problem using a wireless sensor network as a fully parallel and distributed computing hardware platform. TinyOS with its default protocol stack along with nesC were used to develop the simulation model. Simulations were realized for mote counts of 10, 50, 100, and 182; messaging complexity, memory and simulation time costs were measured. Results indicated, as the most prominent finding, that the neural optimization algorithm was able to compute solutions to the MIS problem. The memory footprint of the TOSSIM process in Windows XP environment was about 20 MB for the range of sensor networks considered. The messaging complexity as measured by the total number of messages transmitted and the simulation time increased rather quickly indicating a need to optimize and tune certain aspects of the simulation environment if wireless sensor networks with higher mote counts need to be simulated.

关键词： TOSSIM nesC TinyOS wireless sensor network Hopfield neural network static optimization parallel and distributed computation message complexity scalability

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Minimum Energy Coding in CDMA Wireless Sensor Networks

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2009年第2期8卷 985-994页

作者： Flischione, C. Johansson, K. H. Sangiovanni-Vincentelli, A. Ares, B. Zurita Royal Inst Technol ACCESS Linnaeus Ctr Stockholm Sweden Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA

A theoretical framework is proposed for accurate comparison of minimum energy coding in Coded Division Multiple Access (CDMA) Wireless Sensor Networks (WSNs). Energy consumption and reliability are analyzed for two coding schemes: Minimum Energy coding (ME), and Modified Minimum Energy coding (MME). A detailed model of consumed energy is described as function of the coding, radio transmit power, the characteristics of the transceivers, and the dynamics of the wireless channel. Since CDMA is strongly limited by multi-access interference, the system model includes all the relevant characteristics of wireless propagation. A distributed and asynchronous algorithm, which minimizes the total energy consumption by controlling the radio power, is developed. Numerical results are presented to validate the theoretical analysis and show under which conditions MME outperforms ME with respect to energy consumption and bit error rate. It is concluded that MME is more energy efficient than ME only for short codewords.

关键词： Wireless sensor network (WSNs) minimum energy coding CDMA OOK power control outages parallel and distributed computation

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Compute pairwise Manhattan distance and Pearson correlation coefficient of data points with GPU

Compute pairwise Manhattan distance and Pearson correlation ...

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3rd International Workshop on e-Activity (IWEA2009)/10th ACIS International Conference on Software Engineering Artificial Intelligence, Networking and parallel/distributed Computing

作者： Chang, Dar-Jen Desoky, Ahmed H. Ouyang, Ming Rouchka, Eric C. Univ Louisville Dept Comp Sci & Comp Engn Louisville KY 40292 USA

ISBN: (纸本)9780769536422

Graphics processing units (GPUs) are powerful computational devices tailored towards the needs of the 3-D gaming industry for high-performance, real-time graphics engines. Nvidia Corporation released a new generation of GPUs designed for general-purpose computing in 2006, and it released a GPU programming language called CUDA in 2007. The DNA microarray technology is a high throughput tool for assaying mRNA abundance in cell samples. In. data analysis, scientists often apply hierarchical clustering of the genes, where a fundamental operation is to calculate all pairwise distances. If there are n genes, it takes O(n(2)) time. In this work, GPUs and the CUDA language are used to calculate pairwise distances. For Manhattan distance, GPU/CUDA achieves a 40 to 90 times speed-up compared to the central processing unit implementation;for Pearson correlation coefficient, the speed-up is 28 to 38 times.

关键词： parallel and distributed computation hierarchical clustering similarity and dissimilarity metrics

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Peer-to-peer Estimation over Wireless Sensor Networks via Lipschitz Optimization

Peer-to-peer Estimation over Wireless Sensor Networks via Li...

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8th International Symposium on Information Processing Sensor Networks

作者： Fischione, Carlo Speranzon, Alberto Johansson, Karl Henrik Sangiovanni-Vincentelli, Alberto Royal Inst Technol ACCESS Linnaeus Ctr S-10044 Stockholm Sweden United Technol Res Ctr E Hartford CT 06108 USA Univ Calif Berkeley Berkeley CA 94720 USA

ISBN: (纸本)9781424451081

Motivated by a peer-to-peer estimation algorithm in which adaptive weights are optimized to minimize the estimation error variance, we formulate and solve a novel non-convex Lipschitz optimization problem that guarantees global stability of a large class of peer-to-peer consensus-based algorithms for wireless sensor network. Because of packet. losses, the solution of this optimization problem cannot be achieved efficiently with either traditional centralized methods or distributed Lagrangian message passing. The prove that the optimal solution can be obtained by solving a set of nonlinear equations. A fast distributed algorithm, which requires only local computations, is presented for solving these equations. Analysis and computer simulations illustrate the algorithm and its application to various network topologies.

关键词： Lipschitz Optimization parallel and distributed computation Wireless Sensor Networks distributed Estimation

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A distributed minimum variance estimator for sensor networks

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2008年第4期26卷 609-621页

作者： Speranzon, A. Fischione, C. Johansson, K. H. Sangiovanni-Vincentelli, A. Unilever R&D Port Sunlight Wirral CH63 3JW Merseyside England Univ Calif Berkeley Berkeley CA 94720 USA Royal Inst Technol Sch Elect Engn S-10044 Stockholm Sweden

A distributed estimation algorithm for sensor networks is proposed. A noisy time-varying signal is jointly tracked by a network of sensor nodes, in which each node computes its estimate as a weighted sum of its own and its neighbors' measurements and estimates. The weights are adaptively updated to minimize the variance of the estimation error. Both estimation and the parameter optimization is distributed;no central coordination of the nodes is required. An upper bound of the error variance in each node is derived. This bound decreases with the number of neighboring nodes. The estimation properties of the algorithm are illustrated via computer simulations, which are intended to compare our estimator performance with distributed schemes that were proposed previously in the literature. The results of the paper allow to trading-off communication constraints, computing efforts and estimation quality for a class of distributed filtering problems.

关键词： distributed estimation sensor networks convex optimization parallel and distributed computation in-network processing cooperative communication

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Remote submission and parallel computation of fluorescence image reconstruction of breast cancer

Remote submission and parallel computation of fluorescence i...

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Conference on Smart Medical and Biomedical Sensor Technology

作者： Yang, Y Pargas, RP Clemson Univ Dept Comp Sci Clemson SC 29634 USA

ISBN: (纸本)0819451509

This paper describes a software system currently being developed at Clemson University in which a client provides recently obtained data to a remote server running a compute-intensive algorithm. To improve performance and speed up delivery of the results, the server distributes the data among multiple sub-server processors and assembles partial output from each processor into a coherent whole before sending the final results to the client. To demonstrate the capabilities of the system, a specific application is presented in this paper: a fluorescence image reconstruction system for breast cancer detection. An experimental instrument optically scans the patient's breast and generates some files of experimental data which are then sent to the server via the web. The data is processed by the numerical finite-element based algorithm running in parallel on a server and several sub-servers at Clemson. The algorithm is based on a set of coupled diffusion equations which are used to describe the propagation of excitation and fluorescent emission light in multiply scattering media (such as a breast). The algorithm reconstructs the fluorescence image of the breast in parallel. The resulting fluorescence lifetime and quantum yield mapping data can be sent back to the doctor for image display and analysis. This paper describes the numerical algorithm briefly and the software system which uses Java servlets to collect the data from the client and remote method invocation (Java RMI) to distribute the data to multiple processors. The output of the numerical algorithm, combined with the corresponding finite element mesh information, are input into a mathematical software package called Matlab which is used to produce the final images. Experiments are performed using indocyanine green (ICG) dye and tissue-like phantoms in both single- and multi-target configurations. Phantom experimental results of both lifetime and quantum yield are shown in this paper. Future work includes a refin

关键词： image reconstruction techniques mammography medical optics instrumentation tomography parallel and distributed computation web application

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Automatic methods for hiding latency in parallel and distributed computation

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SIAM JOURNAL ON COMPUTING 1999年第2期29卷 615-647页

作者： Andrews, M Leighton, T Metaxas, PT Zhang, L Bell Labs Murray Hill NJ 07974 USA MIT Dept Math Cambridge MA 02139 USA MIT Comp Sci Lab Cambridge MA 02139 USA Wellesley Coll Dept Comp Sci Wellesley MA 02181 USA

In this paper we describe methods for mitigating the degradation in performance caused by high latencies in parallel and distributed networks. For example, given any "dataflow" type of algorithm that runs in T steps on an n-node ring with unit link delays, we show how to run the algorithm in O(T) steps on any n-node bounded-degree connected network with average link delay O(1). This is a significant improvement over prior approaches to latency hiding, which require slowdowns proportional to the maximum link delay. In the case when the network has average link delay d(ave), our simulation runs in O(root d(ave)T) steps using n/root d(ave) processors, thereby preserving efficiency. We also show how to efficiently simulate an n x n array with unit link delays using slowdown (O) over tilde(d(ave)(2/3)) on a two-dimensional array with average link delay d(ave). Last, we present results for the case in which large local databases are involved in the computation.

关键词： hiding latency parallel and distributed computation linear and two-dimensional arrays complementary slackness

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The apprentice challenge

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ACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS 2002年第3期24卷 193-216页

作者： Moore, JS Porter, G Univ Texas Dept Comp Sci Austin TX 78712 USA

We describe a mechanically checked proof of a property of a small system of Java programs involving an unbounded number of threads and synchronization, via monitors. We adopt the output of the javac compiler as the semantics and verify the system at the bytecode level under an operational semantics for the JVM. We assume a sequentially consistent memory model and atomicity at the bytecode level. Our operational semantics is expressed in ACL2, a Lisp-based logic of recursive functions. Our proofs are checked with the ACL2 theorem prover. The proof involves reasoning about arithmetic;infinite loops;the creation and modification of instance objects in the heap, including threads;the inheritance of fields from superclasses;pointer chasing and smashing;the invocation of instance methods (and the concomitant dynamic method resolution);use of the start method on thread objects;the use of monitors to attain synchronization between threads;and consideration of all possible interleavings (at the bytecode level) over an unbounded number of threads. Readers familiar with monitor-based proofs of mutual exclusion will recognize our proof as fairly classical. The novelty here comes from (i) the complexity of the individual operations on the abstract machine;(ii) the dependencies between Java threads, heap objects, and synchronization;(iii) the bytecode-level interleaving;(iv) the unbounded number of threads;(v) the presence in the heap of incompletely initialized threads and other objects;and (vi) the proof engineering permitting automatic mechanical verification of code-level theorems. We discuss these issues. The problem posed here is also put forth as a benchmark against which to measure other approaches to formally proving properties of multithreaded Java programs.

关键词： languages verification Java Java Virtual Machine parallel and distributed computation mutual exclusion operational semantics theorem proving

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