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distributed implementation of the disabling operator in LOTOS

INFORMATION AND SOFTWARE TECHNOLOGY 1999年第3期41卷 123-130页

作者： Naik, K Cheng, Z Wei, DSL Univ Aizu Dept Comp Software Fukushima 9658580 Japan Fordham Univ Dept Comp & Informat Sci Bronx NY 10458 USA

LOTOS is a process algebra-based formal description technique (FDT). It has been standardized by the International Standards Organization (ISO) for the specification of communication and distributed software systems. The disabling operator of LOTOS is a unique feature not found in other FDTs. Though Lotos is a powerful specification language, it is not used in the industries. This is because it is very difficult to implement its various operators, In this paper, we propose a scheme for distributed implementation of the disabling operator. Our main contribution lies in transforming the operational semantics of the disabling operator to a distributed implementation. The distributed implementation is specified as a hierarchy of communicating finite-state machines which are easy to implement. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： formal methods LOTOS disabling operator operational semantics distributed implementation

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distributed implementation of Kalman object tracker with discrete asynchronous measurements

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IET RADAR SONAR AND NAVIGATION 2018年第9期12卷 979-987页

作者： Rahmanian, Shahabuddin Bateni, Mohammad Hossein Najafi, Majdeddin Isfahan Univ Technol Res Inst Avion Esfahan *** Iran Isfahan Univ Technol Dept Elect & Comp Engn Esfahan *** Iran

Typical tracking systems employ tracking filters in order to consecutively estimate the kinematics of a moving object, based on some limited observations of its position and/or velocity which are contaminated by different types of uncertainties. The Kalman filter is the optimal filter for some simple cases. However, in practical scenarios, designing more complicated filters or making modifications to the Kalman filter may be necessary, in order to provide the tracking process with adequate reliability and accuracy. An appropriate design should consider the discipline under which measurements are gathered and the type of disturbances to which the measurement process is exposed. This study investigates the case of quantised, unreliable, asynchronous velocity and position measurements, and proposes an effective design which realises a distributed Kalman filter with two- or three-dimensional state vectors. It is shown via simulations that the proposed design not only smooths the output and combats the effects of quantisation but also keeps on tracking when the measurements are lost for a quite long duration of time.

关键词： Kalman filters position measurement tracking filters velocity measurement object tracking distributed implementation Kalman object tracker discrete asynchronous measurements tracking systems tracking filters optimal filter complicated filters measurement process asynchronous velocity position measurements distributed Kalman filter moving object kinematics asynchronous velocity measurements

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distributed implementation of Heat Kernel Smoothing for Graph Signal Denoising 65

Distributed Implementation of Heat Kernel Smoothing for Grap...

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IEEE 65th International Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Tseng, Chien-Cheng Lee, Su-Ling Natl Kaohsiung Univ Sci & Technol Dept Comp & Commun Engn Kaohsiung Taiwan Chang Jung Christian Univ Dept Comp Sci & Informat Engn Tainan Taiwan

ISBN: (数字)9781665402798

ISBN: (纸本)9781665402798

In this paper, a graph signal denoising method based on heat kernel smoothing (HKS) and its distributed implementation structures are investigated. First, the graph signal denoising problem and HKS method are briefly described. Because HKS method needs to perform eigen-decomposition of graph Laplacian matrix for computing matrix exponential, it is only suitable for centralized implementation. To obtain a distributed or decentralized implementation of HKS method, three implementation methods are then presented in this study including product expansion method, Taylor series expansion method and numerical differentiation approximation method. Finally, irregular data collected from sensor network and social network are used to demonstrate the effectiveness of the graph signal denoising methods based on heat kernel smoothing.

关键词： heat kernel smoothing graph signal denoising distributed implementation matrix exponential

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Joint Power and Admission Control for Ad-Hoc and Cognitive Underlay Networks: Convex Approximation and distributed implementation

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2011年第12期10卷 4110-4121页

作者： Mitliagkas, Ioannis Sidiropoulos, Nicholas D. Swami, Ananthram Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA Tech Univ Crete Dept Elect & Comp Engn Khania 73100 Greece USA Res Lab Adelphi MD 20783 USA

Power control is important in interference-limited cellular, ad-hoc, and cognitive underlay networks, when the objective is to ensure a certain quality of service to each connection. Power control has been extensively studied in this context, including distributed algorithms that are particularly appealing in ad-hoc and cognitive settings. A long-standing issue is that the power control problem may be infeasible, thus requiring appropriate admission control. The power and admission control parts of the problem are tightly coupled, but the joint optimization problem is NP-hard. We begin with a convenient reformulation which enables a disciplined convex approximation approach. This leads to a centralized approximate solution that is numerically shown to outperform the prior art, and even yield close to optimal results in certain cases - at affordable complexity. The issue of imperfect channel state information is also considered. A distributed implementation is then developed, which alternates between distributed approximation and distributed deflation reaching consensus on a user to drop, when needed. Both phases require only local communication and computation, yielding a relatively lightweight distributed algorithm with the same performance as its centralized counterpart.

关键词： Power control admission control convex optimization distributed implementation dual decomposition subgradient ad-hoc peer-to-peer cognitive radio networks

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Safe Ambients: Abstract machine and distributed implementation

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SCIENCE OF COMPUTER PROGRAMMING 2006年第3期59卷 209-249页

作者： Giannini, P Sangiorgi, D Valente, A Univ Bologna Dipartimento Sci Informaz I-40126 Bologna Italy Univ Piemonte Orientale Dipartimento Informat I-15100 Alessandria Italy Aalborg Univ Dept Software & Media Technol DK-6700 Esbjerg Denmark

The abstract machine PAN for a distributed implementation of an ambient calculus is presented. PAN is different from, and simpler than, previous implementations of ambient-like calculi, mainly because: the underlying calculus is typed Safe Ambients (SA) rather than the untyped Ambient calculus and therefore does not present certain forms of interferences among processes (the grave interferences). In PAN the logical structure of an ambient system and its physical distribution are separated. A translation from SA terms to PAN terms is defined. The correctness of such a translation, which asserts that an SA term and its translation exhibit the same observational behavior, is proved. Moreover, a description of a distributed implementation of the abstract machine in Java is given. (c) 2005 Published by Elsevier B.V.

关键词： Safe Ambients abstract machine proof of correctness distributed implementation

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Collaborative-Relay Beamforming With Perfect CSI: Optimum and distributed implementation

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IEEE SIGNAL PROCESSING LETTERS 2009年第4期16卷 257-U44页

作者： Zheng, Gan Wong, Kai-Kit Paulraj, Arogyaswami Ottersten, Bjorn Univ Coll London Martlesham IP5 3RE England Stanford Univ Informat Syst Lab Stanford CA 94305 USA Royal Inst Technol KTH Sch Elect Engn Stockholm Sweden

This letter studies the collaborative use of amplify-and-forward (AF) relays to form a virtual multiple-input single-output (MISO) beamforming system with the aid of perfect channel state information (CSI) in a flat-fading channel. In particular, we optimize the relay weights jointly to maximize the received signal-to-noise ratio (SNR) at the destination terminal with both individual and total power constraints at the relays. We show that the optimal collaborative-relay beamforming (CRB) solution achieves the full diversity of a MISO antenna system. Another main contribution of this letter is a distributed algorithm that allows each individual relay to learn its own weight, based on the Karush-Kuhn-Tucker (KKT) analysis.

关键词： Collaborative beamforming distributed implementation relay

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distributed implementation of Iterative Kalman Filter Localization with Taylor Expansion for Wireless Sensor Networks

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电脑学刊 2019年第3期30卷 44-58页

作者： Yue-Jiao Wang Zhong Ma Xue-Han Tang

The article integrates the theoretical study, simulation validation and performance analysis to make a deep research on distributed implementation of iterative localization technology in wireless sensor networks. Firstly, we utilize Kalman filter method based on square-root cubature to estimate and correct the node's position in real time. We establish a distributed iterative localization algorithm where the nodes that get localized in the current generation serve as references for remaining nodes to localize and the localization process is repeated. In order to improve the deficiency on location accuracy generated from propagating localization errors, and then we formulate the error feedback control method with Taylor series expansion as condition of evaluating whether a node succeed in localization, which is applied to iterative localization to establish a Taylor feedback Kalman filter localization algorithm. The simulation validation shows that the location accuracy of this kind of algorithm can fully meet the location requirement of the wireless sensor networks. Compared with the traditional method, the results illustrate the performance advantages of the error feedback control method and its contribution to the accuracy of the node position estimation.

关键词： distributed implementation iterative localization algorithm Kalman filter Taylor feedback wireless sensor networks

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Noncoherent Joint Transmission Beamforming for Dense Small Cell Networks: Global Optimality, Efficient Solution and distributed implementation

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2020年第9期19卷 5891-5907页

作者： Vu, Quang-Doanh Tran, Le-Nam Juntti, Markku Univ Oulu Ctr Wireless Commun Oulu 90014 Finland Univ Coll Dublin Sch Elect & Elect Engn Dublin 4 Ireland

We investigate the coordinated multi-point noncoherent joint transmission (JT) in dense small cell networks. The goal is to design beamforming vectors for macro cell and small cell base stations (BSs) such that the weighted sum rate of the system is maximized, subject to a total transmit power at individual BSs. The optimization problem is inherently nonconvex and intractable, making it difficult to explore the full potential performance of the scheme. To this end, we first propose an algorithm to find a globally optimal solution based on the generic monotonic branch reduce and bound optimization framework. Then, for a more computationally efficient method, we adopt the inner approximation (InAp) technique to efficiently derive a locally optimal solution, which is numerically shown to achieve near-optimal performance. In addition, for decentralized networks such as those comprising of multi-access edge computing servers, we develop an algorithm based on the alternating direction method of multipliers, which distributively implements the InAp-based solution. Our main conclusion is that the noncoherent JT is a promising transmission scheme for dense small cell networks, since it can exploit the densitification gain, outperforms the coordinated beamforming, and is amenable to distributed implementation.

关键词： Computer architecture Array signal processing Microcell networks Wireless communication Servers Microprocessors Synchronization Dense small cell networks noncoherent joint transmission weighted sum rate multi-access edge computing distributed implementation branch reduce and bound inner approximation alternating direction method of multipliers

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A distributed implementation using Apache Spark of a genetic algorithm applied to test data generation 17

A distributed implementation using Apache Spark of a genetic...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Paduraru, Ciprian Melemciuc, Marius-Constantin Stefanescu, Alin Univ Bucharest Bucharest Romania Elect Arts Bucharest Romania

ISBN: (纸本)9781450349390

This paper presents a distributed implementation for a genetic algorithm, using Apache Spark, a fast and popular data processing framework. Our approach is rather general, but in this paper the parallelized genetic algorithm is used for test data generation for executable programs. The viability of the approach is demonstrated on two examples.

关键词： distributed implementation Apache Spark genetic algorithms test data generation test coverage

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Cosin: Controllable Social Influence Maximization and Its distributed implementation in Large-scale Social Networks 19

Cosin: Controllable Social Influence Maximization and Its Di...

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48th International Conference on Parallel Processing (ICPP)

作者： Zhou, Jingya Fan, Jianxi Wang, Jin Soochow Univ Suzhou Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing Jiangsu Peoples R China Soochow Univ Prov Key Lab Comp Informat Proc Technol Suzhou Peoples R China

ISBN: (纸本)9781450362955

Influence Maximization (IM) has been extensively applied to many fields, and the viral marketing in today's online social networks (OSNs) is one of the most famous applications, where a group of seed users are selected to activate more users in a distributed cascading fashion. Many prior work explore the IM problem based on the assumption of given budget. However, the budget assumption does not hold in many practical scenarios, since companies might have no sufficient prior knowledge about the market. Moreover, companies prefer a moderately controllable viral marketing that allows them to adjust marketing decision according to the market reaction. In this paper, we propose a new problem, called Controllable social influence maximization (Cosin), to find a set of seed users inside a controllable scope to maximize the benefit given an expected return on investment (ROI). Like the IM problem, the Cosin problem is also NP-hard. We present a distributed multi-hop based framework for the influence estimation, and design a (1/ 2 + epsilon)-approximate algorithm based on the proposed framework. Moreover, we further present a distributed implementation to accelerate the execution of algorithm for large-scale social networks. Extensive experiments with a billion-scale social network indicate that the proposed algorithms outperform state-of-the-art algorithms in both benefit and running time.

关键词： Online social networks Influence maximization Viral marketing distributed implementation

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