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Efficient dissemination of mobile agents

Efficient dissemination of mobile agents

引用

international conference on distributed computing systems Workshop

作者： W. theilmann K. Rothermel Institute of Parallel and Distributed High-Performance Systems University of Stuttgart Stuttgart Germany

An often claimed benefit of mobile agent technology is that it reduces communication cost, but there is hardly any scenario in which this advantage has been proven or quantified on an Internet scale. One important reason for this lack of quantification is that agent systems do not have global knowledge about the quality of network connections between arbitrary agent platforms and data servers. We present an approach for representing a network in a way that allows to derive approximately the quality of network connections between agent platforms and data servers. By using this representation we provide an algorithm which computes a schedule for the efficient dissemination of a mobile agent. the experimental validation of our approach shows that communication cost can be reduced by more than 50 percent in many situations.

关键词： Mobile agents Network servers Costs Web server Mobile communication Internet Delay Context Information retrieval National electric code

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A Failure Handling Framework for distributed Data Mining Services on the Grid

A Failure Handling Framework for Distributed Data Mining Ser...

引用

Euromicro conference on parallel, distributed and Network-Based Processing

作者： Eugenio Cesario Domenico Talia ICAR-CNR Rende Italy University of Calabria Rende Italy

Fault tolerance is an important issue in Grid computing, where many and heterogenous machines are used. In this paper we present a flexible failure handling framework which extends a service-oriented architecture for distributed Data Mining previously proposed, addressing the requirements for fault tolerance in the Grid. the framework allows users to achieve failure recovery whenever a crash can occur on a Grid node involved in the computation. the implemented framework has been evaluated on a real Grid setting to assess its effectiveness and performance.

关键词： Computational modeling Data mining Fault tolerance Fault tolerant systems Algorithm design and analysis Data models Computer architecture

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RCC: A distributed Data Streaming Software Library for Robot-Cloud Platforms

RCC: A Distributed Data Streaming Software Library for Robot...

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19th IEEE international conference on Pervasive computing and Communications (IEEE PerCom)

作者： Zhang, Yuhong Sun, Jingtao Ouyang, Chen Chen, Mingkang Wang, Xinyao Wang, Qiang Wuhan Univ Technol Sch Logist Engn Wuhan Peoples R China Natl Inst Informat Tokyo Japan Tokyo Univ Agr & Technol Grad Sch Engn Tokyo Japan Grad Univ Adv Studies Sokendai Dept Informat Tokyo Japan Univ Calif Riverside Dept Mech Engn Riverside CA 92521 USA

ISBN: (纸本)9781665404242

Driven by new technologies such as cloud computing and AI, the cloud robot has entered a golden period of rapid development. the problem that restricts robot developers in current cloud robot research is the lack of a safe way to transmit messages between edge and cloud. therefore, in this paper, we propose the RCC (Robot Cloud Communication), a Python-based software library, which can help swarm intelligence robots data to be efficiently and securely transferred to different types of business clouds or private cloud platforms. In addition, we integrate the RCC function library and can also provide high-quality data security guarantees for development users when sending and receiving data. through our approach, we successfully implemented the development of an indoor 3D map application which is difficult to achieve on a single robot platform. Our experimental results show that our RCC is not only very stable in performance of reading and writing, but also shows great performance in data encryption and decryption.

关键词： Smart Edge Cloud computing Robot IoT Kafka Security

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A Framework for Managing MapReduce Applications in Dynamic distributed Environments

A Framework for Managing MapReduce Applications in Dynamic D...

引用

Euromicro conference on parallel, distributed and Network-Based Processing

作者： Fabrizio Marozzo Domenico Talia Paolo Trunfio DEIS University of Calabria Rende Cosenza Italy DEIS ICAR-CNR and University of Calabria Rende Cosenza Italy

MapReduce is a programming model widely used in data centers for processing large data sets in a highly parallel way. Current MapReduce systems are based on master-slave architectures that do not cope well with dynamic node participation, since they are mostly designed for conventional parallel computing platforms. On the contrary, in Internet-based computing environments, node churn and failures - including master failures - are likely to happen since nodes join and leave the network at an unpredictable rate. the goal of this work is enabling the use of MapReduce in dynamic distributed environments so as to combine the effectiveness of a well-established programming model with the scalability of a large-scale computing infrastructure. this paper presents an adaptive MapReduce framework, called P2P-MapReduce, which exploits a peer-to-peer model to manage intermittent node participation, master failures and job recovery in a decentralized but effective way, so as to provide a more robust MapReduce middleware that can be effectively exploited in Internet-scale dynamic distributed environments.

关键词： Peer to peer computing Computational modeling Computer architecture Indexes Programming Maintenance engineering Data models

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A parallel and distributed Topological Approach to 3D IC Optimal Layout Design 19th

A Parallel and Distributed Topological Approach to 3D IC Opt...

引用

19th international conference on Artificial Intelligence and Soft computing, ICAISC 2020

作者： Grzesiak-Kopeć, Katarzyna Ogorzalek, Maciej Department of Information Technologies Jagiellonian University in Kraków Kraków Poland

ISBN: (纸本)9783030614003

the task of 3D ICs layout design involves the assembly of millions of components taking into account many different requirements and constraints such as topological, wiring or manufacturability ones. It is a NP-hard problem that requires new non-deterministic and heuristic algorithms. Considering the time complexity, the commonly applied Fiduccia-Mattheyses partitioning algorithm is superior to any other local search method. Nevertheless, it can often miss to reach a quasi-optimal solution in 3D spaces. the presented approach uses an original 3D layout graph partitioning heuristics implemented with use of the extremal optimization method. the goal is to minimize the total wire-length in the chip. In order to improve the time complexity a parallel and distributed Java implementation is applied. Inside one Java Virtual Machine separate optimization algorithms are executed by independent threads. the work may also be shared among different machines by means of the Java Remote Method Invocation system. © 2020, Springer Nature Switzerland AG.

关键词： Heuristic algorithms

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Internet and distributed computing systems 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Giuseppe Di Fatta Giancarlo Fortino Wenfeng Li Mukaddim Pathan Frederic Stahl Antonio Guerrieri

ISBN: (数字)9783319232379

ISBN: (纸本)9783319232362

this book constitutes the refereed proceedings of the 8th international conference on Internet and distributed computing systems, IDCS 2015, held in Windsor, UK, in September 2015. the 19 revised full and 6 revised short papers presented were carefully reviewed and selected from 42 submissions. the selected contributions covered cutting-edge aspects of Cloud computing and Internet of things, sensor networks, parallel and distributed computing, advanced networking, smart cities and smart buildings, Big Data and social networks.

关键词： Computer Communication Networks Information systems Applications (incl. Internet) Algorithm Analysis and Problem Complexity systems and Data Security Information Storage and Retrieval Software Engineering

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Topic 6: Grid, Cluster and Cloud computing (Introduction)

Topic 6: Grid, Cluster and Cloud Computing (Introduction)

引用

19th international conference on Euro-Par

作者： Laure, Erwin Kao, Odej Badia, Rosa M. Lefevre, Laurent Di Martino, Beniamino Prodan, Radu Turilli, Matteo Warneke, Daniel KTH Royal Institute of Technology Sweden Technische Universität Berlin Germany Barcelona Supercomputing Center CSIC Spain INRIA University of Lyon France Seconda Universitá di Napoli Italy University of Innsbruck Austria University of Oxford United Kingdom International Computer Science Institute Berkeley United States

ISBN: (纸本)9783642400476

Grid and cloud computing have changed the IT landscape in the way we access and manage IT infrastructures. the use of computing resources has become essential for many applications in various areas. Both technologies provide easyto- use and on-demand access to large-scale infrastructures. the high number of submissions to “Topic 6: Grid, Cluster and Cloud computing-reflected the importance of the research area. the papers addressed key challenges regarding design, deployment, operation and use of Grid and cloud infrastructures. Moreover, several innovative algorithms and methods for fundamental capabilities and services that are required in a heterogeneous environment, such as adaptability, scalability, reliability and security, and to support applications as diverse as ubiquitous local services, enterprise-scale virtual organizations, and internet-scale distributed supercomputing were proposed. Finally, many experimental evaluations and use-cases delivered an insight into the deployment in real-world scenarios and showed interesting future application domains. Each submission was reviewed by at least four reviewers and, finally, we were able to select nine high-quality papers. the papers were grouped in four sessions that are briefly summarized in following.

关键词： Cluster computing

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A distributed Ensemble of Diverse Deep Learning Models for Predicting COVID-19 Cases 20

A Distributed Ensemble of Diverse Deep Learning Models for P...

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20th international conference on Smart Technologies, EUROCON 2023

作者： Hassan, Mohammad Mehedi Alrakhami, Mabrook S. Elhendi, Ahmed Zohier Alqahtani, Salman A. King Saud University Information Systems Department Ccis Riadh 11543 Saudi Arabia King Saud University Science Technology and Innovation Dept. Riadh 11543 Saudi Arabia King Saud University Computer Engineering Department Ccis Riadh 11543 Saudi Arabia

ISBN: (纸本)9781665463973

the outbreak of the COVID-19 pandemic has resulted in a significant impact on global health and economy. Forecasting the spread of COVID-19 cases is essential for policymakers to make informed decisions and allocate resources accordingly. Deep learning has shown promising results in predicting the spread of infectious diseases, including COVID-19. However, selecting the most appropriate model for a given forecasting task can be challenging, as no single model is guaranteed to perform well for all scenarios. In this paper, we propose a distributed ensemble approach that combines the predictions of different deep learning models, including Autoregressive Integrated Moving Average (Auto-ARIMA), Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM), to improve the accuracy of COVID-19 case forecasts. Specifically, we train each deep learning model on a subset of the data and aggregate their predictions to obtain an ensemble forecast. To achieve a distributed ensemble, we use an edge computing framework to train the deep learning models on multiple nodes in a parallel and distributed manner. We evaluate our approach on publicly available COVID-19 datasets, and our results show that the proposed ensemble model outperforms the individual models in terms of forecasting accuracy. Furthermore, our distributed ensemble approach significantly reduces the training and prediction time compared to training each model separately. © 2023 IEEE.

关键词： COVID-19

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An enhanced parallel loop self-scheduling scheme for cluster environments

An enhanced parallel loop self-scheduling scheme for cluster...

引用

international conference on Advanced Information Networking and Applications (AINA)

作者： Chao-Tung Yang Kuan-Wei Cheng Kuan-Ching Li High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung Taiwan

ISBN: (纸本)0769522491

In this paper, a parallel loop self-scheduling scheme for heterogeneous PC cluster systems is proposed. though the proposed scheme does allow users to choose parameters before the execution initialization phase, there are still weaknesses that motivate us to go further with new improvements in that scheme. For instance, a decision on a fixed and monotonous parameter can easily lead to invalid schedule by using previous input information. thus, it is proposed in this paper a new scheme, where the scheduling parameter can be adjusted dynamically and fit into most widely available computer systems, in order to provide higher overall performance.

关键词： Processor scheduling Dynamic scheduling Load management Master-slave Concurrent computing distributed computing Clustering algorithms Runtime Computer science Scheduling algorithm

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A way towards efficiency of SCADA infrastructure

A way towards efficiency of SCADA infrastructure

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19h IEEE international conference and Workshops on Engineering of Computer-Based systems (ECBS)

作者： Atlagic, Branislav Sagi, Mihaly Milinkov, Dejan Bogovac, Bojan Culaja, Stanko Univ Novi Sad Fac Tech Sci Novi Sad 21000 Serbia

ISBN: (纸本)9780769546643

Traditional SCADA solutions are currently under strong pressure by market, to shift their focus from process control of a limited set of industrial plants, to the control of a whole large-scale system. Usually this whole system is only partially covered by SCADA IO signals;therefore complex simulation model is required not only to give decision support, but also to replace all missing measurements. the whole control system has to be fully integrated, where SCADA infrastructure needs to hold and distribute all data, both SCADA and calculated. It leads to the extreme increase of real-time database, with millions of data points. It is a challenge that traditional SCADA designs, based on shared memory database and competing processes, cannot fulfill in real-time. the paper presents an alternative approach architecture and basic functionality of a SCADA system developed in line with this concept. It implements a SCADA server as a single executable with multiple threads, sharing data points stored in its own local memory. threads provide parallel execution, while data integrity is achieved through careful data organization/segmentation, thread priorities and the use of thread-safe primitives for accessing data. It easily provides performances required by this type of applications.

关键词： SCADA distributed architecture

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