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OLAP performance of distributed PostgreSQL and MongoDB on OpenStack. Preliminary Results on Smaller Scale Factors 23

OLAP performance of distributed PostgreSQL and MongoDB on Op...

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23rd RoEduNet conference: Networking in Education and Research, RoEduNet 2024

作者： Fotache, Marin Badea, Catalina Cluci, Marius-Iulian Pinzaru, Ciprian Esanu, Codrin-Stefan Rusu, Octavian Alexandru Ioan Cuza University of Iasi Dept.of Accounting Information Systems and Statistics Iasi Romania Alexandru Ioan Cuza University of Iasi Iasi Romania Alexandru Ioan Cuza University of Iasi S.C. HVM SRL Iasi Romania Alexandru Ioan Cuza University of Iasi Faculty of Physics Iasi Romania

ISBN: (纸本)9798331540388

Traditional relational or SQL database servers and document/JSON database servers are part of state-of-The-Art data architectures. Comparing the database query (OLAP) performance of relational and document data stores is challenging because of myriads of options in data modeling, query features, data distribution, processing distribution, etc. Based on the TPC-H benchmark tools, this paper presents the initial findings of converting the relational TPC-H schema deployed in a PostgreSQL/Citus cluster into a denormalized JSON schema deployed in a MongoDB cluster and subsequently mapping a 296-query set from SQL to MongoDB Aggregation Framework. The success of each query execution within a 10-minute timeout was collected for both PostgreSQL and MongoDB in six scenarios defined by two small-scale factors (0.01 and 0.1 GB) and three values of nodes (3,6 and 9) for data distribution and processing. Results show that the database server is associated with the success of query execution. © 2024 IEEE.

关键词： Structured Query Language

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Optimizing State-Intensive Non-Blocking Queries Using Run-time Adaptation

Optimizing State-Intensive Non-Blocking Queries Using Run-ti...

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international conference on Data Engineering workshops

作者： Bin Liu Mariana Jbantova Elke A. Rundensteiner Worcester Polytechnic Institute Worcester MA USA

Main memory is a critical resource when processing non-blocking queries with state intensive operators that require real-time responses. While partitioned parallel processing can alleviate the stringent memory demands in some cases, in general even in a distributed system main memory remains bounded. In this work, we thus investigate the integration of two run-time adaptation techniques, namely, state spill to disk and state relocation to an alternate machine, to handle this memory shortage problem. We analyze the tradeoffs regarding key factors affecting these two run-lime operator state adaptation techniques in a modern compute-cluster environment. Two strategics, lazy-disk and active-disk, are then proposed that integrate both state spill and state relocation adaptations with different emphasis on local versus global decision making. Extensive experiments of the proposed query processing system conducted on a compute-cluster (not merely a simulation) confirm the effectiveness of these strategies.

关键词： Exchange rates Query processing Real time systems Decision support systems Remote monitoring Parallel processing Runtime environment Decision making Computational modeling Intrusion detection

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TFluxSCC: Exploiting Performance on Future Many-Core systems through Data-Flow

TFluxSCC: Exploiting Performance on Future Many-Core Systems...

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Euromicro conference on Parallel, distributed and Network-Based Processing

作者： Andreas Diavastos Giannos Stylianou Pedro Trancoso Department of Computer Science University of Cyprus Nicosia Cyprus

The current trend in processor design is to increase the number of cores as to achieve a desired performance. While having a large number of cores on a chip seems to be feasible in terms of the hardware, the development of the software that is able to exploit that parallelism is one of the biggest challenges. In this paper we propose a Data-Flow based system that can be used to exploit the parallelism in large-scale many-core processors in an effective and efficient way. Our proposed system - TFlux SCC - is an extension of the TFlux Data-Driven Multithreading (DDM), which evolved to exploit the parallelism of the 48-core Intel Single-chip Cloud computing (SCC) processor. With TFlux SCC we achieve scalable performance using a global address space without the need of cache-coherency support. Our scalability study shows that application's performance can scale, with speedup results reaching up to 48x for 48 cores. The findings of this work provide insight towards what a Data-Flow implementation requires and what not from a many-core architecture in order to scale the performance.

关键词： Message systems Hardware Multicore processing Parallel processing Programming Runtime Software

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A distributed Dataflow Model for Task-Uncoordinated Parallel Program Execution

A Distributed Dataflow Model for Task-Uncoordinated Parallel...

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international conference on Parallel Processing workshops (ICPPW)

作者： Lucas A. Wilson Jeffery von Ronne The University of Texas at San Antonio San Antonio Texas Texas Advanced Computing Center The University of Texas at Austin Austin Texas University of Texas at San Antonio San Antonio TX US

ISBN: (纸本)9781479956166

High Performance computing (HPC) systems now consist of many thousands of individual servers. While relatively scalable and cost effective, these systems suffer from a complexity of scale that will not improve with increasing machine size. It will become increasingly difficult, if not impossible, for HPC systems to maintain node availability long enough for any type of worthwhile scientific calculations to be performed. Existing execution and programming models, which are dependent on guaranteed hardware reliability, are not well suited to future distributed memory parallel systems where hardware reliability cannot be guaranteed. We propose a distributed dataflow execution model which utilizes a distributed dictionary for data memoization, allowing each parallel task to schedule instructions without direct inter-task coordination. We provide a description of the proposed execution model, including program formulation and autonomous dataflow task selection. Experiments performed demonstrate the proposed model's ability to automatically distribute work across tasks, as well as the proposed model's ability to scale in both shared memory and distributed memory.

关键词： Dictionaries Computational modeling Data models Mathematical model Hardware distributed databases Program processors

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Fractional Order computing and Modeling with Portending Complex Fit Real-World Data 23rd

Fractional Order Computing and Modeling with Portending Comp...

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23rd international conference on Computational Science and its Applications (ICCSA)

作者： Karaca, Yeliz Rahman, Mati Ur Baleanu, Dumitru Univ Massachusetts Chan Med Sch UMASS 55 Lake Ave North Worcester MA 01655 USA MIT 77 Massachusetts Ave Cambridge MA 02139 USA Lebanese Amer Univ Dept Comp Sci & Math Beirut Lebanon Cankaya Univ Dept Math TR-1406530 Ankara Turkiye Inst Space Sci Bucharest Romania

ISBN: (纸本)9783031371042;9783031371059

Fractional computing models identify the states of different systems with a focus on formulating fractional order compartment models through the consideration of differential equations based on the underlying stochastic processes. Thus, a systematic approach to address and ensure predictive accuracy allows that the model remains physically reasonable at all times, providing a convenient interpretation and feasible design regarding all the parameters of the model. Towards these manifolding processes, this study aims to introduce new concepts of fractional calculus that manifest crossover effects in dynamical models. Piecewise global fractional derivatives in sense of Caputo and Atangana-Baleanu-Caputo (ABC) have been utilized, and they are applied to formulate the Zika Virus (ZV) disease model. To have a predictive analysis of the behavior of the model, the domain is subsequently split into two subintervals and the piecewise behavior is investigated. Afterwards, the fixed point theory of Schauder and Banach is benefited from to prove the existence and uniqueness of at least one solution in both senses for the considered problem. As for the numerical simulations as per the data, Newton interpolation formula has been modified and extended for the considered nonlinear system. Finally, graphical presentations and illustrative examples based on the data for various compartments of the systems have been presented with respect to the applicable real-world data for different fractional orders. Based on the impact of fractional order reducing the abrupt changes, the results obtained from the study demonstrate and also validate that increasing the fractional order brings about a greater crossover effect, which is obvious from the observed data, which is critical for the effective management and control of abrupt changes like infectious diseases, viruses, among many more unexpected phenomena in chaotic, uncertain and transient circumstances.

关键词： Fractional computing models crossover behavior complex fit real-world data mathematical biology computational biology fractional calculus piecewise global fractional derivatives Newton interpolation formula ABC fractional derivatives equicontinuous mapping Schauder's fixed point theorem dynamics of multi-compartment models fractional order compartment models stochastic differential equations differential equations

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IP Operations and Management 1

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丛书名： Lecture Notes in Computer Science

1000年

ISBN: (数字)9783540758532

ISBN: (纸本)9783540758525

On behalf of the IEEE Communications Society, the Technical Committee on Network Operations and Management (CNOM), the Manweek 2007 Organizing Committee, and the members of the IPOM Technical Program Committee, it is our pleasure to present the proceedings of the Seventh IEEE Workshop on IP Operations and Management (IPOM2007), held as part of Manweek 2007 during October 31-November 2, 2007. With the widespread deployment of IP-based networks, their operations and management have become increasingly important in terms of understanding emerging technical and scientific problems; lessons from such understanding are particularly important for future Internet design and management. Like the previous IPOM workshops, IPOM 2007 was co-located with several related events as part of the 3rd international Week on Management of Networks and Services (Manweek 2007). The other events were the 10th IFIP/IEEE international conference on Management of Multimedia and Mobile Networks and Services (MMNS 2007), the 18th IFIP/IEEE international Workshop on distributed systems: Operations and Management (DSOM 2007), the 2ndIEEE international Workshop on Modeling Autonomic Communications Environments (MACE 2007), and the 1st IEEE/IFIP international Workshop on End-to-End Virtualization and Grid Management (EVGM 2007). Co-locating those events provided the opportunity for an exchange of ideas between research communities that work on related topics, allowing participants to forge links and exploit synergies.

关键词： Computer Communication Networks Information systems Applications (incl. Internet) Management of computing and Information systems Multimedia Information systems Information Storage and Retrieval Communications Engineering, Networks

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Design of Federated Learning Engagement Method for Autonomous Vehicle Privacy Protection

Design of Federated Learning Engagement Method for Autonomou...

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international Symposium on Soft computing and Intelligent systems (SCIS)

作者： Jung-Sook Kim School of Contents and Design Kimpo University Gimpo-si Geyonggi-do Korea

An autonomous car is defined as a vehicle that can be operated only by an autonomous driving system and does not require a driver or intervention of a driver or passenger. Various types of data collected for fully autonomous car operation include personal information such as location, image, physical, behavior information, and license number. It is hard for a driver or pedestrian to recognize or control automated collection and processing of personal information by autonomous vehicles in real time. It is, therefore, necessary to prepare and apply appropriate countermeasures such as minimizing the collection of personal information, deleting and encrypting unnecessary information, etc. Federated Learning is a distributed machine learning technique that can learn Al models in cooperation with each other without directly sharing data distributed and stored in multiple locations, such as devices or institutions. Instead of transmitting individual client data to the central server (cloud), the Al model of the central server is sent to the client to train the model with each data. By repeating this process, the global Al model of the central server becomes more general and the accuracy of the local Al model of the client improves. In order to protect personal information collected while driving an autonomous car, this paper proposed a federated learning engagement method, where cross-device was used to engage in the federated learning consisting of a very large number of mobile devices, and based on this, personal information can be protected for the efficient operation of autonomous vehicles.

关键词： Privacy Federated learning Process control Data models Real-time systems Mobile handsets Servers

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A Performance Isolation Analysis of Disk-Intensive Workloads on Container-Based Clouds

A Performance Isolation Analysis of Disk-Intensive Workloads...

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Euromicro conference on Parallel, distributed and Network-Based Processing

作者： Miguel G. Xavier Israel C. De Oliveira Fabio D. Rossi Robson D. Dos Passos Kassiano J. Matteussi Cesar A.F. De Rose Pontifical Catholic University of Rio Grande do SuI (PUCRS) Faculty of Informatics Porto Alegre Brazil Fac. of Inf. Pontificia Universidade Catolica do Rio Grande do Sul Porto Alegre RS BR Pontificia Universidade Catolica do Rio Grande do Sul Porto Alegre RS BR

The popularity of Cloud computing due to the increasing number of customers has led Cloud providers to adopt resource-sharing solutions to meet growing demand for infrastructure resources. As the adoption of resource-sharing/consolidation in Cloud computing became arguably a well-established solution, the ability the underlying virtualization systems of preventing performance interferences from customers must also be understood. Virtualization systems based on containers, such as LXC, are the basis of the next-generation of Cloud computing and have become the most popular solution under PaaS/IaaS Cloud platforms with the rise of Docker -- an open platform for developers and sysadmins to build, ship, and run distributed applications. Such platforms have enticed many attentions globally, since they leverage container-based virtualization systems to offer high scalability while low performance overheads, the performance might be solely aggravated if the customers' workloads are consolidated onto the same hardware and the isolation layer does not properly isolate the shared resources. Performance isolation is an inherent concern of such systems due to the nature as they are conceived and is still an unexplored and open research topic, the consequences might influence in the adoption under shared Cloud computing platforms where Quality-of-Service is a crucial factor that cannot be disregarded. In this paper we analyze the performance interference suffered by disk-intensive workloads within very noisy-perturbed containers (different hardware components stressed). Our results show workload combinations whose performance degradation goes up to 38%, but in contrast we expose a workload-balanced scenario wherein the performance does not suffer any interference.

关键词： Containers Virtualization Measurement Stress Hardware Cloud computing Benchmark testing

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Effective delay control for high rate heterogeneous real-time flows

Effective delay control for high rate heterogeneous real-tim...

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international conference on distributed computing systems

作者： Weijia Jia Hanxing Wang Maoning Tang Wei Zhao Department of Computer Engineering and Information Technology City University of Hong Kong Kowloon Hong Kong China Department of Mathematics Shanghai University China Texas A and M University College Station TX USA

ISBN: (纸本)0769519202

This paper presents a new method to control the delay performance for high rate heterogeneous real-time traffic flows based on a novel traffic control algorithm which is a generalization of traditional (/spl sigma/, /spl rho/) regulator. Our new control algorithm operates like the traditional regulator under the normal loading situation, but provides more regulation for the high rate (heavy load condition) of the traffic. For a set of heterogenous real-time traffic flows R we can show that D/sub r/(R) /spl les/ D(R) where D/sub r/(R) and D(R) are the worst-case delay bounds with our new control algorithm and that with (/spl sigma/, /spl rho/) regulator respectively. More specifically, we develop a set of formula that can be used to set the parameters in our new traffic controller so that the worst case delay bound is minimized by streaming the traffic flow. We can prove that there exists a minimum (average) input rate p* such that D/sub r/(R) = D(R) for /spl rho/ /spl les/ /spl rho/* and D/sub r/(R) < D(R) for /spl rho/ > /spl rho/*. Using the extended regulator can effectively control the delay when the average heterogeneous traffic rate is high. The issues are particularly useful for Integrated Services where a flow may over claim its share of resource and for Differentiated Services where a class of traffic flows may possess very high rates.

关键词： Delay effects Traffic control Regulators Communication system traffic control High performance computing Information technology Mathematics Intserv networks Councils Bandwidth

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Environment partitioned distributed simulation of queueing systems 91

Environment partitioned distributed simulation of queueing s...

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Proceedings of the 23rd conference on Winter simulation

作者： John Craig Comfort School of Computer Science Florida International University Miami FL

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