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10th international symposium on NASA Formal Methods, NFM 2018

10th International Symposium on NASA Formal Methods, NFM 201...

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10th international symposium on NASA Formal Methods, NFM 2018

ISBN: (纸本)9783319779348

The proceedings contain 31 papers. The special focus in this conference is on NASA Formal Methods. The topics include: Twenty percent and a few days – Optimising a bitcoin majority attack;an even better approach – Improving the B.A.T.M.A.N. protocol through formal modelling and analysis;towards a formal safety framework for trajectories;static value analysis of python programs by abstract interpretation;model-based testing for general stochastic time;Strategy synthesis for autonomous agents using PRISM;the use of automated theory formation in support of hazard analysis;distributed model checking using ProB;optimal storage of combinatorial state spaces;formal assurance for cooperative intelligent autonomous agents;stubborn transaction reduction;certified Foata normalization for generalized traces;on the timed analysis of big-data applications;tuning permissiveness of active safety monitors for autonomous systems;sound black-box checking in the LearnLib;model-checking task parallel programs for data-race;consistency of property specification patterns with boolean and constrained numerical signals;Automatic generation of DO-178 test procedures;using test ranges to improve symbolic execution;Symbolic execution and reachability analysis using rewriting modulo SMT for spatial concurrent constraint systems with extrusion;ghosts for lists: A critical module of Contiki verified in Frama-C;Experience report: Application of falsification methods on the UxAS system;moDeS3: Model-based demonstrator for smart and safe cyber-physical systems;an executable formal framework for safety-critical human multitasking;simpler specifications and easier proofs of distributed algorithms using history variables;don’t miss the end: Preventing unsafe end-of-file comparisons;an efficient rewriting framework for trace coverage of symmetric systems.

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Graph-Based Speculative Query Execution in Relational databases 16

Graph-Based Speculative Query Execution in Relational Databa...

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16th international symposium on parallel and distributed Computing (ISPDC)

作者： Sasak-Okon, Anna Tudruj, Marek Univ Maria Curie Sklodowska Lublin Pl Marii Curie Sklodowskiej 5 PL-20031 Lublin Poland Polish Acad Sci Inst Comp Sci 21 Ordona Str PL-01237 Warsaw Poland Polish Japanese Inst Informat Technol 83 Koszykowa Str PL-02008 Warsaw Poland

ISBN: (纸本)9781538608623

The paper presents a method for parallel speculative query execution support to be applied in relational database systems. The method is based on dynamic analysis of input query stream in databases serviced in SQLite. A special representation of queries in the form of multigraphs is employed. A middleware called the Speculative Layer is introduced which determines the most promising speculative queries for execution based on analysis of current stream of user queries. The proposed approach assumes a dynamic query speculation window organized in the query queue, which is converted into a query multigraph subdue to the analysis. The paper presents the query graph modelling method and the query graph analysis algorithms based on specific metrics. They aim in finding best candidate queries for speculative execution which fit currently accumulated query window. Experimental results are presented based on the proposed algorithms assessment using a real testbed database serviced in SQLite.

关键词： Servers Relational databases Algorithm design and analysis Measurement Middleware

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A New Method for Improving the Security and Access Time to Data Blocks in Big databases

A New Method for Improving the Security and Access Time to D...

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2018 international Conference on Current Trends towards Converging Technologies, ICCTCT 2018

作者： Nasseri, Mahnaz Jameii, Mahdi Mohseni, Mohsen Department of Computer Engineering Malard Branch Islamic Azad University Tehran Iran Department of Computer Engineering Shahr-e-Qods Branch Islamic Azad University Tehran Iran

ISBN: (纸本)9781538637012

Big Data is a set of data with large volume, a various and complex structure and their size is beyond of limit which can be grasped, managed and processed with usual softwares in a reasonable time. Data volume in the world is increasing day to day. Traditional database systems are not able to save and analyze so much data volume. Because the internet is growing, Big Data volume is growing too. Organizations have become very flexible and open. New data types will make new challenges. One of the key challenges in Big Data is security. According to the increasing volume and variety of Big Data, security challenges will grow too. From the other side, software infrastructures like Hadoop make it possible for extenders to process in thousands of nodes parallel. In this paper, a review will be done on Big Data and security challenges and a method will be offered for improving the efficiency of security and access time to data blocks in Big Data. © 2018 IEEE.

关键词： MapReduce

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DOORS: distributed Object Oriented Runtime System (Position Paper) 16

DOORS: Distributed Object Oriented Runtime System (Position ...

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16th international symposium on parallel and distributed Computing (ISPDC)

作者： Palanciuc, Dorin Univ Politehn Bucuresti Comp Sci Dept Fac Automat Control & Comp Bucharest Romania

ISBN: (纸本)9781538608623

The large software applications of today provide abstractions of the real-life systems that they support. A digital model of the system, and of the changes that occur within, are being maintained and updated, as triggered by real-life events. Morphologically, such applications contain several distinct architectural entities: databases holding the state, central components describing how the system reacts to external events and mechanisms through which the user can view the current state and issue new commands. Each of these entities may use distinct paradigms and employ different technologies. A production-ready software application ends up assembling a relatively high technology stack and provides the final abstractions for both the problem and its solution. In this paper we propose a short-circuit for the long chain of technologies that are usually employed in large, production-ready software applications. The resulting architecture is a distributed, message-based system which behaves as a hybrid between a database and a runtime environment. The system operates with persistent and live entities, encapsulating both state and operations and therefore easily assimilated with OOP classes.

关键词： distributed computing message passing object oriented runtime storage

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HPDC 2017 - proceedings of the 26th international symposium on High-Performance parallel and distributed Computing

HPDC 2017 - Proceedings of the 26th International Symposium ...

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26th ACM international symposium on High-Performance parallel and distributed Computing, HPDC 2017

ISBN: (纸本)9781450346993

The proceedings contain 19 papers. The topics discussed include: enabling workflow-aware scheduling on HPC systems;parallel stream processing against workload skewness and variance;NICE: network-integrated cluster-efficient storage;MaDaTS: managing data on tiered storage for scientific workflows;ArrayUDF: user-defined scientific data analysis on arrays;knor: a NUMA-optimized in-memory, distributed and semi-external-memory k-means library;to push or to pull: on reducing communication and synchronization in graph computations;better safe than sorry: grappling with failures of in-memory data analytics frameworks;LetGo: a lightweight continuous framework for HPC applications under failures;towards a more complete understanding of SDC propagation;COS: a parallel performance model for dynamic variations in processor speed, memory speed, and thread concurrency;explaining wide area data transfer performance;predicting output performance of a petascale supercomputer;TCP throughput profiles using measurements over dedicated connections;IOGP: an incremental online graph partitioning algorithm for distributed graph databases;and machine and application aware partitioning for adaptive mesh refinement applications.

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Reconfiguring parallel State Machine Replication 36

Reconfiguring Parallel State Machine Replication

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36th IEEE symposium on Reliable distributed systems (SRDS)

作者： Alchieri, Eduardo Dotti, Fernando Mendizabal, Odorico M. Pedone, Fernando Univ Brasilia Dept Ciencia Comp Brasilia DF Brazil Pontificia Univ Catolica Rio Grande do Sul Fac Informat Porto Alegre RS Brazil Univ Fed Rio Grande Ctr Ciencias Computacionais Porto Alegre RS Brazil Univ Svizzera Italiana Lugano Switzerland

ISBN: (纸本)9781538616796

State Machine Replication (SMR) is a well-known technique to implement fault-tolerant systems. In SMR, servers are replicated and client requests are deterministically executed in the same order by all replicas. To improve performance in multi-processor systems, some approaches have proposed to parallelize the execution of non-conflicting requests. Such approaches perform remarkably well in workloads dominated by non-conflicting requests. Conflicting requests introduce expensive synchronization and result in considerable performance loss. Current approaches to parallel SMR define the degree of parallelism statically. However, it is often difficult to predict the best degree of parallelism for a workload and workloads experience variations that change their best degree of parallelism. This paper proposes a protocol to reconfigure the degree of parallelism in parallel SMR on-the-fly. Experiments show the gains due to reconfiguration and shed some light on the behavior of parallel and reconfigurable SMR.

关键词： parallel processing Protocols Servers Synchronization Concurrent computing Semantics Message systems

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proceedings - 2017 IEEE 16th international symposium on parallel and distributed Computing, ISPDC 2017

Proceedings - 2017 IEEE 16th International Symposium on Para...

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16th IEEE international symposium on parallel and distributed Computing, ISPDC 2017

ISBN: (纸本)9781538608623

The proceedings contain 20 papers. The topics discussed include: contention-aware selective caching to mitigate intra-warp contention on GPUs;an autonomic approach for the selection of robust dynamic loop scheduling techniques;towards the reproducibility of using DLS techniques in scientific applications;exploring the relation between two levels of scheduling using a novel simulation approach;reducing fragmentation on 3D Torus-based HPC systems using packing-based job scheduling and job placement reconfiguration;a bi-objective scheduling approach for energy optimisation of executing and transmitting HPC Applications in decentralised multi-cloud systems;three-tier private cloud application management system with on-site hardware;the performance and scalability of the SHMEM and corresponding MPI-3 routines on a Cray XC30;a new parallelization scheme for the Hermite interpolation based gyroaverage operator;Benchmarking the WRF Model on Bluegene/P, cluster, and cloud platforms and accelerating model setup through parallel genetic algorithms;the OpenDC vision: towards collaborative datacenter simulation and exploration for everybody;on reliability-aware server consolidation in cloud datacenters;accelerating machine learning on sparse datasets with a distributed memory vector architecture;graph-based speculative query execution in relational databases;and understanding the impact of fine-grained data sharing and thread communication on heterogeneous workload development.

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Assessing Data Usefulness for Failure Analysis in Anonymized System Logs

Assessing Data Usefulness for Failure Analysis in Anonymized...

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international symposium on parallel and distributed Computing

作者： Siavash Ghiasvand Florina M. Ciorba Technische Universität Dresden Germany University of Basel Switzerland

System logs are a valuable source of information for the analysis and understanding of systems behavior for the purpose of improving their performance. Such logs contain various types of information, including sensitive information. Information deemed sensitive can either directly be extracted from system log entries by correlation of several log entries, or can be inferred from the combination of the (non-sensitive) information contained within system logs with other logs and/or additional datasets. The analysis of system logs containing sensitive information compromises data privacy. Therefore, various anonymization techniques, such as generalization and suppression have been employed, over the years, by data and computing centers to protect the privacy of their users, their data, and the system as a whole. Privacy-preserving data resulting from anonymization via generalization and suppression may lead to significantly decreased data usefulness, thus, hindering the intended analysis for understanding the system behavior. Maintaining a balance between data usefulness and privacy preservation, therefore, remains an open and important challenge. Irreversible encoding of system logs using collision-resistant hashing algorithms, such as SHAKE-128, is a novel approach previously introduced by the authors to mitigate data privacy concerns. The present work describes a study of the applicability of the encoding approach from earlier work on the system logs of a production high performance computing system. Moreover, a metric is introduced to assess the data usefulness of the anonymized system logs to detect and identify the failures encountered in the system.

关键词： Data privacy Encoding Encryption Measurement distributed databases High performance computing Privacy

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distributed Container-Based Evaluation Platform for Private/Large Datasets

Distributed Container-Based Evaluation Platform for Private/...

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international symposium on parallel and distributed Computing

作者： Ivan Eggel Roger Schaer Henning Müller HES-SO Institute of Information Systems Sierre Switzerland

The rise of big data and artificial intelligence techniques such as deep learning has lead to an exponential increase in stored data in various fields, including medical imaging, genetics and financial trading. Sharing these increasing amounts of data for research is challenging, as privacy risks increase with the increased size of data. Physically moving very large datasets to researchers is inconvenient, as download or sending physical hard disks are not optimal. Research on sensitive data is often not possible, as sharing is not legal. The popularity of container-based technologies such as Docker has revolutionized the way applications are deployed, due to their self-sufficient, light-weight and portable nature. In this paper, we propose a novel distributed platform using containers for simple execution and evaluation of research applications on the data owner's infrastructure, bringing the algorithms to the data. This approach avoids the cumbersome transfer of large datasets and can help circumventing problems linked to non-shareable data by providing a sandboxed execution environment with read-only access to the data. At no point the data leave the data owner's site, giving researchers access to their evaluation results, only, and not the data themselves. The presented proof-of-concept confirms the feasibility of a distributed container-based evaluation platform for large and/or sensitive data. This has several advantages, including execution of code instead of submission of result files and availability of otherwise inaccessible data. The container architecture allows for minimal computational overhead, no software dependency management on the infrastructure, distributed runtime environment and isolation of processes from the underlying host system. A version addressing various identified architectural and security-related challenges has the potential to be deployed in a production setting and therefore allows researchers to gain insights from previously inacc

关键词： Containers Computer architecture Task analysis Machine learning distributed databases Biomedical imaging Graphics processing units

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Understanding System Characteristics of Online Erasure Coding on Scalable, distributed and Large-Scale SSD Array systems

Understanding System Characteristics of Online Erasure Codin...

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IEEE international symposium on Workload Characterization (IISWC)

作者： Koh, Sungjoon Zhang, Jie Kwon, Miryeong Yoon, Jungyeon Donofrio, David Kim, Nam Sung Jung, Myoungsoo Yonsei Univ Comp Architecture & Memory Syst Lab Sch Integrated Technol Yonsei Inst Convergence Technol Seoul South Korea Lawrence Berkeley Natl Lab Berkeley CA USA SK Telecom Seoul South Korea Univ Illinois Urbana IL USA

ISBN: (纸本)9781538612330

Large-scale systems with arrays of solid state disks (SSDs) have become increasingly common in many computing segments. To make such systems resilient, we can adopt erasure coding such as Reed-Solomon (RS) code as an alternative to replication because erasure coding can offer a significantly lower storage cost than replication. To understand the impact of using erasure coding on system performance and other system aspects such as CPU utilization and network traffic, we build a storage cluster consisting of approximately one hundred processor cores with more than fifty high-performance SSDs, and evaluate the cluster with a popular open-source distributed parallel file system, Ceph. Then we analyze behaviors of systems adopting erasure coding from the following five viewpoints, compared with those of systems using replication: (1) storage system I/O performance;(2) computing and software overheads;(3) I/O amplification;(4) network traffic among storage nodes;(5) the impact of physical data layout on performance of RS-coded SSD arrays. For all these analyses, we examine two representative RS configurations, which are used by Google and Facebook file systems, and compare them with triple replication that a typical parallel file system employs as a default fault tolerance mechanism. Lastly, we collect 54 block-level traces from the cluster and make them available for other researchers.

关键词： Encoding Arrays Maintenance engineering Layout Performance evaluation distributed databases Reliability

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