检索结果-内蒙古大学图书馆

5th IEEE International Conference on Smart Computing (SMARTCOMP)

作者： Mahmood, Khalid Orsborn, Kjell Risch, Tore Uppsala Univ Dept Informat Technol Uppsala Sweden

ISBN: (纸本)9781728116891

With the advent of cyber-physical systems, industrial internet of things (IIoT) and industrial analytics numerous application scenarios have emerged where business and mission-critical decisions depend upon large scale analysis of data in form of sensor streams. However, large volumes of sensor stream data generated at high frequency pose substantial challenges for existing scalable data analysis techniques requiring the use of high-performance distributed datastores. This work covers in-depth performance comparison of three principal categories of distributed state-of-the-art nosql datastores by evaluating their applicability and efficiency for large-scale analysis of sensor logs from real-world hydraulic power systems. One central datastore is selected from each of the three principal categories of nosql datastores: MongoDB from the document store, Cassandra from the column store and Redis from the distributed main memory key-value store to be included in the performance evaluation. Understanding the differences and behavior of this type of systems are crucial for optimizing application performance. Key insights from this work can serve as a basis for an improved understanding of the applicability of nosql datastores in systems for large scale data stream analysis. This will be important for supporting data analytics in IIoT applications as found in monitoring and control of Power plants, Smart Cities, Transportation systems, Environmental and Health monitoring, etc.

关键词： nosql datastores IoT Smart Computing

来源：评论

学校读者我要写书评

暂无评论

RAFIKI: A Middleware for Parameter Tuning of nosql datastores for Dynamic MetagenomicsWorkloads 17

RAFIKI: A Middleware for Parameter Tuning of NoSQL Datastore...

引用

18th ACM/IFIP/USENIX International Middleware Conference (Middleware)

作者： Mahgoub, Ashraf Wood, Paul Ganesh, Sachandhan Mitra, Subrata Gerlach, Wolfgang Harrison, Travis Meyer, Folker Grama, Ananth Bagchi, Saurabh Chaterji, Somali Purdue Univ W Lafayette IN 47907 USA Adobe Res San Jose CA USA Argonne Natl Lab Argonne IL 60439 USA

ISBN: (纸本)9781450347204

High performance computing (HPC) applications, such as metagenomics and other big data systems, need to store and analyze huge volumes of semi-structured data. Such applications often rely on nosql-based datastores, and optimizing these databases is a challenging endeavor, with over 50 configuration parameters in Cassandra alone. As the application executes, database workloads can change rapidly from read-heavy to write -heavy ones, and a system tuned with a read-optimized configuration becomes suboptimal when the workload becomes write-heavy. In this paper, we present a method and a system for optimizing nosql configurations for Cassandra and ScyllaDB when running HPC and metagenomics workloads. First, we identify the significance of configuration parameters using ANOVA. Next, we apply neural networks using the most significant parameters and their workload-dependent mapping to predict database throughput, as a surrogate model. Then, we optimize the configuration using genetic algorithms on the surrogate to maximize the workloaddependent performance. Using the proposed methodology in our system (RAFIKI), we can predict the throughput for unseen workloads and configuration values with an error of 7.5% for Cassandra and 6.9-7.8% for ScyllaDB. Searching the configuration spaces using the trained surrogate models, we achieve performance improvements of 41% for Cassandra and 9% for ScyllaDB over the default configuration with respect to a read-heavy workload, and also significant improvement for mixed workloads. In terms of searching speed, RAFIKI, using only 1/10000-th of the searching time of exhaustive search, reaches within 15% and 9.5% of the theoretically best achievable performances for Cassandra and ScyllaDB, respectively supporting optimizations for highly dynamic workloads.

关键词： Database automatic tuning Metagenomics workloads nosql datastores

来源：评论

学校读者我要写书评

暂无评论

Enabling Attribute-Based Access Control in nosql Databases

引用

IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING 2023年第1期11卷 208-223页

作者： Gupta, Eeshan Sural, Shamik Vaidya, Jaideep Atluri, Vijayalakshmi Indian Inst Technol Dept Comp Sci & Engn Kharagpur 721302 W Bengal India Rutgers State Univ Comp Informat Syst Newark NJ 07102 USA Rutgers State Univ MSIS Dept Comp Informat Syst Newark NJ 07102 USA Rutgers State Univ Ctr Informat Management Integrat & Connect CIMIC Newark NJ 07102 USA

nosql databases are being increasingly used for efficient management of high volumes of unstructured data in applications like information retrieval, natural language processing, social computing, etc. However, unlike traditional databases, data protection measures such as access control for these databases are still in their infancy, which could lead to significant vulnerabilities and security/privacy issues as their adoption increases. Attribute-based Access Control (ABAC), which provides a flexible and dynamic solution to access control, can be effective for mediating accesses in typical usage scenarios for nosql databases. In this paper, we propose a novel methodology for enabling ABAC in nosql databases. Specifically we consider MongoDB, which is one of the most popular nosql databases in use today. We present an approach to both specify ABAC access control policies and to enforce them when an actual access request has been made. MongoDB Wire Protocol is used for extracting and processing appropriate information from the requests. We also present a method for supporting dynamic access decisions using environmental attributes and handling of ad-hoc access requests through digitally signed user attributes. Results from an extensive set of experiments on the Enron corpus as well as on synthetically generated data demonstrate the scalability of our approach. Finally, we provide details of our implementation on MongoDB and share a Github repository so that any organization can download and deploy the same for enabling ABAC in their own MongoDB installations.

关键词： Access control nosql databases Databases Servers Wires Protocols Organizations Attribute-based access control nosql datastores MongoDB

来源：评论

学校读者我要写书评

暂无评论

Approximating closed fork-join queueing networks using product-form stochastic Petri-nets

引用

JOURNAL OF SYSTEMS AND SOFTWARE 2015年 110卷 264-278页

作者： Osman, Rasha Harrison, Peter G. Univ London Imperial Coll Sci Technol & Med Dept Comp London SW7 2AZ England

Computing paradigms have shifted towards highly parallel processing and massive replication of data. This entails the efficient distribution of requests and the synchronization of results provided to users. Guaranteeing SLAs requires the ability to evaluate the performance of such systems while taking the effect of non-parallel workloads into consideration. This can be achieved with performance models that are able to represent both parallel and sequential workloads. This paper presents a product-form stochastic Petri-net approximation of fork-join queueing networks with interfering requests. We derive the necessary conditions that guarantee the accuracy of the approximations and verify this through examples in comparison to simulation. We apply these approximate models to the performance evaluation of replication in nosql cloud datastores and illustrate the composition of large models from smaller models, thus facilitating the ability to model a range of deployment scenarios. We show the efficiency of our solution method, which finds the product-form solution of the models without the representation of the state-space of the underlying CTMC. (c) 2015 The Authors. Published by Elsevier Inc.

关键词： Product-form stochastic Petri nets Reversed Compound Agent Theorem (RCAT) nosql datastores

来源：评论

学校读者我要写书评

暂无评论

Enhancing MongoDB with Purpose-Based Access Control

引用

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2017年第6期14卷 591-604页

作者： Colombo, Pietro Ferrari, Elena Univ Insubria Dipartimento Sci Teor & Applicate Varese Italy

Privacy has become a key requirement for data management systems. Nevertheless, nosql datastores, namely highly scalable non relational database management systems, which often support data management of Internet scale applications, still do not provide support for privacy policies enforcement. With this work, we begin to address this issue, by proposing an approach for the integration of purpose based policy enforcement capabilities into MongoDB, a popular nosql datastore. Our contribution consists of the enhancement of the MongoDB role based access control model with privacy concepts and related enforcement monitor. The proposed monitor is easily integrable into any MongoDB deployment through simple configurations. Experimental results show that our monitor enforces purpose-based access control with low overhead.

关键词： Purpose-based access control nosql datastores MongoDB

来源：评论

学校读者我要写书评

暂无评论

Evaluating the effects of access control policies within nosql systems

引用

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2021年 114卷 491-505页

作者： Colombo, Pietro Ferrari, Elena Univ Insubria Dept Theoret & Appl Sci Via O Rossi 9 I-21100 Varese Italy

Access control is a key service of any data management system. It allows regulating the access to data resources at different granularity levels on the basis of access control models which vary on the protection options they offer. The more powerful is the access control model in terms of protection requirements, the more difficult is for security administrators to understand the effect of a set of access control policies on the protected resources. This is further complicated within schemaless systems, like nosql datastores, when fine grained access control policies are specified for data resources characterized by heterogeneous structures. The lack of a reference data model and related manipulation languages exacerbates this issue. To the best of our knowledge, a general approach to evaluate the impact of access control policies on the protected resources within nosql systems is still missing. In this paper, we start to fill this void, by proposing a data model agnostic approach, which, starting from schemaless datasets protected by different discretionary access control models, derives a view of the protected resources that points out authorized and unauthorized contents. Experimental results show the approach efficiency even with large datasets. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Access control nosql datastores Big data Authorized views

来源：评论

学校读者我要写书评

暂无评论

Privacy Aware Access Control for Big Data: A Research Roadmap

引用

BIG DATA RESEARCH 2015年第4期2卷 145-154页

作者： Colombo, Pietro Ferrari, Elena Univ Insubria Dept Theoret & Appl Sci I-21100 Varese Italy

Big Data is an emerging phenomenon that is rapidly changing business models and work styles [1]. Big Data platforms allow the storage and analysis of high volumes of data with heterogeneous format from different sources. This integrated analysis allows the derivation of properties and correlations among data that can then be used for a variety of purposes, such as making predictions that can profitably affect decision processes. As a matter of fact, nowadays Big Data analytics are generally considered an asset for making business decisions. Big Data platforms have been specifically designed to support advanced form of analytics satisfying strict performance and scalability requirements. However, no proper consideration has been devoted so far to data protection. Indeed, although the analyzed data often include personal and sensitive information, with relevant threats to privacy implied by the analysis, so far Big Data platforms integrate quite basic form of access control, and no support for privacy policies. Although the potential benefits of data analysis are manifold, the lack of proper data protection mechanisms may prevent the adoption of Big Data analytics by several companies. This motivates the fundamental need to integrate privacy and security awareness into Big Data platforms. In this paper, we do a first step to achieve this ambitious goal, discussing research issues related to the definition of a framework that supports the integration of privacy aware access control features into existing Big Data platforms. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Big Data nosql datastores MapReduce systems Privacy policies Access control enforcement

来源：评论

学校读者我要写书评

暂无评论

Wrapping a nosql Datastore for Stream Analytics 21

Wrapping a NoSQL Datastore for Stream Analytics

引用

21st IEEE International Conference on Information Reuse and Integration for Data Science (IEEE IRI)

作者： Mahmood, Khalid Orsborn, Kjell Risch, Tore Uppsala Univ Dept Informat Technol Uppsala Sweden

ISBN: (纸本)9781728110547

With the advent of the Industrial Internet of Things (IIoT) and Industrial Analytics, numerous application scenarios emerge, where business and mission-critical decisions depend upon large scale analytics of sensor streams. However, very large volumes of data from data streams generated at a high rate pose substantial challenges in providing scalable analytics from existing Database Management Systems (DBMS). While scalability can be provided by high-performance distributed datastores, due to the simple query operations, access to high-level query-based data analytics is usually limited. This work combines high-level query-based data analytics capabilities with high-performance distributed scalability by applying a wrapper-mediator approach. The Amos II extensible main-memory DBMS provides online query processing data analytics engine in front of the MongoDB distributed nosql datastore to support large-scale distributed data analytics over persisted data streams. Thus, the implemented system enables query-based online data stream analytics over persisted data streams stored/logged in distributed nosql datastores.

关键词： nosql datastores MongoDB IIoT Data Streams

来源：评论

学校读者我要写书评

暂无评论

A Big Data Framework for Cloud Monitoring 2

A Big Data Framework for Cloud Monitoring

引用

IEEE/ACM 2nd International Workshop on Big Data Software Engineering (BIGDSE)

作者： Zareian, Saeed Fokaefs, Marios Khazaei, Hamzeh Litoiu, Marin Zhang, Xi York Univ Sch Informat Technol Toronto ON Canada York Univ Dept Elect Engn & Comp Sci Toronto ON Canada Sichuan Univ Coll Comp Sci Chengdu Peoples R China

ISBN: (纸本)9781450341523

Elasticity is a key component of modern cloud environments and monitoring is an essential part of this process. Monitoring demonstrates several challenges including gathering metrics from a variety of layers (infrastructure, platform, application), the need for fast processing of this data to enable efficient elasticity and the proper management of this data in order to facilitate analysis of current and past data and future predictions. In this work, we classify monitoring as a big data problem and propose appropriate solutions in a layered, pluggable and extendable architecture for a monitoring component. More specifically, we propose the use of nosql databases as the back-end and BigQueue as a write buffer to achieve high throughput. Our evaluation shows that our monitoring is capable of achieving response time of a few hundreds of milliseconds for the insertion of hundreds of rows regardless of the underlying nosql database.

关键词： monitoring system cloud applications nosql datastores big data performance analysis

来源：评论

学校读者我要写书评

暂无评论

A Qualitative Comparison of nosql Data Stores

引用

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2019年第2期10卷 330-338页

作者： Kamal, Sarah H. Elazhary, Hanan H. Hassanein, Ehab E. Akhbar Elyom Acad Informat Syst Dept 6th October City Egypt Elect Res Inst Comp & Syst Dept Cairo Egypt Cairo Univ Fac Comp & Informat Informat Syst Dept Cairo Egypt

Due to the proliferation of big data with large volume, velocity, complexity, and distribution among remote servers, it became obvious that traditional relational databases are unsuitable for meeting the requirements of such data. This led to the emergence of a novel technology among organizations and business enterprises;nosql datastores. Today such datastores have become popular alternatives to traditional relational databases, since their schema-less data models can manipulate and handle a huge amount of structured, semi-structured and unstructured data, with high speed and immense distribution. Those data stores are of four basic types, and numerous instances have been developed under each type. This implies the need to understand the differences among them and how to select the most suitable one for any given data. Unfortunately, research efforts in the literature either consider differences from a theoretical point of view (without real use cases), or address performance issues such as speed and storage, which is insufficient to give researchers deep insight into the mapping of a given data structure to a given nosql datastore type. Hence, this paper provides a qualitative comparison among three popular datastores of different types (Redis, Neo4j, and MongoDB) using a real use case of each type, translated to the others. It thus highlights the inherent differences among them, and hence what data structures each of them suits most.

关键词： Document datastores graph datastores key-value datastores MonoDB Neo4j nosql datastores Redis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：