检索结果-内蒙古大学图书馆

An evaluation of relational and NoSQL distributed databases on a low-power cluster

JOURNAL OF SUPERCOMPUTING 2023年第12期79卷 13402-13420页

作者： da Silva, Lucas Ferreira Lima, Joao V. F. Univ Fed Santa Maria Grad Program Comp Sci Santa Maria RS Brazil

The constant growth of social media, unconventional web technologies, mobile applications, and Internet of Things (IoT) devices create challenges for cloud data systems in order to support huge datasets and very high request rates. NoSQL databases, such as Cassandra and HBase, and relational SQL databases with replication, such as Citus/PostgreSQL, have been used to increase horizontal scalability and high availability of data store systems. In this paper, we evaluated three distributed databases on a low-power low-cost cluster of commodity Single-Board Computers (SBC): relational Citus/PostgreSQL and NoSQL databases Cassandra and HBase. The cluster has 15 Raspberry Pi 3 nodes with Docker Swarm orchestration tool for service deployment and ingress load balancing over SBCs. We believe that a low-cost SBC cluster can support cloud serving goals such as scale-out, elasticity, and high availability. Experimental results clearly demonstrated that there is a trade-off between performance and replication, which provides availability and partition tolerance. Besides, both properties are essential in the context of distributed systems with low-power boards. Cassandra attained better results with its consistency levels specified by the client. Both Citus and HBase enable consistency but it penalizes performance as the number of replicas increases.

关键词： distributed databases Raspberry Pi Low-power Single-Board Computers Docker swarm Big data NoSQL

来源：评论

学校读者我要写书评

暂无评论

Resource Utilization of distributed databases in Edge-Cloud Environment

引用

IEEE INTERNET OF THINGS JOURNAL 2023年第11期10卷 9423-9437页

作者： Mansouri, Yaser Prokhorenko, Victor Ullah, Faheem Babar, Muhammad Ali Univ Adelaide Ctr Res Engn Software Technol Sch Comp Sci Adelaide SA 5005 Australia

A benchmark study of modern distributed databases (DDBs) (e.g., Cassandra, MongoDB, Redis, and MySQL) is an important source of information for selecting the right technology for managing data in edge-cloud deployments. While most of the existing studies have investigated the performance and scalability of DDBs in cloud computing, there is a lack of focus on resource utilization (e.g., energy, bandwidth, and storage consumption) of workload offloading for DDBs deployed in edge-cloud environments. For this purpose, we conducted experiments on various physical and virtualized computing nodes, including variously powered servers, Raspberry Pi, and hybrid cloud (OpenStack and Azure). Our extensive experimental results reveal insights into which database under which offloading scenario is more efficient in terms of energy, bandwidth, and storage consumption.

关键词： databases distributed databases Servers Cloud computing Bandwidth Task analysis Time factors cloud computing distributed databases (DDBs) edge computing energy storage

来源：评论

学校读者我要写书评

暂无评论

Column generation-based algorithm for fragment allocation: minimizing query splitting in distributed databases

引用

INFORMATION TECHNOLOGY & MANAGEMENT 2024年 1-14页

作者： Amiri, Ali Oklahoma State Univ Spears Sch Business Dept MSIS Stillwater OK 74078 USA

This paper focuses on the fragment allocation problem in distributed databases and proposes an approach that minimizes query splitting. Query splitting occurs when a query has to access multiple servers to retrieve the fragments it needs, resulting in reduced system performance. The objective of minimizing query splitting is important because it captures many factors that affect the performance of the database, such as reducing response time and cost. The paper presents a column generation-based algorithm to solve the fragment allocation problem, which requires less fine-tuning of its parameters and outperforms the IP approach implemented by CPLEX in terms of the number of queries split and execution time. The approach and algorithm offer practical solutions to optimize the design of a distributed database system. The paper's contribution is significant as it fills the gap in the literature by offering a novel approach that minimizes query splitting, which can serve as a proxy for achieving a combination of other objectives such as minimizing costs, reducing response time, and balancing server workloads.

关键词： distributed databases Fragment allocation Query splitting Integer programming Column generation

来源：评论

学校读者我要写书评

暂无评论

Checking causal consistency of distributed databases

引用

COMPUTING 2022年第10期104卷 2181-2201页

作者： Zennou, Rachid Biswas, Ranadeep Bouajjani, Ahmed Enea, Constantin Erradi, Mohammed Mohammed V Univ ENSIAS Rabat Morocco Univ Paris CNRS IRIF F-75013 Paris France

The CAP Theorem shows that (strong) consistency, availability, and partition tolerance are impossible to be ensured together. Causal consistency is one of the weak consistency models that can be implemented to ensure availability and partition tolerance in distributed systems. In this work, we propose a tool to check automatically the conformance of distributed/concurrent systems executions to causal consistency models. Our approach consists in reducing the problem of checking if an execution is causally consistent to solving datalog queries. The reduction is based on complete characterizations of the executions violating causal consistency in terms of the existence of cycles in suitably defined relations between the operations occurring in these executions. We have implemented the reduction in a testing tool for distributed databases, and carried out several experiments on real case studies, showing the efficiency of the suggested approach.

关键词： Causal consistency Causal memory Causal convergence distributed databases Formal verification Testing

来源：评论

学校读者我要写书评

暂无评论

Collusion-resistant protocols for private processing of aggregated queries in distributed databases

引用

distributed AND PARALLEL databases 2021年第1期39卷 97-127页

作者： Rylands, Leanne Seberry, Jennifer Yi, Xun Kelarev, Andrei Ryan, Joe Lin, Yuqing Western Sydney Univ Ctr Res Math & Data Sci Locked Bay 1797 Penrith NSW 2751 Australia Univ Wollongong Sch Comp & Informat Technol Northfields Ave Wollongong NSW 2522 Australia RMIT Univ Sch Sci GPO Box 2476 Melbourne Vic 3001 Australia Univ Newcastle Sch Elect Engn & Comp Callaghan NSW 2308 Australia

Private processing of database queries protects the confidentiality of sensitive data when queries are answered. It is important to design collusion-resistant protocols ensuring that privacy remains protected even when a certain number of honest-but-curious participants collude to share their knowledge in order to gain unauthorised access to sensitive information. A novel setting arises when aggregated queries need to be answered for a large distributed database, but legal requirements or commercial interests forbid making access to records in each subdatabase available to other counterparts. For example, a very large number of medical records may be stored in a distributed database, which is a union of several separate databases from different hospitals, or even from different countries. The present article introduces and investigates two protocols for collusion-resistant private processing of aggregated queries in this novel setting: Accelerated Multi-round Iterative Protocol (AMIP) and Restricted Multi-round Iterative Protocol (RMIP). We define a large collection of query functions and show that AMIP and RMIP protocols can answer all queries in this collection. Our experiments demonstrate that the AMIP protocol outperforms all other applicable algorithms, and this achievement is especially significant in terms of the communication complexity.

关键词： Aggregated queries Multi-round iterative protocol Privacy protection Private query processing distributed databases

来源：评论

学校读者我要写书评

暂无评论

PatchIndex: exploiting approximate constraints in distributed databases

引用

distributed AND PARALLEL databases 2021年第3期39卷 833-853页

作者： Klaebe, Steffen Sattler, Kai-Uwe Baumann, Stephan TU Ilmenau Ilmenau Germany Actian Germany GmbH Ilmenau Germany

Cloud data warehouse systems lower the barrier to access data analytics. These applications often lack a database administrator and integrate data from various sources, potentially leading to data not satisfying strict constraints. Automatic schema optimization in self-managing databases is difficult in these environments without prior data cleaning steps. In this paper, we focus on constraint discovery as a subtask of schema optimization. Perfect constraints might not exist in these unclean datasets due to a small set of values violating the constraints. Therefore, we introduce the concept of a generic PatchIndex structure, which handles exceptions to given constraints and enables database systems to define these approximate constraints. We apply the concept to the environment of distributed databases, providing parallel index creation approaches and optimization techniques for parallel queries using PatchIndexes. Furthermore, we describe heuristics for automatic discovery of PatchIndex candidate columns and prove the performance benefit of using PatchIndexes in our evaluation.

关键词： Self-managing databases distributed databases Schema refinement Approximate constraints Uniqueness Patch processing

来源：评论

学校读者我要写书评

暂无评论

Benchmarking Consistency Levels of Cloud-distributed NoSQL databases Using YCSB

引用

IEEE ACCESS 2025年 13卷 63428-63438页

作者： Ferreira, Saulo Mendonca, Julio Nogueira, Bruno Tiengo, Willy Andrade, Ermeson Fed Rural Univ Pernambuco UFRPE Dept Comp BR-52171900 Recife PE Brazil Univ Luxembourg Interdisciplinary Ctr Secur Reliabil & Trust SnT L-4365 Esch Sur Alzette Luxembourg Univ Fed Alagoas Inst Comp BR-57260000 Maceio Brazil

distributed database systems offer scalability and fault tolerance by replicating databases across geographically dispersed nodes. This redundancy aims to ensure data availability even during failures and allows for backups in case of disasters. However, maintaining strong data consistency, where all nodes reflect the latest data simultaneously, becomes a challenge in such geographically distributed setups since database systems need to prioritize availability or performance over strong data consistency. This study examines how different data consistency configurations affect the performance of popular NoSQL (Not only SQL) databases, namely Cassandra, MongoDB, and Redis, in a multi-region cloud environment. We adopt the Yahoo! Cloud Serving Benchmark (YCSB) tool to simulate various workloads, measure performance metrics, and compare the results. Our findings reveal significant performance degradation associated with strong data consistency configurations. For instance, in Cassandra, the number of writing/reading operations processed per second can decrease by up to 95% for specific workloads. Similarly, enforcing strong data consistency in Redis can result in execution times that are over 20 times slower on writing/reading operations.

关键词： NoSQL databases databases distributed databases Database systems Benchmark testing Cloud computing Time factors Runtime Relational databases Redundancy Database NoSQL cloud benchmarking

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Swarm Intelligence Model for Efficient Query Optimization in distributed databases Using Genetic and Ant Colony Algorithms

A Hybrid Swarm Intelligence Model for Efficient Query Optimi...

引用

Intelligent Control, Computing and Communications (IC3), International Conference on

作者： Nemala Jayasri Santosh Kumar B Navdeep Singh Ajeet Singh Taqi Mohammed Khattab Al-Rubaye Mallikarjuna Rao Department of CSE-AI&ML MLR Institute of Technology Hyderabad Telangana India Department of Computer Science Engineering New Horizon College of Engineering Bangalore India Lovely Professional University Phagwara India Department of Electrical Electronics & Communication Engineering Galgotias university Gerater Noida Uttar Pradesh Department of Medical Laboratory Technology College of Medical Technologies The Islamic University Najaf Iraq Department of CSE GRIET Bachupally Hyderabad Telangana India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

Optimisation of queries in distributed databases is more imperative to enhance the processing rate and use of resources with limited computational abilities. This work presents a novel GA-ACO hybrid swarm intelligence model to address the query optimization problem. The optimization effort of the proposed model starts with GA for an initial population of probable paths for query execution which uses the concept of evolution to select diverse solutions. After that, ACO strengthens this set by the application of pheromone-based reinforcement that allows adjusting of a query paths toward the best solution or its approximation with the following number values. In this way the enhancement of the convergence rates and the scalability of the proposed solution when distributed databases are used can be explained. The model was tested with artificial query logs with DEAP being used for the implementation of the genetic algorithm while ant colony operations were implemented using Python built ACO libraries. Performance analysis shows the success of the developed model in decreasing query response time as follows: This essentially complex hybrid mechanism shows potential for future use in other areas with large data sets and efficient query handling.

关键词： Costs Query processing Computational modeling Scalability distributed databases Time factors Particle swarm optimization Optimization Genetic algorithms Load modeling

来源：评论

学校读者我要写书评

暂无评论

Conan: Uncover Consensus Issues in distributed databases Using Fuzzing-Driven Fault Injection

Conan: Uncover Consensus Issues in Distributed Databases Usi...

引用

IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Haojia Huang Pengfei Chen Guangba Yu Haiyu Huang Jia Chang Jun Li Jian Han Sun Yat-sen University Huawei

ISBN: (数字)9798331535100

ISBN: (纸本)9798331535117

Consensus is critical for distributed databases as it ensures the consistency of states across nodes, reinforcing the robustness of the overall system. However, faults related to the consensus protocols such as Paxos can lead to serious issues in distributed databases. Such consensus issues impact the correctness and availability of these databases. Therefore, to automatically uncover consensus issues in distributed databases, we propose Conan, a framework designed with fuzzing-driven fault injection. Conan applies a state-guided fuzzing algorithm to effectively explore the fault search space. Moreover, Conan employs hybrid fault sequences that combines fine-grained message-level faults and coarse-grained system-level faults to enhance fault injection. We implement and evaluate Conan on 3 widely-used distributed databases, including etcd, rqlite and openGauss. Finally, Conan has successfully uncovered previously unknown consensus issues, some of which are not detected by existing approaches.

关键词： distributed databases Fuzzing Software Robustness Consensus protocol

来源：评论

学校读者我要写书评

暂无评论

Comparison Between Centralized and distributed databases in IP Multimedia Subsystem

Comparison Between Centralized and Distributed Databases in ...

引用

International Symposium on Communications and Information Technologies (ISCIT)

作者： Tuan Duc Ninh Linh Duc Nguyen Hieu Minh Tran Minh Van Nguyen Vuong Van Ngo Viettel High Tech Viettel Group Hanoi Vietnam

ISBN: (数字)9798350353952

ISBN: (纸本)9798350353969

The IP Multimedia Subsystem (IMS) refers to the standard for a telecommunication system that controls multimedia services accessing different networks. IMS is integrated in both 4G and 5G networks to enable packet-switched voice calls service. The design of the IMS system always needs to be completed before developing any functions of the system. Choosing of database model is an important part of designing the system, and there are some models of database implementation, such as centralized databases and distributed databases. Moreover, both centralized and distributed databases have some advantages and drawbacks. Each type of database requires different techniques to store and search the users' information. The database implementation and these techniques are described in detail in the manuscript. Besides, simulation of each database implementation is also conducted to evaluate the databases' performance. With the performance comparison between centralized and distributed databases, the IMS system can be optimized by choosing a suitable database model.

关键词： 5G mobile communication distributed databases Multimedia databases Control systems Information and communication technology Multimedia communication IP networks Standards

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：