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Offloaded Data Processing Energy Efficiency Evaluation

INFORMATICA 2024年第3期35卷 649-669页

作者： Prokhorenko, Victor Babar, Muhammad Ali Univ Adelaide Adelaide Australia

The growing popularity of mobile and cloud computing raises new challenges related to energy efficiency. This work evaluates four various SQL and nosql database solutions in terms of energy efficiency. Namely, Cassandra, MongoDB, Redis, and MySQL are taken into consideration. This study measures energy efficiency of the chosen data storage solutions on a selected set of physical and virtual computing nodes by leveraging Intel RAPL (Running Average Power Limit) technology. Various database usage scenarios are considered in this evaluation including both local usage and remote offloading. Different workloads are benchmarked through the use of YCSB (Yahoo! Cloud Serving Benchmark) tool. Extensive experimental results show that (i) Redis and MongoDB are more efficient in energy consumption under most usage scenarios, (ii) remote offloading saves energy if the network latency is low and destination CPU is significantly more powerful, and (iii) computationally weaker CPUs may sometimes demonstrate higher energy efficiency in terms of J/ops. An energy efficiency measurement framework is proposed in order to evaluate and compare different database solutions based on the obtained experimental results.

关键词： energy measurement nosql databases SQL database cloud computing edge computing performance

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BIM Big Data Storage in WebVRGIS

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2020年第4期16卷 2566-2573页

作者： Lv, Zhihan Li, Xiaoming Lv, Haibin Xiu, Wenqun Qingdao Univ Sch Data Sci & Software Engn Qingdao 266071 Peoples R China Shenzhen Univ Sch Architecture & Urban Planning Res Inst Smart Cities Shenzhen 518060 Peoples R China Minist Nat Resources North Sea Bur North China Sea Offshore Engn Survey Inst Qingdao 266061 Peoples R China Shenzhen Urban Publ Safety & Technol Inst Ctr Res & Dev Shenzhen 518046 Peoples R China

In the context of big data and the Internet of Things, with the advancement of geospatial data acquisition and retrieval, the volume of available geospatial data is increasing every minute. Thus, new data-management architecture is needed. We proposed a building information model (BIM) big data-storage-management solution with hybrid storage architecture based on web virtual reality geographical information system (WebVRGIS). BIM is associated with the integration of spatial and semantic information on the various stages of urban building. In this paper, based on the spatial distribution characteristics of BIM geospatial big data, a data storage and management model is proposed for BIM geospatial big data management. The architecture primarily includes Not only Structured Query Language (nosql) database and distributed peer-to-peer storage. The evaluation of the proposed storage method is conducted on the same software platform as our previous research about WebVR. The experimental results show that the hybrid storage architecture proposed in this research has a lower response time compared to the traditional relational database in geospatial big data searches. The integration and fusion of BIM big data in WebVRGIS realizes a revolutionary transformation of city information management during a full lifecycle. The system also has great promise for the storage of other geospatial big data, such as traffic data.

关键词： Spatial databases Data models Big Data nosql databases Geospatial analysis Semantics Computer architecture Internet of things building information model (BIM) big data geographical information system (GIS)

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Designing and testing a pool-based evolutionary algorithm

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NATURAL COMPUTING 2013年第2期12卷 149-162页

作者： Merelo, J. J. Mora, A. M. Fernandes, C. M. Esparcia-Alcazar, Anna I. Univ Granada Dept Comp Architecture & Technol ETSIIT & CITIC E-18071 Granada Spain S2 Grp Valencia Spain

This paper focuses on the iterative design of SofEA , an architecture for distributing evolutionary algorithms (EAs) across computer networks in an asynchronous and decentralized way. SofEA is based on a pool architecture implemented on an object store, allowing the asynchronous interaction with which several clients. The fact that each client is autonomous leads to complex behavior, which will be examined in the work, so that the design can be validated, rules of thumb can be extracted, and the limits of scalability can be found. In this paper we advance the design of an asynchronous, fault-tolerant, and hopefully scalable distributed EA based on the object store CouchDB. We do so by iteratively analyzing running time and average evaluations to solutions on increasingly better versions of the algorithm, looking for the best results, at least from the point of view of running time. By doing so, we increase speed almost fourfold, and also decrement the average number of evaluations to solution in some cases. Experiments have shown also which critical parameters have the bigger influence on the performance in this kind of systems: live population size and number of conflicts, with both being influenced by the number of clients and the size of the population block each client handles at a time. These experiments also show that there is a balance between scalability and fault tolerance, with scalability dropping when a certain number of clients is reached;further clients only increase fault tolerance, at least in the configurations we are using in this paper. The paper also shows that experimentation and measurement conform a good methodology for the design of this kind of asynchronous, heterogeneous and distributed systems, where analytic performance prediction is almost impossible.

关键词： Cloud computing Cloud storage Evolutionary algorithms Distributed algorithms nosql databases Key-value stores Complex systems

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Self-tuning Database Systems: A Systematic Literature Review of Automatic Database Schema Design and Tuning

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ACM COMPUTING SURVEYS 2024年第11期56卷 1-37页

作者： Mozaffari, Maryam Dignos, Anton Gamper, Johann Stoerl, Uta Free Univ Bozen Bolzano Bolzano Italy Fernuniv Databases & Informat Syst Hagen Germany

Self-tuning is a feature of autonomic databases that includes the problem of automatic schema design. It aims at providing an optimized schema that increases the overall database performance. While in relational databases automatic schema design focuses on the automated design of the physical schema, in nosql databases all levels of representation are considered: conceptual, logical, and physical. This is mainly because the latter are mostly schema-less and lack a standard schema design procedure as is the case for SQL databases. In this work, we carry out a systematic literature survey on automatic schema design in both SQL and nosql databases. We identify the levels of representation and the methods that are used for the schema design problem, and we present a novel taxonomy to classify and compare different schema design solutions. Our comprehensive analysis demonstrates that, despite substantial progress that has been made, schema design is still a developing field and considerable challenges need to be addressed, notably for nosql databases. We highlight the most important findings from the results of our analysis and identify areas for future research work.

关键词： Data modeling schema design and tuning self-tuning databases nosql databases SQL databases

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Tool for materializing OWL ontologies in a column-oriented database

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SOFTWARE-PRACTICE & EXPERIENCE 2019年第1期49卷 100-119页

作者： Reyes-Alvarez, Liudmila del Mar Roldan-Garcia, Maria Aldana-Montes, Jose F. Univ Malaga Edificio Invest Ada Byron E-29071 Malaga Spain

Big data technologies enable people to store, analyze, and utilize large amounts of complex data effectively. In this context, nosql (Not only Structured Query Language) databases have emerged as the most commonly used infrastructure for handling big Resource Description Framework data. In this paper, we present our proposal to materialize classified OWL (Web Ontology Language) ontologies in a nosql database. This materialization process enables the distributed storage of Resource Description Framework data by exploiting the inherent distribution of the nosql database nodes. Furthermore, this approach supposes the first step toward a novel approach to scalable OWL reasoning, which enables scalable Linked Data reasoning. To validate our proposal, we developed a prototype for a tool that stores an OWL ontology in a Cassandra database following our approach. Finally, we introduce our reasoning strategy to compute the ontology closure using this Cassandra database.

关键词： Linked Data MapReduce framework nosql databases OWL ontologies scalable reasoning

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A Model-Driven Approach to Generate Schemas for Object-Document Mappers

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IEEE ACCESS 2019年 7卷 59126-59142页

作者： Hernandez Chillon, Alberto Sevilla Ruiz, Diego Garcia Molina, Jesus Feliciano Morales, Severino Univ Murcia Fac Comp Sci E-30100 Murcia Spain Autonomous Univ Guerrero Fac Engn Chilpancingo 39087 Mexico

Many actual nosql systems are schemaless, that is, the structure of the data is not defined beforehand in any schema, but it is implicit in the data itself. This characteristic is very convenient when the data structure suffers frequent changes. However, the agility and flexibility achieved is at the cost of losing some important benefits, such as 1) assuring that the data stored and retrieved fits the database schema;2) some database utilities require to know the schema, and;3) schema visualization helps developers to write better code. In previous work, we proposed a model-based reverse engineering approach to infer schema models from nosql data. Model-driven engineering (MDE) techniques can be used to take advantage of extracted models with different purposes, such as schema visualization or automatic code generation. Here, in this paper, we present an MDE solution to automate the usage of Object-nosql mappers when the database already exists. We will focus on mappers that are available for document systems (Object-Document mappers, ODMs), but the proposed approach is mapper-independent. These mappers are emerging to provide similar functionality to Object-Relational mappers: they are in charge of the mapping of objects into nosql data (documents in the case of ODMs) for object-oriented applications. We show how schemas and other artifacts (e.g. validators and indexes) for ODMs can be automatically generated from inferred schemas. The solution consists of a two-step model transformation chain, where an intermediate model is generated to ease the code generation. We have applied our approach for two popular ODMs: Mongoose and Morphia and validated it with the StackOverflow dataset.

关键词： Object-document mappers nosql databases Mongoose Morphia code generation model-driven engineering model-based solution nosql data engineering

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GridMesa: A nosql-based big spatial data management system with an adaptive grid approximation model

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2024年 155卷 324-339页

作者： Yang, Xiangyang Guan, Xuefeng Pang, Zhaoxing Kui, Xing Wu, Huayi Wuhan Univ State Key Lab Informat Engn Surveying Mapping & Re Wuhan 430079 Peoples R China

Due to the urgent demand for managing massive spatial data, various spatial data management systems built on distributed nosql databases have emerged. However, current systems usually employ coarse MBR to approximate spatial objects in order to accelerate spatial operations;this leads to numerous mismatched spatial objects entering the time-consuming refinement process and thus limits retrieval efficiency. Moreover, since spatial objects vary in size and shape, their index levels will exhibit distinct differences when building grid -based spatial indexes. However, few systems consider these distribution differences, which results in many invalid query windows during the query process and exerts high pressure on the underlying parallelism. To overcome these issues, we propose a grid -based management system for massive spatial data, named GridMesa. First, within GridMesa, an adaptive grid -based approximation model for spatial objects (called GridAM) is proposed that can accelerate the underlying spatial computations. The cost model of Grid -AM is further analyzed to estimate the adaptive approximation granularity and thereby balance the filtering and refinement costs. Second, GridMesa incorporates a nosql-based storage scheme that integrates Grid -AM with HBase. The storage scheme also includes a novel secondary index for recording the distribution of spatial objects, which helps improve the quality of query windows. Finally, on the top of this storage scheme, GridMesa also implements efficient query algorithms to support data retrieval, including the range and kNN queries. Extensive experiments with real -world datasets demonstrate that GridMesa outperforms available popular nosql-based systems, e.g., GeoMesa, GeoWave, etc.

关键词： Spatial data management nosql databases Grid approximation Spatial indexes Spatial computation

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A partitioning framework for Cassandra nosql database using Rendezvous hashing

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JOURNAL OF SUPERCOMPUTING 2017年第10期73卷 4444-4465页

作者： Elghamrawy, Sally M. Hassanien, Aboul Ella MISR Higher Inst Engn & Technol Mansoura Egypt Cairo Univ Fac Comp & Informat Giza Egypt SRGE Giza Egypt

Due to the gradual expansion in data volume used in social networks and cloud computing, the term "Big data" has appeared with its challenges to store the immense datasets. Many tools and algorithms appeared to handle the challenges of storing big data. nosql databases, such as Cassandra and MongoDB, are designed with a novel data management system that can handle and process huge volumes of data. Partitioning data in nosql databases is considered one of the critical challenges in database design. In this paper, a MapReduce Rendezvous Hashing-Based Virtual Hierarchies (MR-RHVH) framework is proposed for scalable partitioning of Cassandra nosql database. The MapReduce framework is used to implement MR-RHVH on Cassandra to enhance its performance in highly distributed environments. MR-RHVH distributes the nodes to rendezvous regions based on a proposed Adopted Virtual Hierarchies strategy. Each region is responsible for a set of nodes. In addition, a proposed bloom filter evaluator is used to ensure the accurate allocation of keys to nodes in each region. Moreover, a number of experiments were performed to evaluate the performance of MR-RHVH framework, using YCSB for database benchmarking. The results show high scalability rate and less time consuming for MR-RHVH framework over different recent systems.

关键词： Cassandra Rendezvous hashing Consistent hashing MapReduce nosql databases Partitioning

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Information Leakage in Cloud Data Warehouses

IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING

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IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING 2020年第2期5卷 192-203页

作者： Ahmadian, Mohammad Marinescu, Dan C. Univ Cent Florida Dept Comp Sci Orlando FL 32816 USA

Information leakage is the inadvertent disclosure of sensitive information through correlation of records from several databases/collections of a cloud data warehouse. Malicious insiders pose a serious threat to cloud data security and this justifies the focus on information leakage due to rogue employees or to outsiders using the credentials of legitimate employees. The discussion in this paper is restricted to nosql databases with a flexible schema. Data encryption can reduce information leakage, but it is impractical to encrypt large databases and/or all fields of database documents. Encryption limits the operations that can be carried on the data in a database. It is thus, critical to distinguish sensitive documents in a data warehouse and concentrate on efforts to protect them. The capacity of a leakage channel introduced in this work quantifies the intuitively obvious means to trigger alarms when an insider attacker uses excessive computer resources to correlate information in multiple databases. The Sensitivity Analysis based on Data Sampling (SADS) introduced in this paper balances the trade-offs between higher efficiency in identifying the risks posed by information leakage and the accuracy of the results obtained by sampling very large collections of documents. The paper reports on experiments assessing the effectiveness of SADS and the use of selective disinformation to limit information leakage. Cloud services identifying sensitive records and reducing the risk of information leakage are also discussed.

关键词： Encryption Cloud computing Data warehouses Sensitivity analysis nosql databases Database as a service information leakage capacity of a leakage channel sensitivity analysis approximate query processing biased sampling cross-correlation estimation

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Managing Data in Healthcare Information Systems: Many Models, One Solution

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COMPUTER 2015年第3期48卷 52-59页

作者： Kaur, Karamjit Rani, Rinkle Thapar Univ Dept Comp Sci & Engn Patiala 147004 Punjab India

Because healthcare data comes from multiple, vastly different sources, databases must adopt a range of models to process and store it. A polyglot-persistent framework combines relational, graph, and document data mode... 详细信息

关键词： SQL data models document handling electronic health records health care relational databases nosql data stores data management data processing data storage document data model graph data model healthcare data healthcare information systems polyglot-persistent framework relational data model relational data store Big data Data models Database languages Knowledge based systems Medical information processing Medical services Relational databases MongoDB Neo4j nosql databases big data data management healthcare data management

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