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Springer International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS)

作者： Wahid, Abdul Kashyap, Kanupriya Natl Inst Technol Patna Dept Comp Sci & Engn Patna 800005 Bihar India Natl Inst Technol Kurukshetra Dept Comp Engn Kurukshetra 136119 Haryana India

ISBN: (纸本)9789811319518;9789811319501

In big data environment, apache Cassandra is a distributed database which offers very high availability. It is an open source database system and is designed to manage large transactional data across various server globally. Main feature of Cassandra is to provide high availability and very high fault tolerance, decentralized database system with zero downtime. A traditional relational database (RDBMSs) is used to storing data for various applications from many years, but some changes are required because application must be scale to levels that were unimaginable. But only scaling is not the main concern of changes, companies are also requires such type of applications that always available and running fast where RDBMS database fail. Apache Cassandra is a fully distributed database that has such type of architecture where it handles extreme data velocity with highly availability, scalability and recovers from fault tolerance easily. In Cassandra architecture, there is no master node to handle all the nodes in the ring or network. The data distribution among nodes in this architecture is in equal probation. Cassandra creates such type of environment where an entire datacenter can lose but still perform as if nothing happened. This paper provides a brief idea about Cassandra.

关键词： distributed database Cassandra Decentralized Fault tolerant

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SFDDM: A Secure distributed database Management in Combined Fog-to-Cloud Systems 24

SFDDM: A Secure Distributed Database Management in Combined ...

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24th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (IEEE CAMAD)

作者： Sengupta, Souvik Kahvazadeh, Sarang Masip-Bruin, Xavi Garcia, Jordi UPC BarcelonaTech CRAAX Lab Dept Comp Architecture DAC Vilanova I La Geltru Spain

ISBN: (纸本)9781728110165

Technological revolutions have greatly increased the use of IoT devices for our daily life. Driving the fact that everything surrounding us is getting connected what turns into an unstoppable increase in the amount of data produced. This data represents the state of diverse environmental events and helps to control a large set of distinct activities. So, accurate and secure management of this data is essential for any computing platform. Moreover, in order to provide real-time services in a distributed system (i.e., smart city), the data should be properly and securely managed. It is well known that shifting these tasks to the edge (i.e., near to the end users), highly facilitates these two objectives. The recently proposed Fog-to-Cloud (F2C) model is intended to enable data processing near to the edge, which helps to get better latency-sensitive services. However, some challenges remain to accurately and securely manage this data over the system, mainly due to the distributed F2C nature. Thus, considering these facts and challenges, in this paper we propose an architectural solution aimed at building a secure distributed database for F2C systems. Then, considering a real-case scenario, we perform some tests to measure the performance of our proposing schema. Finally, by comparing the performance between traditional cloud, fog/edge based execution model and our proposing SFDDM, we validate the effectiveness of our proposing schema.

关键词： Fog-to-Cloud (F2C) distributed database Internet-of-Thing (IoT) Security and Privacy

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AstroServ: A distributed database for Serving Large-Scale Full Life-Cycle Astronomical Data 1

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1st International Conference on Big Scientific Data Management (BigSDM)

作者： Yang, Chen Meng, Xiaofeng Due, Zhihui Qiu, JiaMing Liang, Kenan Du, Yongjie Duan, Zhiqiang Ma, Xiaobin Fang, Zhijian Renmin Univ Sch Informat Beijing Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China Shandong Univ Sch Comp Sci & Technol Jinan Peoples R China

ISBN: (数字)9783030280611

ISBN: (纸本)9783030280611;9783030280604

In time-domain astronomy, STLF (Short-Timescale and Large Field-of-view) sky survey is the latest way of sky observation. Compared to traditional sky survey who can only find astronomical phenomena, STLF sky survey can even reveal how short astronomical phenomena evolve. The difference does not only lead the new survey data but also the new analysis style. It requires that database behind STLF sky survey should support continuous analysis on data streaming, real-time analysis on short-term data and complex analysis on long-term historical data. In addition, both insertion and query latencies have strict requirements to ensure that scientific phenomena can be discovered. However, the existing databases cannot support our scenario. In this paper, we propose AstroServ, a distributed system for analysis and management of large-scale and full life-cycle astronomical data. AstroServ's core components include three data service layers and a query engine. Each data service layer serves for a specific time period of data and query engine can provide the uniform analysis interface on different data. In addition, we also provide many applications including interactive analysis interface and data mining tool to help scientists efficiently use data. The experimental results show that AstroServ can meet the strict performance requirements and the good recognition accuracy.

关键词： distributed database Astronomical data Full life-cycle

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DDQO: An Algorithm for distributed database Query Optimization 19

DDQO: An Algorithm for Distributed Database Query Optimizati...

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4th International Conference on Big Data and Computing (ICBDC)

作者： Dong, Liang Chu, AnKang Liu, Fengkui Beijing Univ Technol Future Network Innovat Ctr Beijing Peoples R China China Elect Power Res Inst Beijing Peoples R China

ISBN: (纸本)9781450362788

With the continuous development of modern information technology, the use of scientific and technological literature data is increasing, among which semi-structured data accounts for a large proportion, and it has the characteristics of large quantity and extensive growth. Therefore, distributed database has been widely applied. At the same time, the optimization algorithm for distributed database becomes the research hot spot. However, when using optimization algorithm to solve problems, researchers have not fully solved the limitations of optimization algorithm. In order to improve the retrieval speed of distributed database, this paper combined with the global optimization ability of ant colony algorithm and the local optimization ability of simulated annealing algorithm, the DDQO algorithm is proposed. At the same time, this paper conducted a control experimental on the DDQO algorithm. Experimental results show that the DDQO algorithm is superior to ant colony algorithm and simulated annealing algorithm, it increase the query speed of distributed database by 24%.

关键词： distributed database rapid retrieval ant colony algorithm simulated annealing algorithm

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Join query optimization in the distributed database system using an artificial bee colony algorithm and genetic operators

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2019年第17期31卷 e5218-e5218页

作者： Panahi, Vahideh Navimipour, Nima Jafari Islamic Azad Univ Tabriz Branch Dept Comp Engn Tabriz Iran

As the main factor in the distributed database systems, query optimization is aimed at finding an optimal execution plan to reduce the runtime. In such systems, because of the repeated relations on various sites, the query optimization is very challenging. Moreover, the query optimization issue with large-scale distributed databases is an NP-hard problem. Therefore, in this paper, an Artificial Bee Colony Algorithm based on Genetic Operators (ABC-GO) is proposed to find a solution to join the query optimization problems in the distributed database systems. The ABC algorithm has the global-local search capabilities and genetic operators to create new candidate solutions for improving the performance of the ABC algorithm. The obtained results have shown that the cost of the query evaluation is minimized and the quality of Top-K query plans is improved for a given distributed query. Moreover, this method decreases the overhead. However, it needs a longer execution time.

关键词： artificial bee colony optimization distributed database genetic operator query plan optimization

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An Enhanced University Registration Model Using distributed database Schema

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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2019年第7期13卷 3533-3549页

作者： Maabreh, Khaled Saleh Zarqa Univ Fac Informat Technol Zarqa Jordan

A big database utilizes the establishing network technology, and it became an emerging trend in the computing field. Therefore, there is a necessity for an optimal and effective data distribution approach to deal with this trend. This research presents the practical perspective of designing and implementing distributed database features. The proposed system has been establishing the satisfying, reliable, scalable, and standardized use of information. Furthermore, the proposed scheme reduces the vast and recurring efforts for designing an individual system for each university, as well as it is effectively participating in solving the course equivalence problem. The empirical finding in this study shows the superiority of the distributed system performance based on the average response time and the average waiting time than the centralized system. The system throughput also overcomes the centralized system because of data distribution and replication. Therefore, the analyzed data shows that the centralized system thrashes when the workload exceeds 60%, while the distributed system becomes thrashes after 81% workload.

关键词： Availability Cloud Computing distributed database Fragmentation Registration Reliability

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Optimization algorithm of redundant data classification in distributed database

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JOURNAL OF DISCRETE MATHEMATICAL SCIENCES & CRYPTOGRAPHY 2018年第2期21卷 439-444页

作者： Chen, Dong Sichuan Post & Telecommun Coll Comp Sci Dept Chengdu 610067 Sichuan Peoples R China

Large-scale distributed database includes a large number of redundant data, which will lead to low correlation between the data, resulting in lower network efficiency. This paper proposes a method for optimizing redundant data classification in distributed databases. Firstly, the redundant data attributes are extracted to provide the accurate data base for the classification of redundant data. Then the optimal classification threshold is obtained according to the weight probability theory, and the redundant data classification is realized. The experimental results show that the algorithm can improve the accuracy of classification and achieve satisfactory results.

关键词： distributed database Big data Redundant data Classification technology

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The Application of distributed database on Spectrum Big Data 4th

The Application of Distributed Database on Spectrum Big Data

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4th International Conference on Cloud Computing and Security (ICCCS)

作者： Chen, Zhenjia Zhang, Yonghui Guo, Xia Hainan Univ Coll Informat Sci & Technol Haikou 570228 Hainan Peoples R China

ISBN: (纸本)9783030000097;9783030000080

The management and utilization of spectrum resources has always been an important issue. The data of radio signals from the time domain, frequency domain, and space domain is tremendous. The current spectrum databases are mainly centralized and the disaster recovery capacity of centralized database is insufficient. In the future, cognitive radio network (CRN) will be the development trend of mobile communications. The access to the spectrum database by a large number of cognitive radio (CR) terminals and the uploading of spectrum detection data by the spectrum detection terminal in real time will exert tremendous pressure on CRN. This paper proposes use of distributed spectrum databases instead of centralized database architectures in the spectrum big data to improve the fault tolerance of spectrum databases. Multi-node collaborative electromagnetic detection method with source parameter is proposed to replace the traditional wide-band energy detection method. The traditional spectrum database stores spectrum data with energy values, and the redundancy of data is really high. We propose to store the instantaneous parameters of signal source with the structure of blockchain. The timestamp is used as the link ID of the block to connect each block end-to-end, and a distributed spectrum database is established. With the timestamp as a unique identifier, the nodes locally interact with real-time detection data. Secondary user (SU) achieve the complete electromagnetic spectrum data by access each node. SUs can analyze the electromagnetic spectrum environment, and formulate appropriate strategies for rapid dynamic spectrum access (DSA).

关键词： distributed database Spectrum big data Cooperative detection Blockchain Spectrum visualization

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GraphChain - A distributed database with Explicit Semantics and Chained RDF Graphs 18

GraphChain - A Distributed Database with Explicit Semantics ...

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27th World Wide Web (WWW) Conference

作者： Sopek, Mirek Gradzki, Przemyslaw Kosowski, Witold Kuzinski, Dominik Trojczak, Rafal Trypuz, Robert MakoLab SA Lodz Poland DC Lublin MakoLab SA R&D Team Lublin Poland MakoLab SA R&D Team Lublin Poland Fac Philosophy KUL Lublin Poland

ISBN: (纸本)9781450356404

In this paper we present a new idea of creating a Blockchain compliant distributed database which exposes its data with explicit semantics, is easily and natively accessible, and which applies Blockchain securitization mechanisms to the RDF graph data model directly, without additional packaging or specific serialisation. Essentially, the resulting database forms the linked chain of named RDF graphs and is given a name: GraphChain. Such graphs can then be published with the help of any standard mechanisms using triplestores or as linked data objects accessible via standard web mechanisms using the HTTP protocol to make them available on the web. They can also be easily queried using techniques like SPARQL or methods typical to available RDF graphs frameworks (like rdflib, Apache Jena, RDF4J, OWL API, RDF HDT, dotnetRDF and others). The GraphChain concept comes with its own, OWL-compliant ontology that defines all the structural, invariant elements of the GraphChain and defines their basic semantics. The paper describes also a few simple, prototypical GraphChain implementations with examples created using Java, .NET/C# and JavaScript/*** frameworks.

关键词： distributed database semantic blockchain GraphChain linked data

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Construction of distributed database Model Of Mass Sports Data of College Based on Cloud Computing 2018

Construction of Distributed Database Model Of Mass Sports Da...

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2nd International Conference on Education and E-Learning (ICEEL)

作者： Zhang, Fan Nanjing Forest Police Coll 28 Wen Lan Rd Nanjing 210023 Jiangsu Peoples R China

ISBN: (纸本)9781450365772

This paper studies the construction and data mining of college sports database model. Aiming at the problems of low parallelism and unsystematic of current sports data processing, this paper proposes a mass of college sports data modeling and analysis method based on cloud computing to improve the management and analysis ability of college sports information, and constructs a distributed database model of college sports data. In the cloud computing environment, the database access model is designed, and the K-means data clustering method is used to mine the reliability of sports data, so as to realize the optimal information scheduling and retrieval analysis of college sports data. The simulation results show that the model has good real-time performance, high accuracy and reliability, and has a certain application prospect.

关键词： Sports performances Cloud Computing distributed database Model building

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