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Journal articles on the topic 'Distributed transaction processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Daniels, Dean S., Alfred Z. Spector, and Dean S. Thompson. "Distributed logging for transaction processing." ACM SIGMOD Record 16, no. 3 (December 1987): 82–96. http://dx.doi.org/10.1145/38714.38728.

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2

Jing, Changhong, Wenjie Liu, Jintao Gao, and Ouya Pei. "Research and implementation of HTAP for distributed database." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 39, no. 2 (April 2021): 430–38. http://dx.doi.org/10.1051/jnwpu/20213920430.

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Data processing can be roughly divided into two categories, online transaction processing OLTP(on-line transaction processing) and online analytical processing OLAP(on-line analytical processing). OLTP is the main application of traditional relational databases, and it is some basic daily transaction processing, such as bank pipeline transactions and so on. OLAP is the main application of the data warehouse system, it supports some more complex data analysis operations, focuses on decision support, and provides popular and intuitive analysis results. As the amount of data processed by enterprises continues to increase, distributed databases have gradually replaced stand-alone databases and become the mainstream of applications. However, the current business supported by distributed databases is mainly based on OLTP applications, lacking OLAP implementation. This paper proposes an implementation method of HTAP for distributed database CBase, which provides an implementation method of OLAP analysis for CBase, and can easily deal with data analysis of large amounts of data.

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3

Kommareddy, Manjula, and Johnny Wong. "Non-blocking distributed transaction processing system." Journal of Systems and Software 54, no. 1 (September 2000): 65–76. http://dx.doi.org/10.1016/s0164-1212(00)00053-4.

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4

Ravoor, Suresh B., and Johnny S. K. Wong. "Multithreaded transaction processing in distributed systems." Journal of Systems and Software 38, no. 2 (August 1997): 107–17. http://dx.doi.org/10.1016/s0164-1212(96)00114-8.

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5

Banks, Richard, Peter Furniss, Klaus Heien, and H. Rüdiger Wiehle. "OSI distributed transaction processing commitment optimizations." ACM SIGCOMM Computer Communication Review 28, no. 5 (October 1998): 61–75. http://dx.doi.org/10.1145/303297.303308.

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6

Zamanian, Erfan, Julian Shun, Carsten Binnig, and Tim Kraska. "Chiller." ACM SIGMOD Record 50, no. 1 (June 15, 2021): 15–22. http://dx.doi.org/10.1145/3471485.3471490.

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Distributed transactions on high-overhead TCP/IP-based networks were conventionally considered to be prohibitively expensive. In fact, the primary goal of existing partitioning schemes is to minimize the number of cross-partition transactions. However, with the new generation of fast RDMAenabled networks, this assumption is no longer valid. In this paper, we first make the case that the new bottleneck which hinders truly scalable transaction processing in modern RDMA-enabled databases is data contention, and that optimizing for data contention leads to different partitioning layouts than optimizing for the number of distributed transactions. We then present Chiller, a new approach to data partitioning and transaction execution, which aims to minimize data contention for both local and distributed transactions.

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7

Mills, John A. "Large scale interoperability and distributed transaction processing." Journal of Systems Integration 3, no. 3-4 (September 1993): 351–69. http://dx.doi.org/10.1007/bf01975520.

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8

Mafla, E., and B. Bhargava. "Communication facilities for distributed transaction-processing systems." Computer 24, no. 8 (August 1991): 61–66. http://dx.doi.org/10.1109/2.84878.

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9

Chen, Graham. "Distributed transaction processing standards and their applications." Computer Standards & Interfaces 17, no. 4 (September 1995): 363–73. http://dx.doi.org/10.1016/0920-5489(95)00005-f.

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10

Sherman, Mark. "Architecture of the Encina distributed transaction processing family." ACM SIGMOD Record 22, no. 2 (June 1993): 460–63. http://dx.doi.org/10.1145/170036.170136.

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11

Obermeier, Sebastian, Stefan Böttcher, Martin Hett, Panos K. Chrysanthis, and George Samaras. "Blocking reduction for distributed transaction processing within MANETs." Distributed and Parallel Databases 25, no. 3 (February 24, 2009): 165–92. http://dx.doi.org/10.1007/s10619-009-7033-z.

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12

Hiraga, Kohei, Osamu Tatebe, and Hideyuki Kawashima. "Scalable Distributed Metadata Server Based on Nonblocking Transactions." JUCS - Journal of Universal Computer Science 26, no. 1 (January 28, 2020): 89–106. http://dx.doi.org/10.3897/jucs.2020.006.

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Metadata performance scalability is critically important in high-performance computing when accessing many small files from millions of clients. This paper proposes a design of a scalable distributed metadata server, PPMDS, for parallel file systems using multiple key-value servers. In PPMDS, hierarchical namespace of a file system is efficiently managed by multiple servers. Multiple entries can be atomically updated using a nonblocking distributed transaction based on an algorithm of dynamic software transactional memory. This paper also proposes optimizations to further improve the metadata performance by introducing a server-side transaction processing, multiple readers, and a shared lock mode, which reduce the number of remote procedure calls and prevent unnecessary blocking. Performance evaluation shows the scalable performance up to 3 servers, and achieves 62,000 operations per second, which is 2.58x performance improvement compared to a single metadata performance.

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13

Park, Seongjoon, and Hwangnam Kim. "DAG-Based Distributed Ledger for Low-Latency Smart Grid Network." Energies 12, no. 18 (September 18, 2019): 3570. http://dx.doi.org/10.3390/en12183570.

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In this paper, we propose a scheme that implements a Distributed Ledger Technology (DLT) based on Directed Acyclic Graph (DAG) to generate, validate, and confirm the electricity transaction in Smart Grid. The convergence of the Smart Grid and distributed ledger concept has recently been introduced. Since Smart Grids require a distributed network architecture for power distribution and trading, the Distributed Ledger-based Smart Grid design is a spotlighted research domain. However, only the Blockchain-based methods, which are a type of the distributed ledger scheme, are currently either being considered or adopted in the Smart Grid. Due to computation-intensive consensus schemes such as Proof-of-Work and discrete block generation, Blockchain-based distributed ledger systems suffer from efficiency and latency issues. We propose a DAG-based distributed ledger for Smart Grids, called PowerGraph, to resolve this problem. Since a DAG-based distributed ledger does not need to generate blocks for confirmation, each transaction of the PowerGraph undergoes the validation and confirmation process individually. In addition, transactions in PowerGraph are used to keep track of the energy trade and include various types of transactions so that they can fully encompass the events in the Smart Grid network. Finally, to ensure that PowerGraph maintains a high performance, we modeled the PowerGraph performance and proposed a novel consensus algorithm that would result in the rapid confirmation of transactions. We use numerical evaluations to show that PowerGraph can accelerate the transaction processing speed by over 5 times compared to existing DAG-based DLT system.

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14

Bhunje, Anagha, and Swati Ahirrao. "Workload Aware Incremental Repartitioning of NoSQL for Online Transactional Processing Applications." International Journal of Advances in Applied Sciences 7, no. 1 (March 1, 2018): 54. http://dx.doi.org/10.11591/ijaas.v7.i1.pp54-65.

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<p><span lang="EN-US">Numerous applications are deployed on the web with the increasing popularity of internet. The applications include, 1) Banking applications,<br /> 2) Gaming applications, 3) E-commerce web applications. Different applications reply on OLTP (Online Transaction Processing) systems. OLTP systems need to be scalable and require fast response. Today modern web applications generate huge amount of the data which one particular machine and Relational databases cannot handle. The E-Commerce applications are facing the challenge of improving the scalability of the system. Data partitioning technique is used to improve the scalability of the system. The data is distributed among the different machines which results in increasing number of transactions. The work-load aware incremental repartitioning approach is used to balance the load among the partitions and to reduce the number of transactions that are distributed in nature. Hyper Graph Representation technique is used to represent the entire transactional workload in graph form. In this technique, frequently used items are collected and Grouped by using Fuzzy C-means Clustering Algorithm. Tuple Classification and Migration Algorithm is used for mapping clusters to partitions and after that tuples are migrated efficiently.</span></p>

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15

Yoon, Yong I., and Song C. Moon. "Reliable transaction processing for real-time distributed database systems." Microprocessing and Microprogramming 34, no. 1-5 (February 1992): 63–66. http://dx.doi.org/10.1016/0165-6074(92)90103-e.

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16

Komiya, Takao, Tomoya Enokido, and Makoto Takizawa. "Mobile agent model for transaction processing on distributed objects." Information Sciences 154, no. 1-2 (August 2003): 23–38. http://dx.doi.org/10.1016/s0020-0255(03)00004-5.

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17

Ulusoy, Özgür. "Transaction processing in distributed active real-time database systems." Journal of Systems and Software 42, no. 3 (September 1998): 247–62. http://dx.doi.org/10.1016/s0164-1212(98)10013-4.

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18

Ciciani, B., D. M. Dias, B. R. Iyer, and P. S. Yu. "A hybrid distributed centralized system structure for transaction processing." IEEE Transactions on Software Engineering 16, no. 8 (1990): 791–806. http://dx.doi.org/10.1109/32.57619.

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19

Li, Jianjiang, Qian Ge, Jie Wu, Yue Li, Xiaolei Yang, and Zhanning Ma. "Research and implementation of a distributed transaction processing middleware." Future Generation Computer Systems 74 (September 2017): 232–40. http://dx.doi.org/10.1016/j.future.2016.01.021.

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20

A. M, JOHN-OTUMU,, IMHANLAHIMI, R. E, and OSHOIRIBHOR, E. O. "Automated Workflow Execution of Loan Transaction Processing for Distributed Environment." Journal of Computer and Information Technology 10, no. 2 (April 21, 2019): 14–23. http://dx.doi.org/10.22147/jucit/100202.

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21

Yao, Chang, Meihui Zhang, Qian Lin, Beng Chin Ooi, and Jiatao Xu. "Scaling distributed transaction processing and recovery based on dependency logging." VLDB Journal 27, no. 3 (March 22, 2018): 347–68. http://dx.doi.org/10.1007/s00778-018-0500-2.

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22

Thomasian, A. "Distributed optimistic concurrency control methods for high-performance transaction processing." IEEE Transactions on Knowledge and Data Engineering 10, no. 1 (1998): 173–89. http://dx.doi.org/10.1109/69.667102.

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23

Rahm, Erhard. "A Framework for workload allocation in distributed transaction processing systems." Journal of Systems and Software 18, no. 2 (May 1992): 171–90. http://dx.doi.org/10.1016/0164-1212(92)90126-5.

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24

Singh, Prakash Kumar, and Udai Shanker. "Transaction Scheduling Heuristics in Mobile Distributed Real Time Database System." Recent Advances in Computer Science and Communications 13, no. 4 (October 19, 2020): 758–70. http://dx.doi.org/10.2174/2213275912666190809120654.

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Background: Today's widely used small and portable mobile database technologies have geared toward the mobile distributed real-time database systems (MDRTDBS).Various real time applications like mobile devices, missile systems, navigation control systems, satellites and many others are some examples of MDRTDBS. In the new era of technology, a large domain of applications are based on MDRTDBS, meanwhile different intrinsic limitation like disconnection and mobility typically effect on its correct execution. Mobile distributed real-time systems have different wireless constrained such like energy, processing capacity, memory storage facilities and variable network communication channels. In last few years, different applications run on different mobile nodes needed a suitable transaction mechanism to complete their service without failing its deadline. In recent years researchers focused on MDRTDBS, to develop a suitable concurrency control, commit control method. Replication, check pointing, security, caching and query processing are some other hot research topics in the field of MDRTDBS. Objective: it is needed to maintain data consistency and correct results in mobile distributed real time database system. In our review we have identified key issues which might be considered for development of various transaction executing protocols. We have Introduce a taxonomy of different CC, commit, replication and security issues, which could be advantageous for design, and development of transaction protocols. Method: In the review we have discussed various concurrency, commit, replication methods. Apart from these we have discussed various check pointing, caching and query techniques which is developed in database system. A comparison among various concurrency and commit protocols has been done in the review. The role of different key methods which can affect and help the transaction execution in wireless environment is discussed separately in the paper. Results: Analytical results are not mentioned in the review paper. However the role and affect on the transaction execution are mentioned clearly. Issues and their advantages of different concurrency and commit protocols are mentioned. Results: Analytical results are not mentioned in the review paper. However the role and affect on the transaction execution are mentioned clearly. Issues and their advantages of different concurrency and commit protocols are mentioned. Conclusion: It is found that transaction processing is still a challenging area of research. A number of issues has been discussed and reviewed various approaches to control concurrency control and atomicity methods. We have presented a detailed survey and classification of various issues based on commit, concurrency, and replication methods for MTDRTDBS. However, in the paper different security, caching and query processing and check pointing issues has been also discussed which should be considered for future work. Database researchers have needed to integrate these issues with their work and develop a suitable protocol.

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25

Vishwakarma, Jaychand. "Transaction Processing Environment Kernelized Architecture in Multilevel Secure Application Policies." International Journal of Advanced Research in Computer Science and Software Engineering 8, no. 2 (February 28, 2018): 87. http://dx.doi.org/10.23956/ijarcsse.v8i2.577.

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Multilevel security poses many challenging problems for transaction processing. The challenges are due to the conflicting requirements imposed by confidentiality, integrity, and availability} the three components of security. We identify these requirements on transaction processing in Multilevel Secure (MLS) database management systems (DBMSs) and survey the efforts of a number of researchers to meet these requirements .While our emphasis on centralized system based on kernelized Architecture, we briefly overview the research in the distributed MLS DBMSs as well.

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26

Dakroury, Y., and J. P. Elloy. "A Distributed Real-Time Transaction Processing Environment for the CIM Applications." IFAC Proceedings Volumes 28, no. 22 (September 1995): 157–63. http://dx.doi.org/10.1016/s1474-6670(17)46686-9.

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27

Lee, Juchang, Kyu Hwan Kim, Hyejeong Lee, Mihnea Andrei, Seongyun Ko, Friedrich Keller, and Wook-Shin Han. "Asymmetric-partition replication for highly scalable distributed transaction processing in practice." Proceedings of the VLDB Endowment 13, no. 12 (August 2020): 3112–24. http://dx.doi.org/10.14778/3415478.3415538.

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28

Bariyira Christopher, Gabriel, and Kabari Ledisi G. "HYBRIDIZED CONCURRENCY CONTROL TECHNIQUE FOR TRANSACTION PROCESSING IN DISTRIBUTED DATABASE SYSTEM." International Journal of Computer Science and Mobile Computing 9, no. 9 (September 30, 2020): 118–27. http://dx.doi.org/10.47760/ijcsmc.2020.v09i09.012.

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29

Thomasian, A. "Determining the number of remote sites accessed in distributed transaction processing." IEEE Transactions on Parallel and Distributed Systems 4, no. 1 (1993): 99–103. http://dx.doi.org/10.1109/71.205656.

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30

Liao, Jianwei, Xiaodan Zhuang, Renyi Fan, and Xiaoning Peng. "Toward a General Distributed Messaging Framework for Online Transaction Processing Applications." IEEE Access 5 (2017): 18166–78. http://dx.doi.org/10.1109/access.2017.2717930.

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31

Crichlow, Joel M. "Combining optimism and pessimism to produce high availability in distributed transaction processing." ACM SIGOPS Operating Systems Review 28, no. 3 (July 1994): 43–64. http://dx.doi.org/10.1145/182110.182115.

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32

Apers, Peter, and Peter Scheuermann. "Schema architectures and their relationship to transaction processing in distributed database systems." Information Sciences 54, no. 1-2 (March 1991): 41–66. http://dx.doi.org/10.1016/0020-0255(91)90044-u.

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33

Haldar, S., and D. K. Subramanian. "An affinity-based dynamic load balancing protocol for distributed transaction processing systems." Performance Evaluation 17, no. 1 (January 1993): 53–71. http://dx.doi.org/10.1016/0166-5316(93)90012-j.

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34

Cai, Wenjun, Wei Jiang, Ke Xie, Yan Zhu, Yingli Liu, and Tao Shen. "Dynamic reputation–based consensus mechanism: Real-time transactions for energy blockchain." International Journal of Distributed Sensor Networks 16, no. 3 (February 29, 2020): 155014772090733. http://dx.doi.org/10.1177/1550147720907335.

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The energy blockchain is a distributed Internet protocol for energy transactions between nodes in power systems. The consensus algorithm is the core component of the energy blockchain and has an essential impact on its application. At present, in the implementation of the energy blockchain, there are problems such as low transaction throughput (transactions per second) and high latency, which cannot meet the application requirements of real-time processing transactions in the energy field. To this end, according to the analysis of conventional blockchain consensus algorithm and traditional practical Byzantine fault tolerance algorithm, a dynamic-reputation practical Byzantine fault tolerance algorithm for the energy blockchain is proposed. The dynamic-reputation practical Byzantine fault tolerance algorithm adopts a credit-based consortium node consensus election method. The monitoring node divides the remaining nodes into two types of nodes according to the reputation value: the consensus node and the secondary node, which, respectively, participate in different stages of the block generation process, and dynamically update the consensus nodes with low reputation ratings. By constructing the experimental platform simulation, the test results verify the effectiveness of the dynamic-reputation practical Byzantine fault tolerance algorithm. Compared with the algorithm of the fabric platform, the dynamic-reputation practical Byzantine fault tolerance algorithm improves the transaction processing speed and is suitable for the blockchain application in the energy field.

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35

Bhargava, Bharat. "Transaction Processing and Consistency Control of Replicated Copies during Failures in Distributed Databases." Journal of Management Information Systems 4, no. 2 (September 1987): 93–112. http://dx.doi.org/10.1080/07421222.1987.11517795.

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36

AMAMIYA, MAKOTO, HIDEO TANIGUCHI, and TAKANORI MATSUZAKI. "AN ARCHITECTURE OF FUSING COMMUNICATION AND EXECUTION FOR GLOBAL DISTRIBUTED PROCESSING." Parallel Processing Letters 11, no. 01 (March 2001): 7–24. http://dx.doi.org/10.1142/s0129626401000397.

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We are pursuing the FUCE architecture project at Kyushu University. FUCE means FUsion of Communication and Execution. The main objective of our research is, as the name shows, to develop a new architecture that truly fuses communication and computation. The FUCE project develops a new on-chip-multi-processor and kernel software on it. We name the processor FUCE processor, and the kernel software as CEFOS (Communication and Execution Fusion OS). The FUCE processor is designed as a network node processor to perform mainly switching/transmitting of messages/transaction and handling its contents. FUCE processor architecture is designed as a multiprocessor-on-chip to support the fine-grain multi-threading. The kernel software CEFOS is also developed on the concept of multithreading. User and system processes are constructed as a set of threads, which are executed concurrently according to thread dependences.

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37

Akhatov, A. R., and F. M. Nazarov. "METHODS OF IMPLEMENTATION OF BLOCKCHAIN TECHNOLOGIES ON THE BASIS OF CRYPTOGRAPHIC PROTECTION FOR THE DATA PROCESSING SYSTEM WITH CONSTRAINT AND LAGGING INTO ELECTRONIC DOCUMENT MANAGEMEN." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 184 (October 2019): 3–12. http://dx.doi.org/10.14489/vkit.2019.10.pp.003-012.

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The problem of application design by restriction and delay in ED (Electronic Document) management based on blockchain technologies to ensure a new level of security, reliability, transparency of data processing is considered. Increasing the reliability of information in systems by limiting and delaying ED management of enterprises and organizations during collecting, transmitting, storing and processing ED based on new, little-studied optimization technologies for processing blockchain-type data is a relevant and promising research topic. Important advantages of the potential use of transaction blocks built according to certain rules in systems by limiting and delaying ED are ensuring security by encrypting transactions for subsequent confirmation, the inability to make unauthorized changes due to the dependence of the current blockchain state on previous transactions, transparency and reliability of procedures due to public and distributed storage, as well as the interaction of a large number of users between without the use of “trusted intermediaries”. Studies show that when using existing algorithms for adding blocks in any system, it is possible to achieve the requirements of decentralization, openness of the entered data, the inability to change the data once entered into the system. However, mathematics-cryptographic information protection must be developed for each designed system separately. The task of providing and formulating the rules of data reliability control by limiting and delaying in ED circulation based on cryptographic methods of encrypting transaction blocks constituting the blockchain has been formulated. The approaches have been adopted as a methodology of support for systems by limiting and delaying electronic documents based on a new database architecture.

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38

Xiao, Chuqiao, Yefeng Xia, Qian Zhang, Xueqing Gong, and Liyan Zhu. "CBase-EC: Achieving Optimal Throughput-Storage Efficiency Trade-Off Using Erasure Codes." Electronics 10, no. 2 (January 8, 2021): 126. http://dx.doi.org/10.3390/electronics10020126.

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Many distributed database systems that guarantee high concurrency and scalability adopt read-write separation architecture. Simultaneously, these systems need to store massive amounts of data daily, requiring different mechanisms for storing and accessing data, such as hot and cold data access strategies. Unlike distributed storage systems, the distributed database splits a table into sub-tables or shards, and the request frequency of each sub-table is not the same within a specific time. Therefore, it is not only necessary to design hot-to-cold approaches to reduce storage overhead, but also cold-to-hot methods to ensure high concurrency of those systems. We present a new redundant strategy named CBase-EC, using erasure codes to trade the performances of transaction processing and storage efficiency for CBase database systems developed for financial scenarios of the Bank. Two algorithms are proposed: the hot-cold tablets (shards) recognition algorithm and the hot-cold dynamic conversion algorithm. Then we adopt two optimization approaches to improve CBase-EC performance. In the experiment, we compare CBase-EC with three-replicas in CBase. The experimental results show that although the transaction processing performance declined by no more than 6%, the storage efficiency increased by 18.4%.

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39

Xiao, Chuqiao, Yefeng Xia, Qian Zhang, Xueqing Gong, and Liyan Zhu. "CBase-EC: Achieving Optimal Throughput-Storage Efficiency Trade-Off Using Erasure Codes." Electronics 10, no. 2 (January 8, 2021): 126. http://dx.doi.org/10.3390/electronics10020126.

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Many distributed database systems that guarantee high concurrency and scalability adopt read-write separation architecture. Simultaneously, these systems need to store massive amounts of data daily, requiring different mechanisms for storing and accessing data, such as hot and cold data access strategies. Unlike distributed storage systems, the distributed database splits a table into sub-tables or shards, and the request frequency of each sub-table is not the same within a specific time. Therefore, it is not only necessary to design hot-to-cold approaches to reduce storage overhead, but also cold-to-hot methods to ensure high concurrency of those systems. We present a new redundant strategy named CBase-EC, using erasure codes to trade the performances of transaction processing and storage efficiency for CBase database systems developed for financial scenarios of the Bank. Two algorithms are proposed: the hot-cold tablets (shards) recognition algorithm and the hot-cold dynamic conversion algorithm. Then we adopt two optimization approaches to improve CBase-EC performance. In the experiment, we compare CBase-EC with three-replicas in CBase. The experimental results show that although the transaction processing performance declined by no more than 6%, the storage efficiency increased by 18.4%.

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40

Ciciani, B., D. M. Dias, and P. S. Yu. "Analysis of concurrency-coherency control protocols for distributed transaction processing systems with regional locality." IEEE Transactions on Software Engineering 18, no. 10 (1992): 899–914. http://dx.doi.org/10.1109/32.163606.

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41

Tolchin, Stephen G., Eric S. Bergan, Marina Arseniev, Peter Kuzmak, Roger Nordquist, and Dennis Siegel. "Transaction processing using remote procedure calls (RPC) for a heterogeneous distributed clinical information system." Computer Methods and Programs in Biomedicine 25, no. 2 (September 1987): 193–208. http://dx.doi.org/10.1016/0169-2607(87)90054-x.

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42

Qin, Biao, and Yunsheng Liu. "A hybrid distributed optimistic concurrency control method for high-performance real-time transaction processing." Journal of Computer Science and Technology 18, no. 1 (January 2003): 77–83. http://dx.doi.org/10.1007/bf02946653.

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43

Ulusoy, Özgür. "A study of two transaction-processing architectures for distributed real-time data base systems." Journal of Systems and Software 31, no. 2 (November 1995): 97–108. http://dx.doi.org/10.1016/0164-1212(94)00090-a.

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44

Urban, Susan D., Suzanne W. Dietrich, Akash Saxena, and Amy Sundermier. "Interconnection of Distributed Components: An Overview of Current Middleware Solutions*." Journal of Computing and Information Science in Engineering 1, no. 1 (November 1, 2000): 23–31. http://dx.doi.org/10.1115/1.1344239.

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From design and manufacturing to electronic commerce, coordinating business activities in engineering applications requires accessing data and software from distributed sources. The Common Object Request Broker Architecture (CORBA) of the Object Management Group emerged in the 1990’s as a standard for access to distributed software components. Since that time, the standard has matured significantly, providing advanced features for event notification and transaction processing. At the same time, Java-based technology for distributed object computing has also emerged, from Remote Method Invocation to Enterprise JavaBeans, Jini Connection Technology, JavaSpaces, Java Messaging Service, and Java Transaction Service. Sorting through the options available for the use of such tools can be a difficult task. This paper provides an overview of CORBA and Java technology for distributed object computing. A comparison of these different technologies is presented, discussing the similarities and differences, as well as the way in which such tools can be used together for distributed access to the types of software and data components that are needed for the construction of distributed engineering applications. Future directions for the use of such tools are also identified.

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45

Xu, Hua Fen, Jing Wu, and Guo Jun Mao. "The Key Technologies for Classification of Distributed Data Streams." Applied Mechanics and Materials 727-728 (January 2015): 976–81. http://dx.doi.org/10.4028/www.scientific.net/amm.727-728.976.

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With advances in data collection and generation technologies, environments that produce data streams is more and more. In recent years, the network application is further universal and the applications of a single data stream transfer toward a multi-node distributed data streams, such as sensor network, network monitoring, web log analysis and the credit card transaction data of multiple sites. These data is not only real-time, continuous and large scale, but also distributed. How to manage and analyze large dynamic datasets is an important subject that researchers are faced with. In view of the situation, it presented the formalization description of homogeneous and heterogeneous distributed data stream in this paper, analyzed advantages and disadvantages of the centralized stream processing architecture and distributed streaming processing architecture, discussed the recent progress in distributed data stream classification algorithm, summed up the problems and challenges faced by the distributed data stream mining, and possible future research directions.

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46

Yoshida, Makoto, and Kazumine Kojima. "High Performance Computing Design by Code Migration for Distributed Desktop Computing Grids." International Journal of Grid and High Performance Computing 3, no. 4 (October 2011): 53–70. http://dx.doi.org/10.4018/jghpc.2011100105.

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Large scale loosely coupled PCs can organize clusters and form desktop computing grids on sharing each processing power; power of PCs, transaction distributions, network scales, network delays, and code migration algorithms characterize the performance of the computing grids. This article describes the design methodologies of workload management in distributed desktop computing grids. Based on the code migration experiments, transfer policy for computation was determined and several simulations for location policies were examined, and the design methodologies for distributed desktop computing grids are derived from the simulation results. The language for distributed desktop computing is designed to accomplish the design methodologies.

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Hühn, Oliver, Christian Markl, and Martin Bichler. "On the predictive performance of queueing network models for large-scale distributed transaction processing systems." Information Technology and Management 10, no. 2-3 (July 10, 2009): 135–49. http://dx.doi.org/10.1007/s10799-009-0056-3.

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Al-Haija, Qasem Abu, and Abdulaziz A. Alsulami. "High Performance Classification Model to Identify Ransomware Payments for Heterogeneous Bitcoin Networks." Electronics 10, no. 17 (August 31, 2021): 2113. http://dx.doi.org/10.3390/electronics10172113.

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The Bitcoin cryptocurrency is a worldwide prevalent virtualized digital currency conceptualized in 2008 as a distributed transactions system. Bitcoin transactions make use of peer-to-peer network nodes without a third-party intermediary, and the transactions can be verified by the node. Although Bitcoin networks have exhibited high efficiency in the financial transaction systems, their payment transactions are vulnerable to several ransomware attacks. For that reason, investigators have been working on developing ransomware payment identification techniques for bitcoin transactions’ networks to prevent such harmful cyberattacks. In this paper, we propose a high performance Bitcoin transaction predictive system that investigates the Bitcoin payment transactions to learn data patterns that can recognize and classify ransomware payments for heterogeneous bitcoin networks. Specifically, our system makes use of two supervised machine learning methods to learn the distinguishing patterns in Bitcoin payment transactions, namely, shallow neural networks (SNN) and optimizable decision trees (ODT). To validate the effectiveness of our solution approach, we evaluate our machine learning based predictive models on a recent Bitcoin transactions dataset in terms of classification accuracy as a key performance indicator and other key evaluation metrics such as the confusion matrix, positive predictive value, true positive rate, and the corresponding prediction errors. As a result, our superlative experimental result was registered to the model-based decision trees scoring 99.9% and 99.4% classification detection (two-class classifier) and accuracy (multiclass classifier), respectively. Hence, the obtained model accuracy results are superior as they surpassed many state-of-the-art models developed to identify ransomware payments in bitcoin transactions.

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Zhong, Zhen Kui. "Design and Implementation of Software Architecture of Manufacturing Execution System Based on Middleware Technology." Applied Mechanics and Materials 443 (October 2013): 526–30. http://dx.doi.org/10.4028/www.scientific.net/amm.443.526.

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Manufacturing execution system is the software system that is used most widely for manufacturing enterprises to realize informatization. In order to solve the problem of distributed heterogeneous environment, MES introduces the concept of middleware. It is in the middle of the operation system software and MES and above the operation system, network and database and below the MES. It helps the software developers to flexibly and high effectively develop and integrate complicated all modules in MES as well as complicated application and communications in enterprises. This design adopts two kinds of middleware. The first kind is Message Oriented Middleware (MOM). Message Oriented Middleware hides the details of interaction between all kinds of machine equipment and MES data under the unified data specifications. It makes in-time, high-efficient and stable data transmission as well as easily copes with the complicated production environment. The second kind is common transaction processing middleware. It enclosures the details of transaction processing and offers a stable transaction platform, enabling the developers to pay attention to the development of business logic. It ensures the development qualities and the development costs.

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Chandrashekar, D. K., K. C. Srikantaiah, and K. R. Venugopal. "Map Reduce Based Association Rule Mining from Big Data." Journal of Computational and Theoretical Nanoscience 17, no. 9 (July 1, 2020): 4262–66. http://dx.doi.org/10.1166/jctn.2020.9059.

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In today’s world, the shopping is the largest fashionable trend where the transaction processing is meticulous to fetch the items from the shopping transaction history by using traditional Apriori algorithm. An Apriori algorithm is the one which is used for finding frequent pattern from the given dataset. The problem of Apriori is to find useful itemsets for business purpose was time consuming. To overcome this problem, we have proposed Map Reduce based Apriori algorithm which generates frequent itemset and association rules by using parallel computations to reduce computations. The Spark distributed systems along with data bricks technology have been used. The experimental result shows that have been reduced the time taken fetch the data from the database.

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