Transactions In Database Systems Research Articles

GlassDB: An Efficient Verifiable Ledger Database System Through Transparency

Verifiable ledger databases protect data history against malicious tampering. Existing systems, such as blockchains and certificate transparency, are based on transparency logs --- a simple abstraction allowing users to verify that a log maintained by an untrusted server is append-only. They expose a simple key-value interface without transactions. Building a practical database from transparency logs, on the other hand, remains a challenge. In this paper, we explore the design space of verifiable ledger databases along three dimensions: abstraction, threat model, and performance. We survey existing systems and identify their two limitations, namely, the lack of transaction support and the inferior efficiency. We then present GlassDB, a distributed database system that addresses these limitations under a practical threat model. GlassDB inherits the verifiability of transparency logs, but supports transactions and offers high performance. It extends a ledgerlike key-value store with a data structure for efficient proofs, and adds a concurrency control mechanism for transactions. GlassDB batches independent operations from concurrent transactions when updating the core data structures. In addition, we design a new benchmark for evaluating verifiable ledger databases, by extending YCSB and TPC-C benchmarks. Using this benchmark, we compare GlassDB against four baselines: reimplemented versions of three verifiable databases, and a verifiable map backed by a transparency log. Experimental results demonstrate that GlassDB is an efficient, transactional, and verifiable ledger database system.

Scalar DL

This paper presents Scalar DL, a Byzantine fault detection (BFD) middleware for transactional database systems. Scalar DL manages two separately administered database replicas in a database system and can detect Byzantine faults in the database system as long as either replica is honest (not faulty). Unlike previous BFD works, Scalar DL executes non-conflicting transactions in parallel while preserving a correctness guarantee. Moreover, Scalar DL is database-agnostic middleware so that it achieves the detection capability in a database system without either modifying the databases or using database-specific mechanisms. Experimental results with YCSB and TPC-C show that Scalar DL outperforms a state-of-the-art BFD system by 3.5 to 10.6 times in throughput and works effectively on multiple database implementations. We also show that Scalar DL achieves near-linear (91%) scalability when the number of nodes composing each replica increases.

Data protection in transactional and statistical applications of databases

The article describes a discussion on the issue of data protection in databases. The discussion attempts to answer the question about the possibility of using a transactional database system as a system capable of data protection in a statistical database. The discussion is preceded by a reminder of the basic issues related to data protection in databases, including reminder of flow control models, access control models and the inference. The key element of the article is the analysis, based on the example of the Oracle database management system, whether data protection mechanisms in transactional databases can be effective in case of data protection in statistical databases.

On a Three-Valued Logic with Blamey\u2019s Interjunction for the Formal Description of Atomic Transactions

The article demonstrates that to describe the property of atomicity (one of the ACID property) of transactions in database systems, we need a three-valued logic with propositional connective characterized in the same way as Blamey’s interjunction. However, the article explains that since Blamey’s partial logic with interjunction is a logic without tautologies, it does not satisfy some salient conditions of being a logic of atomic transactions. The article introduces a logic of the considered kind, and provides an example of the formal exposition of the case of an atomic transaction. Finally, the article explains the philosophical significance of the introduced logic.

Determinant factors of using data and knowledge in bridge engineering

Complexity and heterogeneity of information and decision processes in bridge construction necessitates the use of heterogeneous and complex information resources. However, for data collection and processing in this area, transactional database systems are mainly employed. They allow only the processing of detailed precise data as well as static ones. Other categories of data used in this area, including, for instance, fuzzy, temporal or active data, make it necessary to use additional specialized database systems. A similar remark can be made in relation to the various categories of acquired and processed knowledge in bridge construction projects (e.g. complete or incomplete knowledge in the reasoning process). Numerous independent and autonomous software applications used for this purpose do not offer comprehensive support for complex and multi-stage problems. It appears then that rational IT solutions in this area should be sought within the integrated systems of intelligent databases, supplemented with data fuzzing mechanisms and active data support, and, additionally, enabling the exchange of data with heuristic reasoning systems, in particular with expert systems that use the rule-based organization of knowledge, cooperating with case-based reasoning systems.

FineLine

Recovery is an intricate aspect of transaction processing architectures. In its traditional implementation, recovery requires the management of two persistent data stores---a write-ahead log and a materialized database---which must be carefully orchestrated to maintain transactional consistency. Furthermore, the design and implementation of recovery algorithms have deep ramifications into almost every component of the internal system architecture, from concurrency control to buffer management and access path implementation. Such complexity not only incurs high costs for development, testing, and training, but also unavoidably affects system performance, introducing overheads and limiting scalability. This paper proposes a novel approach for transactional storage and recovery called FineLine. It simplifies the implementation of transactional database systems by eliminating the log-database duality and maintaining all persistent data in a single, log-structured data structure. This approach not only provides more efficient recovery with less overhead, but also decouples the management of persistent data from in-memory access paths. As such, it blurs the lines that separate in-memory from disk-based database systems, providing the efficiency of the former with the reliability of the latter.

FineLine

Recovery is an intricate aspect of transaction processing architectures. In its traditional implementation, recovery requires the management of two persistent data stores---a write-ahead log and a materialized database---which must be carefully orchestrated to maintain transactional consistency. Furthermore, the design and implementation of recovery algorithms have deep ramifications into almost every component of the internal system architecture, from concurrency control to buffer management and access path implementation. Such complexity not only incurs high costs for development, testing, and training, but also unavoidably affects system performance, introducing overheads and limiting scalability.This paper proposes a novel approach for transactional storage and recovery called FineLine. It simplifies the implementation of transactional database systems by eliminating the log-database duality and maintaining all persistent data in a single, log-structured data structure. This approach not only provides more efficient recovery with less overhead, but also decouples the management of persistent data from in-memory access paths. As such, it blurs the lines that separate in-memory from disk-based database systems, providing the efficiency of the former with the reliability of the latter.

Trading Real-World Assets on Blockchain

Since its introduction in 2008, blockchain technology has outgrown its use in cryptocurrencies and is now preparing to revolutionize a multitude of commercial applications including value and supply chains, business models, and market structures. This work follows design science research to guide the implementation of a blockchain-based proof-of-concept prototype that enables the automated transaction of real-world assets, such as cars, and provides a valid, transparent, and immutable record of vehicle history to market participants, authorities, and other third parties. The contribution of this study to existing research is threefold: First, it introduces a built-in mechanism to reduce transaction risk resulting from the irreversibility of transactions in blockchain-based systems. Second, it replaces a trust-based, centralized, and bureaucratic register with a tamper-free and autonomous transactional database system that comprises a secure registration and transaction process. Third, it proposes a novel approach to mitigate adverse selection effects in lemon markets by providing a reliable, transparent, and complete record of each marketable asset’s history. In total, the findings in this article illustrate the potential of blockchain-based systems but also highlight technological shortcomings and challenges for commercial applications, such as scalability or privacy issues.

Verification and Identification Approach to Maintain MVCC in Cloud Computing

MultiVersion concurrency control is maintained over transactional database systems for secure, fast and efficient access to the shared data file implementation scenario. Most of the services and application offered in cloud world are real-time, which entails optimized compatibility service environment between master and slave clusters. In the paper, offered methodology supports replication and triggering methods intended for data consistency and dynamicity. Here, cluster based communication is set up for processing. Intercommunication among different clusters is administered through middleware besides slave intra-communication is handled by verification and identification protection. The proposed approach incorporates resistive flow to handle high impact systems that identifies and verifies multiple processes. Statistical analysis determines that the new scheme reduces the overheads from different master and slave servers as they are co-located in clusters which allow increased horizontal and vertical scalability of resources.

Data Management Challenges in Cloud Environments

Recently the cloud computing paradigm has been receiving special excitement and attention in the new researches. Cloud computing has the potential to change a large part of the IT activity, making software even more interesting as a service and shaping the way IT hardware is proposed and purchased. Developers with novel ideas for new Internet services no longer require the large capital outlays in hardware to present their service or the human expense to do it. These cloud applications apply large data centers and powerful servers that host Web applications and Web services. This report presents an overview of what cloud computing means, its history along with the advantages and disadvantages. In this paper we describe the problems and opportunities of deploying data management issues on these emerging cloud computing platforms. We study that large scale data analysis jobs, decision support systems, and application specific data marts are more likely to take benefit of cloud computing platforms than operational, transactional database systems. 

락의 실제 : 멀티코어 상의 데이터베이스 성능 분석

락은 멀티프로세서 환경에서 공유 데이터에 대한 접근을 안전하게 하는 잘 알려진 일반적인 방법이다. 1960년대에 상호 배제가 소개된 후에 많은 스핀락 알고리즘이 제안되었고 운영체제나 데이터베이스 시스템에 사용되어 왔다. 이 연구에서 고성능 멀티코어 시스템 상에서 락 알고리즘이 데이터베이스 시스템에 미치는 영향을 측정하였다. 평가를 위해 그 동안 멀티코어 상에서 성능 개선을 위해 재구조화된 최신 MySQL 5.6 및 MySQL에 탑재된 InnoDB 엔진을 사용하였다. InnoDB의 스핀락 함수를 수정하여 다양한 락 알고리즘들을 구현하였고 구현된 락 알고리즘들을 멀티코어 환경에서 평가하였다. A lock is a general and popular way of serializing accesses to shared data in multiprocessor environments. After the mutual exclusion was first introduced in 1960s, many spinlock algorithms have been proposed and deployed to real systems such as operating systems and (transactional) database systems. In this study, we measure impacts of a lock mechanism on a database system under various CPU configurations using a high-end multicore system. For the evaluation, we use the most up-to-date version of MySQL (version 5.6) with InnoDB engine, which has been substantially re-architected to improve scalability on multicore machines. We changed the original spinlock function of InnoDB to evaluate various spinlock mechanisms on multicore machines.

NoSQL in Higher Education. A Case Study

Big Data and NoSQL technologies are simultaneously marketing hypes and tools that could significantly change the database and application development landscape. This paper argues that, despite the negation and revolt suggested by their name, NoSQL data stores are rather a complement of traditional transactional database systems. The paper is focused on the module implemented at the Faculty of Economics and Business Administration dedicated to web and application servers log analysis. Using MongoDB -- a popular NoSQL product, JavaScript, Pyhon environment and Tornado web server, the module extracts data from large log files and provides useful information about users who have not succeeded to connect to applications such as Blackboard system, faculty portal and web site, about the usage of workstations and labs and other information for which NoSQL technologies can complement relational databases. For a better understanding, beside the module architecture and the solution itself, the authors also try to draw the big picture for the NoSQL technologies and the current context in the data storage environment.

Balancing Performance, Accuracy, and Precision for Secure Cloud Transactions

In distributed transactional database systems deployed over cloud servers, entities cooperate to form proofs of authorizations that are justified by collections of certified credentials. These proofs and credentials may be evaluated and collected over extended time periods under the risk of having the underlying authorization policies or the user credentials being in inconsistent states. It therefore becomes possible for policy-based authorization systems to make unsafe decisions that might threaten sensitive resources. In this paper, we highlight the criticality of the problem. We then define the notion of trusted transactions when dealing with proofs of authorization. Accordingly, we propose several increasingly stringent levels of policy consistency constraints, and present different enforcement approaches to guarantee the trustworthiness of transactions executing on cloud servers. We propose a Two-Phase Validation Commit protocol as a solution, which is a modified version of the basic Two-Phase Validation Commit protocols. We finally analyze the different approaches presented using both analytical evaluation of the overheads and simulations to guide the decision makers to which approach to use.

Detecting intrusion transactions in database systems:a novel approach

The security of computers and their networks is of crucial concern in the world today. One mechanism to safeguard information stored in database systems is an Intrusion Detection System (IDS). The purpose of intrusion detection in database systems is to detect malicious transactions that corrupt data. Recently researchers are working on using data mining techniques for detecting such malicious transactions in database systems. Their approach concentrates on mining data dependencies among data items. However, the transactions not compliant with these data dependencies are identified as malicious transactions. Algorithms that these approaches use for designing their data dependency miner have limitations. For instance, they need to experimentally determine appropriate settings for minimum support and related constraints, which does not necessarily lead to strong data dependencies. In this paper we propose a new data mining algorithm, called the Optimal Data Access Dependency Rule Mining (ODADRM), for designing a data dependency miner for our database IDS. ODADRM is an extension of k-optimal rule discovery algorithm, which has been improved to be suitable in database intrusion detection domain. ODADRM avoids many limitations of previous data dependency miner algorithms. As a result, our approach is able to track normal transactions and detect malicious ones more effectively than existing approaches.

Ethopian Database Management system as a Cloud Service: Limitations and advantages

An Ethiopian Cloud database management system is a distributed database that delivers computing as a service instead of a product. It is the sharing of resources, software, and information between multiple devices over a network which is mostly the internet. It is expected that this number will grow significantly in the future. As a result, there is a growing interest in outsourcing database management tasks to third parties that can provide these tasks for much lower cost due to the economy of scale just like putting it into the cloud. In this paper, we discuss the recent trend in database management system and the possibilities of making it as one of the services offered in the cloud. We also Recently the cloud computing paradigm has been receiving significant excitement and attention in the media and blogosphere. To some, cloud computing seems to be little more than a marketing umbrella, encompassing topics such as distributed computing, grid computing, utility computing, and software as- a-service, that have already received significant research focus and commercial implementation. Nonetheless, there exist an increasing number of large companies that are offering cloud computing infrastructure products and services that do not entirely resemble the visions of these individual component topics. In this article we discuss the limitations and opportunities of deploying data management issues on these emerging cloud computing platforms. We speculate that large scale data analysis tasks, decision support systems, and application specific data marts are more likely to take advantage of cloud computing platforms than operational, transactional database systems (at least initially). We then discuss some currently available open source and commercial database options that can be used to perform such analysis tasks, and conclude that none of these options, as presently architected, match the requisite features. We thus express the need for a new DBMS, designed specifically for Ethiopian cloud computing environments.

An Improved Distributed Mining Algorithm of Association Rules

Large amount of data is stored in distributed web node as Internet and distributed database develops, it is impossible to store these data in single node on account of communication, efficiency and security. Through research was conducted on mining association rules in the distributed database system and classical Apriori algorithm was extended based on transactional database system. Then an efficient algorithm that get association rules from frequent itemsets was presented. Experiment results show that the algorithm has sound extension, short time complexity and small communication cost.

Consistency and orderability

The semantics of objects and transactions in database systems are investigated. User-defined predicates called consistency assertions are used to specify user programs. Three new correctness criteria are proposed. The first correctness criterion consistency is based solely on the users' specifications and admit nonserializable executions that are acceptable to the users. Integrity constraints of the database are maintained through consistency assertions. The second correctness criterion orderability is a generalization of view serializability and represents a weak notion of equivalence to a serial schedule. Finally, the third correctness criterion strong order-ability is introduced as a generalization of conflict serializability. Unlike consistency, the notions of orderability allow users to operate an isolation as maintenance of the integrity constrainst now becomes the responsibility of the database system.

Performance comparison of database concurrency control mechanisms based on two-phase locking, timestamping and mixed approach

Many techniques have been proposed for managing concurrent execution of transactions in database systems. There are two well-known categories: one uses locks and the other uses timestamps. The performance of seven different concurrency control algorithms belonging to these two categories have been investigated with the help of detailed and realistic simulation models so that a comparative evaluation of their performance can be done. These include the performance of four different locking techniques, the basic timestamp technique and wound-wait and wait-die systems. We have evaluated the effect of deadlocks, read : write ratio, cascade rollback, degree of concurrency, transaction-size mixes, transaction wait time and transaction blockings on the overall performance of these algorithms. We show that cascade rollbacks, contrary to our expectation, do not affect throughput significantly, since these rollbacks do not occur very frequently and their average degree is always small. Deadlocks occur rarely and the degree of cycles is never very high. The effect of read : write ratios does not extend to higher transaction arrival rates and the effect of transaction waittime on the throughput is not so severe. We also give some guidelines for selecting the most suitable concurrency control mechanism for a particular type of workload.

Modeling and analysis of transaction execution in database systems

The controlled-generator model of P.J. Ramadge and W.M. Wonham (1988) is used to formulate the concurrent execution of transactions in database systems as a control problem for a partially observed discrete-event dynamical system. The control objectives of this problem (for concurrency control and recovery) and the properties of some important transaction scheduling techniques are characterized in terms of the language generated by the controlled process and in terms of the stage of an ideal complete-information scheduler. Results about the performance of these techniques are presented. >