Distributed Database Systems Research Articles

Query Computation Time and Its Performance over Distributed Database Frameworks

It is essential to maintain a relevant methodology for data fragmentation to employ resources, and thus, it needs to choose an accurate and efficient fragmentation methodology to improve authority of distributed database system. This leads the challenges on data reliability, stable storage space and costs, Communication costs, and security issues. In Distributed database framework, query computation and data privacy plays a vital role over portioned distributed databases such as vertical, horizontal and hybrid models, Privacy of any information is regarded as the essential issue in nowadays hence we show an approach by that we can use privacy preservation over the two parties which are actually distributing their data horizontally or vertically. In this chapter, I present an approach by which the concept of hierarchal clustering applied over the horizontally partitioned data set. We also explain the desired algorithm like hierarchal clustering, algorithms for finding the minimum closest cluster. Furthermore, it explores the performance of Query Computation over portioned databases with the analysis of Efficiency and Privacy.

A general fragments allocation method for join query in distributed database

The quality of fragments allocation is key for improving performance of join query in distributed database. Current strategies concentrate on using heuristic rules to allocate fragments to corresponding locations, such as picking the location with maximum required data or with greedy algorithm. Notwithstanding their benefits, under distributed environment, facing various query plans, different data distributions and expensive network cost, their scene-sensitive character may easily generate low quality allocation plan due to lack of generalization ability.In this paper, for breaking this limitation, we propose a general strategy for allocating fragments(AlCo, Allocate fragments based on Cost). AlCo evaluates multiple candidate allocation plans based on cost, which is realized by a modified genetic algorithm employed from PostgreSQL. Our fitness function (cost model) synthetically considers various changeable factors to support generalization ability. For reducing the risks caused by randomization of genetic algorithm, AlCo provides an upper bound computed through current heuristic methods to improve the robustness of our genetic algorithm. We implement AlCo in a distributed database system, and the experiments show that, on TPC-H benchmark, AlCo is up to 2x–4x better on performance than existing strategies and performs well in robustness and scalability.

LIFT- A Linear Two-Phase Commit Protocol

Two phase commit (2PC) protocol is used to coordinate transaction commitment in distributed database system. The 2PC protocol is further classified into linear and centralized versions. The linear version of 2PC i.e. L-2PC protocol runs serially whereas in the centralized version, the commit process allows every site involved in executing the transaction to prepare and commit in parallel. In past, very little efforts have been made to overcome the unfavourable message overhead, poor recovery process and some other problems associated with L-2PC protocol. This paper proposes a Linear and Fast-paced recovery centred Transaction commit (LIFT) protocol to improve the existing recovery mechanism of linear 2PC by allowing autonomy to the participating cohorts to inform the cohort-in-doubt about the distributed transaction’s state instead of always looking for coordinator’s stand. The performance results confirm that proposed protocol will be a better alternative.

Read atomic transactions with prevention of lost updates: ROLA and its formal analysis

Abstract Designers of distributed database systems face the choice between stronger consistency guarantees and better performance. A number of applications only require read atomicity (RA) (either all or none of a transaction’s updates are visible to other transactions) and prevention of lost updates (PLU). Existing distributed transaction systems that meet these requirements also provide additional stronger consistency guarantees (such as causal consistency ), but this comes at the price of lower performance. In this paper we propose a new distributed transaction protocol, ROLA, that targets application scenarios where only RA and PLU are needed. We formally specify ROLA in Maude. We then perform model checking to analyze both the correctness and the performance of ROLA. For correctness, we use standard model checking to analyze ROLA’s satisfaction of RA and PLU. To analyze performance we: (a) perform statistical model checking to analyze key performance properties; and (b) compare these performance results with those obtained by also modeling and analyzing in Maude the well-known protocols Walter and Jessy that also guarantee RA and PLU. Our statistical model checking results show that ROLA outperforms both Walter and Jessy.

Scalable Linear Algebra on a Relational Database System

As data analytics has become an important application for modern data management systems, a new category of data management system has appeared recently: the scalable linear algebra system. In this paper, we argue that a parallel or distributed database system is actually an excellent platform upon which to build such functionality. Most relational systems already have support for cost-based optimization-which is vital to scaling linear algebra computations-and it is well-known how to make relational systems scale. We show that by making just a few changes to a parallel/distributed relational database system, such a system can be a competitive platform for scalable linear algebra. Taken together, our results should at least raise the possibility that brand new systems designed from the ground up to support scalable linear algebra are not absolutely necessary, and that such systems could instead be built on top of existing relational technology. Our results also suggest that if scalable linear algebra is to be added to a modern dataflow platform such as Spark, they should be added on top of the system's more structured (relational) data abstractions, rather than being constructed directly on top of the system's raw dataflow operators.

Fault-tolerant precise data access on distributed log-structured merge-tree

Log-structured merge tree has been adopted by many distributed storage systems. It decomposes a large database into multiple parts: an in-writing part and several read-only ones. Records are firstly written into a memory-optimized structure and then compacted into in-disk structures periodically. It achieves high write throughput. However, it brings side effect that read requests have to go through multiple structures to find the required record. In a distributed database system, different parts of the LSM-tree are stored in distributed fashion. To this end, a server in the query layer has to issues multiple network communications to pull data items from the underlying storage layer. Coming to its rescue, this work proposes a precise data access strategy which includes: an efficient structure with low maintaining overhead designed to test whether a record exists in the in-writing part of the LSM-tree; a lease-based synchronization strategy proposed to maintain consistent copies of the structure on remote query servers.We further prove the technique is capable of working robustly when the LSM-Tree is re-organizing multiple structures in the backend. It is also fault-tolerant, which is able to recover the structures used in data access after node failures happen. Experiments using the YCSB benchmark show that the solution has 6x throughput improvement over existing methods.

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

SummaryAs 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.

Non‐blocking two‐phase commit using blockchain

SummaryThe two‐phase commit (2PC) protocol has long been known to have a provably inevitable vulnerability to blocking or non‐progress amidst server crashes, even when the distributed database system guarantees the most demanding timing‐related or “synchrony” requirements. Our aim here is to eliminate this vulnerability by using a blockchain for coordinating 2PC execution. We present the impossibilities, the possibilities, the cost, and the trade‐offs in this blockchain‐based approach to blocking‐free management of distributed transactions. We prove that a non‐blocking and blockchain‐coordinated 2PC protocol can exist only if both the blockchain and distributed database systems meet synchrony requirements; otherwise, although blocking remains eliminated, transactions can unnecessarily abort. We present a blockchain‐coordinated 2PC protocol and provide rigorous arguments for its correctness under the synchrony requirements. We then implement this protocol on the Ethereum Testnet and demonstrate, through our experiments, that the monetary cost of executing smart contracts is quite small, that the protocol performance slows down when using a public blockchain like Ethereum, and that even major violations of synchrony requirements lead only to relatively small increases in unnecessary aborts. We thus identify a trade‐off between improving protocol performance and admitting a risk that transactions could occasionally abort unnecessarily.

Privacy-Preserving Secure Computation of Skyline Query in Distributed Multi-Party Databases

Selecting representative objects from a large-scale database is an essential task to understand the database. A skyline query is one of the popular methods for selecting representative objects. It retrieves a set of non-dominated objects. In this paper, we consider a distributed algorithm for computing skyline, which is efficient enough to handle “big data”. We have noticed the importance of “big data” and want to use it. On the other hand, we must take care of its privacy. In conventional distributed algorithms for computing a skyline query, we must disclose the sensitive values of each object of a private database to another for comparison. Therefore, the privacy of the objects is not preserved. However, such disclosures of sensitive information in conventional distributed database systems are not allowed in the modern privacy-aware computing environment. Recently several privacy-preserving skyline computation frameworks have been introduced. However, most of them use computationally expensive secure comparison protocol for comparing homomorphically encrypted data. In this work, we propose a novel and efficient approach for computing the skyline in a secure multi-party computing environment without disclosing the individual attributes’ value of the objects. We use a secure multi-party sorting protocol that uses the homomorphic encryption in the semi-honest adversary model for transforming each attribute value of the objects without changing their order on each attribute. To compute skyline we use the order of the objects on each attribute for comparing the dominance relationship among the objects. The security analysis confirms that the proposed framework can achieve multi-party skyline computation without leaking the sensitive attribute value to others. Besides that, our experimental results also validate the effectiveness and scalability of the proposed privacy-preserving skyline computation framework.

A Survey on Efficient Concurrency Control Algorithm in Distributed Database Systems

Transaction commit protocols help in reaching an agreement among the participating nodes when a transaction has to be committed or aborted. To initiate an agreement each participating node is asked to vote its decision on the operations on its transactional fragment. The participating nodes can decide to either commit or abort an ongoing transaction. In case of a node failure, the active participants take essential steps such as running the termination protocol to preserve database correctness. This paper sought to investigate the current distributed databases commit protocols such as 2PC and 3PC in order to pin-point their shortcomings. For instance, 2PC suffers from blocking of participant site in case of coordinator failure and increased latency due to forced writes of logs. On its part, 3PC suffers more communication overhead due to extra pre-commit phase. Based on these setbacks, an efficient protocol is suggested towards the end of this paper that it believed to address some of the challenges such as blocking and extra message exchange between communicating nodes.

Query optimization mechanisms in the cloud environments: A systematic study

SummaryThe goal of a query optimizer is to provide an optimal Query Execution Plan (QEP) by comparing alternative query plans. In a distributed database system over cloud environment, the relations required by a query plan may be stored at multiple sites. This leads to an exponential increase in the number of possible equivalent plan alternatives to find an optimal QEP. Although it is not computationally reasonable to explore exhaustively all possible plans in such large search space. Although query optimization mechanisms are important in the cloud environments, to the best of our knowledge, there exists no complete and systematic review on investigating these issues. Therefore, in this paper, four categories to study these mechanisms are considered which are search‐based, machine learning‐based, schema‐based, and security‐based mechanisms. Also, this paper represents the advantages and disadvantages of the selected query optimization techniques and investigates the metrics of their techniques. Finally, the important challenges of these techniques are reviewed to develop more efficient query optimization techniques in the future.

Towards an Efficient Data Fragmentation, Allocation, and Clustering Approach in a Distributed Environment

Data fragmentation and allocation has for long proven to be an efficient technique for improving the performance of distributed database systems’ (DDBSs). A crucial feature of any successful DDBS design revolves around placing an intrinsic emphasis on minimizing transmission costs (TC). This work; therefore, focuses on improving distribution performance based on transmission cost minimization. To do so, data fragmentation and allocation techniques are utilized in this work along with investigating several data replication scenarios. Moreover, site clustering is leveraged with the aim of producing a minimum possible number of highly balanced clusters. By doing so, TC is proved to be immensely reduced, as depicted in performance evaluation. DDBS performance is measured using TC objective function. An inclusive evaluation has been made in a simulated environment, and the compared results have demonstrated the superiority and efficacy of the proposed approach on reducing TC.

Online Motor Vehicle Licensing System Using RBAC Mechanism

Motor vehicle administration is a composite process and revolves around the management and the control of motor licensing.Motor vehicle licensing is the payment of a fee for the use of motor vehicles on public roads. Motor vehicle licensing in Nigeriabegan over 100 years ago starting from the colonial administration and the records then were manually kept which did not help inraising the efficiency of the general automotive services. The current process of motor vehicle licensing is being operated manually and due to this procedure, numerous problems are been encountered. This study seeks to develop a software that linksall the procedures of the motor vehicle licensing system in motor license authority in the manual system of motor vehicleregistration and introduces a better system which is the computerized system that will contribute to providing solutions to theproblems in the manual system. This work was designed to aid the framework for a client-server distributed database system forlicensing and registration of automobiles in Nigeria online. The system was implemented using PHP scripting language, HTML,MySQL Server, and Macromedia Dreamweaver. This study highly recommends that the motor vehicle licensing office should setup a computer-based system and more research done to perfect and make it more useful.

Security Framework for Distributed Database System

This research aims to study various Symmetrical Algorithms, while the main objective of this study is to find out a suitable algorithm for the encryption of any specific size of text file where the experiment of each algorithm is based on encryption of different sizes of the text files, which are in “10 KB to 5 MB”, and also to calculate the time duration that each algorithm takes to encrypt or to decrypt the particular size of each text file. There are many types of encryption algorithm, which can be used to encrypt the computerized information in different Organizations, whose all algorithms can encrypt and decrypt any size of text file, but the time duration of each Algorithm during the encryption or decryption process of specific file size is not fixed. Some of the algorithms are suitable for encryption of specific ranges of the file size, or some of algorithms are functional while encryption small size of files, and others algorithms are functional for encryption of big size of text files, based on the time duration disparity among symmetric algorithms during encryption of text files. In this study five symmetrical algorithms are merged in one program using classes and concept of inheritance in the form that if encryption is needed, the program will select the file and it checks the size of the text file. After this process the program automatically will select the suitable encryption algorithm to encrypt the specific text file according to the range of the file size. Knowing that the file size before or after encryption will not change or is stable, in this case of the decryption algorithm will apply the same process of encryption while decrypting files, the program of encryption and decryption code will write using visual Studio 2013. The result will be analyzed with R program (R software), the cipher text will appear in the format of UTF8 which means Unicode Transformation Format, “8” Means “8” bits to represent a character, the size format that will apply in the program will be in format of KB (kilo Byte).

An adaptive multi-level caching strategy for Distributed Database System

The Internet of Things (IoT) has become a promising technology for addressing societal and industrial challenges by connecting geo-distributed and diverse devices to create smart systems worldwide. Nowadays, Distributed Database Systems (DDBS) are widely used in Internet of Things (IoT) frameworks to improve performance of massive data access. However, most recent caching techniques focus on collaborative caching and neglect the unbalanced workloads on hot data nodes, which may potentially become a bottleneck of latency-sensitive IoT services. To tackle this issue, we propose an adaptive multi-level caching strategy to solve the performance bottleneck caused by hot data access and therefore improve data access performance in DDBS. The essential idea of our strategy is to dynamically adjust cache resource allocation and cache size in different data nodes according to realtime access rate. In this way, more resources could be allocated to hot data node to speed up queries and eliminate the bottleneck. In addition, instead of the traditional Least Recently Used (LRU) algorithm, an efficient cache replacement algorithm is also proposed and implemented in our DDBS. The testbed experimental results indicate that the performance of DDBS with our adaptive multi-level caching strategy can be significantly improved by 20% compared with traditional strategies.

A study of Concurrent transaction execution and their problems in Distributed Database System

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

Analysis of Energy Consumption for a Distributed Database System Using Smartphone in Cellular Network

Analysis of Energy Consumption for a Distributed Database System Using Smartphone in Cellular Network

Framework for Distributed Database System Using Smart Phone in Cellular Network

Framework for Distributed Database System Using Smart Phone in Cellular Network

Managing Database Replication Using Binary Vote Assignment on Grid Quorum with Association Rule

Nowadays, many organizations deploy the database application systems in order to manage their business operation. Administrations is required to deliver up to date data to users who live distantly, thus replicated databases can be one solution to increase the business operations performance in the distributed environment. Even though data availability is increased, common existing replication strategies neglect the correlation among the different data files in a Distributed Database Systems. In this paper, Binary Vote Assignment on Grid Quorum with Association Rules (BVAGQ-AR) has been proposed to manage the database replication. This technique combines data replication and data mining approaches in order to decrease the job processing time. The result shows that BVAGQ-AR has the lowest job processing time compared to other techniques. BVAGQ-AR performs 66.548 ms to complete a transaction compared to BRS with 137.157 ms, HRS with 257.928 ms, and ROWA with 262.243 ms. From the results, it is proved that managing replication and transaction through the proposed BVAGQ-AR able to preserve data consistency with low job processing time.

Differential bond energy algorithm for optimal vertical fragmentation of distributed databases

Distributed database systems are gaining importance due to the production in massive amount of data. The efficacy of such systems is highly dependent upon the design of the system. To increase the effectiveness and efficiency of distributed databases, two processes are mainly employed i.e. fragmentation and allocation. Fragmentations can be vertical or horizontal. This work focuses on vertical fragmentation design methods. In this paper, a novel differential bond energy (DBE) algorithm is proposed with objective to determine optimal partition point. The performance of proposed algorithm is compared with classical bond energy algorithm (BEA) on basis of global affinity measure (GAM) value. Results are depicted in form of line graphs. The mean difference in GAM values for both algorithms are also illustrated. The experimental results portrays that DBE is suitable for vertical fragmentation of high dimensional problems as it attain high GAM value as compared to BEA on various datasets.