Distributed 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.

Distributed Database Systems for Large-Scale Data Management

Distributed database systems are essential to modern computing. Such infrastructures offer scalability, speed, fault tolerance, and security, enabling applications to analyse massive data volumes in real time. Some of the difficulties in designing and maintaining a distributed database system include data consistency, performance, security, scalability, complexity, and cost. A distributed database system must be carefully planned, constructed, and managed in order to address these problems. It also has to be constantly monitored and maintained in order to provide the highest levels of performance and security. Distributed databases provide a wide range of applications in these fields and more, despite the difficulties posed by sectors like e-commerce, social networking, healthcare, the Internet of Things (IoT), online gaming, financial services, and logistics. Distributed database systems will become more and more crucial in allowing real-time data processing and analytics as well as aiding the creation of new applications and services as the volume and complexity of data keep rising. In today's computer applications, the benefits of using a distributed database system for managing and analysing massive amounts of data far outweigh the drawbacks.

The NDNS PERFORMANCE WITH VARIATION OF TOPOLOGY AND PREFIX ON NAMED DATA NETWORKING

NDNS is DNS embedded in Named Data Network (NDN) architecture as a distributed database system to support NDN caching and know the content's location. In this research, the simulation performed using two topologies, Abilene and PAN-Europe with changes to their prefixes. This simulation conducted to see performance of NDNS with minimal ability to cache on NDN router or Caching Resolver. From simulation results, the variation of prefix at Second Level Domain and Top Level Domain there is no difference in average delay in both topologies, namely 1% increase in average delay as the variation of prefix increases. There is a decrease in the Cache Hit Ratio by 0.16% (Abilene) and 0.18% (PAN-Europe) because the probability of getting cached data decreases as the prefix varies. In the change in interest frequency, there is an increase of 0.4% in average delay and the Cache Hit Ratio decreases by 0.08% in both topologies as the frequency of interest per second increases. NDNS with cache in Router and Caching Resolver get 43% lower average delay (Abilene) and 44% (PAN-Europe) than NDN with cache in Router and 57% lower (Abilene) and 60% (PAN-Europe) than NDNS with cache in Caching Resolver only.

An automate failure recovery for synchronous distributed database system

Periodically, researchers have been sharing their constant attempts to improve the existing methods for data replication in distributed database system. The main goal is to work for an efficient distributed environment. An efficient environment may handle huge amount of data and preserve data availability. The occasionally failures in distributed systems will affect the end results, such as data loss, income loss etc. Thus, to prevent the data loss and guarantee the continuity of the business, many organizations have applied disaster recovery solutions in their system. One of the widely used is database replication, because it guarantees data safety and availability. However, disaster still can occur in database replication. Hence, an automatic failure recovery technique called distributed database replication with fault tolerance (DDR-FT) has been proposed in this research. DDR-FT uses heartbeat message for node monitoring. Subsequently, a foundation of binary vote assignment for fragmented database (BVAFD) replication technique has been used. In DDR-FT, the data nodes are continuously monitored while auto reconfiguring for automatic failure recovery. From the conducted experiments, it is proved that DDR-FT can preserve system availability. It shows that DDR-FT technique provides a convenient approach to system availability for distributed database replication in real time environment.

Design of Distributed Database System Based on Improved DES Algorithm

Design of Distributed Database System Based on Improved DES Algorithm

Evaluation of Hash Join Operations Performance Executing on SDN Switches: A Cost Model Approach

Distributed database systems store and manipulate data on multiple machines. In these systems, the processing cost of query operations is mainly impacted by the data access latency between machines over the network. With recent technology advances in programmable network devices, the network switches provide new opportunities for dynamically managing the network topology, enabling the data processing on these devices with the same network throughput. In this paper, we explore the programmable network switches in query processing, evaluating the processing performance of a cost model in executing the hash join operation. We assume the storage of the hash table built from outer relation and the materialization of the join probing are made in switches using advanced matching techniques similar to package inspections enabled by Ternary Content-Addressable Memories (TCAM) or SRAM via hashing. Our results show that processing the hash join operation using network switches achieved the best results compared to traditional servers, with an average time reduction of 91.82% (Query-10 from TPC-H) and 96.52% (Query-11 from TPC-H).

Optimization of University Archives Management under the Application of Blockchain Technology in the Digital Age

The centralized database can store a variety of electronic archives. Electronic archives face a variety of network attack vulnerabilities as information technology and network technology continue to advance. Furthermore, these archives will be readily forged and tampered with by internal management or external attackers. Data security and authenticity problems prevail in China’s management system for archives. First, this exploration elaborates the blockchain technology, distributed database technology, and distributed database system structure. Secondly, blockchain technology is applied to the authenticity protection of electronic archives. Then, an optimization model of university archives based on blockchain technology is constructed. Finally, this exploration investigates the current use of blockchain technology for college archive management systems. The questionnaire is used to understand the current university personnel’s views on the college archive management system under the application of blockchain. The survey results suggest that most people support the digital college archive management system. At present, the operation efficiency of the college archive management system still needs to be improved, and the quality of archives search should be promoted. Therefore, the college archive management system still needs to optimize the archive’s efficiency as well as quality. According to the above survey results, this investigation gives suggestions for optimizing the college archive management system using blockchain technology, as well as some suggestions and references for further management.

Proof-of-Useful-Work: BlockChain Mining by Solving Real-Life Optimization Problems

Blockchains (BCs) are distributed database systems, popular for their innovative, unsupervised maintenance process. They use a so-called consensus protocol to prevent inference by any third party of absolute trust. Security, privacy, consistency, and energy consumption have been identified as the main issues involved in BC maintenance. According to the recent literature, some of these issues can be formulated as combinatorial optimization (CO) problems, and this fact motivated us to consider incorporating CO approaches into a BC. In this paper, we propose the new combinatorial optimization consensus protocol (COCP) based on the proof-of-useful-work (PoUW) concept that assumes solving instances of real-life CO problems. Due to the complexity of the underlying CO problems, we have developed various types of heuristic methods, which are utilized in the COCP. Most of these methods are problem-dependent stochastic heuristic or metaheuristic methods. As is the case with the majority of consensus protocols, PoUW exhibits the property of asymmetry. It is difficult to find a solution for the considered CO problem; however, once a solution is found, its verification is straightforward. We present here a BC framework combining the two above-mentioned fields of research: BC and CO. This framework consists of improvements aiming towards developing the COCP of the PoUW type. The main advantage of this consensus protocol is the efficient utilization of computing resources (by exploring them for finding solutions of real-life CO problem instances), and the provision of a broad range of incentives for the various BC participants. We enumerate the potential benefits of the COCP with respect to its practical impacts and savings in power consumption, describing in detail an illustrative example based on part of the real-life BC network. In addition, we identify several challenges that should be resolved in order to implement a useful, secure, and efficient PoUW consensus protocol.

Artificial Intelligence for Demystifying Blockchain Technology Challenges: A Survey of Recent Advances

Blockchain technology has gained lots of traction in the past five years due to the innovations introduced in digital currency, the Bitcoin. This technology is powered by distributed ledger technology, which is a distributed database system. It is often renowned for decentralization, anti-attack, and unfalsified attributes making it a top choice in several non-monetary applications. In fact, the problem of privacy and security of the Internet of Things has been undertaken aggressively with Blockchain. Several problems have been identified with blockchain technology such as large delays and lack of support for real-time transaction processing, authorization, node verification, and consensus mechanisms. This article intends to provide a comprehensive survey on the recent advances and solutions to the problems of blockchain technology by leveraging the artificial intelligence approaches. The outcomes of this study will provide valuable information and guidance on the design of Blockchain-based systems to support time-sensitive and real-time specific applications and processes.

A two-part multi-algorithm concurrency control optimization strategy for distributed database systems

In this paper, we propose a novel holistic approach to address the issues of concurrency control after an exhaustive examination of the problem and the various forms it can transpire. The proposed strategy was formulated depending on different perspectives that are based on exploring a wide range of algorithms, methods, and strategies proposed in practice and theory that attempted to address the problem and its forms, but only partially succeeded in doing so. Here we proposed a two-part holistic strategy to optimize concurrency control in distributed environments that address a wide range of concurrency control anomalies by taking advantage of several concurrency control algorithms' strengths while minimizing their weaknesses. The novelty of our approach transpires from two interconnected parts that can be applied regardless of the type of distributed database environment. The first is a structured tier-based data classification system based on data sensitivity with respect to serializability requirements and ranges from strict to very relaxed forms of serializability constraints. The second is a concurrency management algorithm that allocates the appropriate concurrency control algorithm to each transaction depending on the type of transaction and/or type of data being accessed from the aforementioned tier-based classification method. Our proposed method also incorporates a priority allocation mechanism within the concurrency management algorithm. Priority is allocated to different tier transactions depending on the tier's level, which in turn reflects data importance and sensitivity. Although our proposed strategy remains an algorithmic approach as we encountered various challenges regarding performance testing of a novel multi-algorithm approach for handling concurrency control in distributed database systems. However, future work involves testing the performance of our proposed strategy either through real-time systems after considerable adjustments or by constructing an appropriate customized simulation framework. Finally, the potentials of the strategy presented here are very promising, hence, we recommend as we are also optimistic that other scholars are encouraged to further exploit the concept of using multiple concurrency control algorithms within the same distributed database environment.

Improving blockchain performance in clinical trials using intelligent optimal transaction traffic control mechanism in smart healthcare applications

Blockchain technology has revolutionized the ways of processing and storing data in terms of reliability and security. Blockchain plays a pivotal role in transferring the processing hurdle from the client–server to a decentralized and secured platform. Blockchain is deemed to be an efficient technology in a forthcoming era that would beneficiate multifarious industries. An issue that becomes a bottleneck for blockchain-based applications is their restricted ability to process in comparison to distributed database systems. In this paper, we present intelligent traffic control using a hybrid model based on the PSO-based optimization algorithm and fuzzy logic in order to improve blockchain performance. The real-time network feedback model is designed and used as an input to control the transaction traffic across the entire network in a robust way without human intervention. In order to evaluate the effectiveness of the designed model, a clinical trial service framework as a test network is implemented on top of Hyperledger Fabric. The case study is further compared with baseline network, network with fuzzy approach, and network with optimized parameter. The experiments show that the proposed model not only enhanced the network by maximizing the network throughput and minimizing the network latency. A smart contract is implemented to automate the transaction flow as per real-time data of network conditions. An open-source blockchain framework, Hyperledger Fabric, is harnessed for implementation of the experiment environment in order to signify the potential of the proposed model. The outcome of this study indicated a remarkable increase in transaction throughput (i.e., 38.5%) and a decrease in transaction latency of 40.5%. Moreover, the proposed model can easily be integrated with other existing blockchain-based performance-enhancing tools.

TAOBench

The continued emergence of large social network applications has introduced a scale of data and query volume that challenges the limits of existing data stores. However, few benchmarks accurately simulate these request patterns, leaving researchers in short supply of tools to evaluate and improve upon these systems. In this paper, we present a new benchmark, TAOBench, that captures the social graph workload at Meta. We open source workload configurations along with a benchmark that leverages these request features to both accurately model production workloads and generate emergent application behavior. We ensure the integrity of TAOBench's workloads by validating them against their production counterparts. We also describe several benchmark use cases at Meta and report results for five popular distributed database systems to demonstrate the benefits of using TAOBench to evaluate system tradeoffs as well as identify and address performance issues. Our benchmark fills a gap in the available tools and data that researchers and developers have to inform system design decisions.

Multi-Level Security Model Developed to Provide Data Privacy in Distributed Database Systems

Multi-Level Security Model Developed to Provide Data Privacy in Distributed Database Systems

Data Processing Method of Distributed Parallel Database System Based on Wireless Network

With the development of society and the arrival of the information age, data processing has become more and more complex, so people need to manage data systems through wireless communication, and distributed systems can effectively improve data analysis, so this paper is based on wireless communication. Distributed database systems are studied. With the rapid development of database systems, how to effectively obtain useful information about massive data has gradually become an important research problem of/with the field of data management. The purpose of this paper is to study how to research the data processing of distributed parallel database system based on wireless network. This paper puts forward the basic concepts of wireless network and distributed parallel database system and proposes a clustering analysis algorithm. The preimproved clustering analysis and the improved distributed parallel clustering analysis are described and compared in detail. From the data in the figure in the experimental part of the text, it can be seen that the efficiency of the database system before the improvement is the lowest at 41% and the highest at 58%. The efficiency of the improved distributed database system is at least 65%, and the highest are 95%. It can be seen that the efficiency of the improved distributed database system is much higher than that of the preimproved database system. So it is very feasible to use the distributed database system to process data.

A Transaction Traffic Control Approach Based on Fuzzy Logic to Improve Hyperledger Fabric Performance

Blockchain is a potential technology for migrating the central server’s processing burden into a decentralized, secure, and transparent manner. This technology has had significant influence and revolution in various industries. However, the limited transaction processing power is a stumbling block, especially compared to proven alternatives like distributed database systems. This paper proposes a transaction traffic control approach based on fuzzy logic to enhance the blockchain network’s transaction processing capacity. The proposed fuzzy controller is implemented in the smart contract to adjust the transaction traffic flow in real-time network conditions automatically. An experiment environment is built on Hyperledger Fabric to demonstrate the design approach’s significance. According to the experiment results, the blockchain performance is significantly improved compared to the baseline. Furthermore, the proposed approach is integrated with an existing blockchain performance-enhancing tool, and the results indicate that the proposed approach is flexible enough to integrate with other existing approaches.

Comparison Of Replication Strategies On Distributed Database Systems

Today's computer applications have ever-increasing database system capabilities and performance. The growing amount of data that has to be processed in a business company makes centralized data processing ineffective. This inefficiency shows itself as a long reaction time. This is in direct opposition to the purpose of utilizing databases in data processing, which is to reduce the amount of time it takes to process data. Another database design is required to tackle this problem. Distributed database technology refers to an architecture in which several servers are linked together, and each one may process and fulfill local queries. Each participating server is responsible for serving one or more requests. In a multi-master replication scenario, all sites are main sites, and all main sites communicate with one another. The distributed database system comprises numerous linked computers that work together as a single system.

Multi-level security model in distributed database systems

Multi-level security model in distributed database systems

A new secure 2PL real-time concurrency control algorithm (ES2PL)

A secure concurrency control algorithms must be devoid of covert channels originating from data conflicts between transactions, in addition to ensuring database integrity. Current secure concurrency control algorithms mistreat transactions with higher access classes. Because it better solves the priority inversion problem. A widely used concurrency control algorithm is the two-phase locking with high priority (2 PL-HP). The inclusion of cyclic restart, deadlock, unnecessary abort, pseudo-priority inversion, and starvation, on the other hand, may reduce its performance. In this paper, a new enhanced of secure two-phase locking protocol with multilevel secure distributed database systems is presented, the idea of enhanced secure Two-Phase locking protocol by adding the security level to assign the priority to the transaction. The enhanced add a secure manager to decide the level of the security and give the instruction to process the transaction in real lock with data x/virtual lock with version data x0 or decided to Abort the transaction based on the security level. The suggested study intends to reduce transaction miss rate by addressing the following issues: deadlock by splitting the execution stage into locking and processing phases, it reduces unnecessary cycle restart, transaction aborts by checking the security priority level (high, medium, low), and generating virtual lock and versions data. Finally, simulation performance confirms that improvement in transactions miss's percent and reduction in transactions' rollbacks compared to other secure concurrency control.

Design and Implementation of Ship Water Pollution Supervision and Service Information System

In order to improve the ship pollutant discharge monitoring system, control the ship pollutant discharge, establish a more convenient and efficient information communication channel for ship pollutant discharge and receiving services, a ship water pollution discharge system is designed and implemented. This system is divided into three workbenches, namely ship workbenches, enterprise workbenches and supervision workbenches. It is developed based on the front-end and back-end separation mode. The front-end uses Vue framework to implement page function, and Element UI to complete page UI design, Mapbox to display maps, and ECharts component to draw charts. The back-end is implemented through the Spring Boot framework. Redis is used for data caching to improve concurrency and provide data interfaces. Spring Security + JWT is used to achieve single sign on and permission control. The Nginx service gateway is used to achieve service load balancing. MySQL database is used to storage the water pollution discharge information. AIS historical data storage is realized through the distributed database system of Doris cluster.

A Gitbash-Generative Model for an Enhanced Query Processing In a Distributed Database System

This research study is directly focused on an enhanced query processing system using GitBash- Deep Generative Model, it is use to improve the performance of big data. Due to Poor query execution plan and absence of an improved aggregate query method which impose threats to qualities of good query processing in distributed databases which also cause memory pressure in a database, inflated central processing unit (CPU) and an overall reduction in concurrency. Also the volume of data use in any organization is progressively increasing in it seize, thereby resulting or demand a large storage location or space system. The availability of intended software that will confront the problem of storage contents and execution plan for query processing is a vital challenge facing big data in a processing system, which can prompt to information loss and missing record of vital document in an enterprises. The study will boost solution and addresses the problem of latencies, inability to transform and store queries, and poor query processing plans for future improvement of distributed databases, using an unsupervised learning approach such as deep generative model. The adopted methodology is dynamic system development method (DSDM). php programming language and mongoDB database is adopted for implementation. The datasets used for the proposed system was generated from e-library server/data.json (query) and is inserted into MongoDB database json format. The datasets are all trained and recognized by the Deep Generative algorithm through the Git Bash server. The proposed system result shows highly increase in the efficiency of management of big data and improved query processing. General Term Query Processing System Keywords Big Data, Deep Generative Model, Query Processing System, Information Management, Gitbash.