Improved Integrity Constraints Checking in Distributed Databases by Exploiting Local Checking

Most of the previous studies concerning checking the integrity constraints in distributed database derive simplified forms of the initial integrity constraints with the sufficiency property, since the sufficient test is known to be cheaper than the complete test and its initial integrity constraint as it involves less data to be transferred across the network and can always be evaluated at the target site （single site）. Their studies are limited as they depend strictly on the assumption that an update operation will be executed at a site where the relation specified in the update operation is located, which is not always true. Hence, the sufficient test, which is proven to be local test by previous study, is no longer appropriate. This paper proposes an approach to checking integrity constraints in a distributed database by utilizing as much as possible the local information stored at the target site. The proposed approach derives support tests as an alternative to the existing complete and sufficient tests proposed by previous researchers with the intention to increase the number of local checking regardless the location of the submitted update operation. Several analyses have been performed to evaluate the proposed approach, and the results show that support tests can benefit the distributed database, where local constraint checking can be achieved.

An adaptive strategy for statistics collecting in distributed database

Collecting statistics is a time-and resource-consuming operation in database systems.It is even more challenging to efficiently collect statistics without affecting system performance,meanwhile keeping correctness in distributed database.Traditional strategies usually consider one dimension during collecting statistics,which is lack of adaptiveness.In this paper,we propose an adaptive strategy for statistics collecting(ASC),which well balances collecting efficiency,correctness of statistics and effect to system performance.We formally define the procedure of collecting statistics and abstract the relationships among collecting efficiency,correctness of statistics and effect to system performance,and introduce an elastic structure(ESI)storing necessary information generated during proceeding our strategy.ASC can pick appropriate time to trigger collecting action and filter unnecessary tasks,meanwhile reasonably allocating collecting tasks to appropriate executing locations with right executing models through the information stored at ESI.We implement and evaluate our strategy in a distributed database.Experiments show that our solutions generally improve the efficiency and correctness of collecting statistics,moreover,reduce the negative effect to system performance comparing with other strategies.

Use of Component Integration Services in Multidatabase Systems: A Feasible Solution for Integrating Academic Institutions or Commercial Industries

The book chapter is an extended version of the research paper entitled “Use of Component Integration Services in Multidatabase Systems”, which is presented and published by the 13th ISITA, the National Conference of Recent Trends in Mathematical and Computer Sciences, T.M.B. University, Bhagalpur, India, January 3-4, 2015. Information is widely distributed across many remote, distributed, and autonomous databases (local component databases) in heterogeneous formats. The integration of heterogeneous remote databases is a difficult task, and it has already been addressed by several projects to certain extents. In this chapter, we have discussed how to integrate heterogeneous distributed local relational databases because of their simplicity, excellent security, performance, power, flexibility, data independence, support for new hardware technologies, and spread across the globe. We have also discussed how to constitute a global conceptual schema in the multidatabase system using Sybase Adaptive Server Enterprise’s Component Integration Services (CIS) and OmniConnect. This is feasible for higher education institutions and commercial industries as well. Considering the higher educational institutions, the CIS will improve IT integration for educational institutions with their subsidiaries or with other institutions within the country and abroad in terms of educational management, teaching, learning, and research, including promoting international students’ academic integration, collaboration, and governance. This will prove an innovative strategy to support the modernization and large expansion of academic institutions. This will be considered IT-institutional alignment within a higher education context. This will also support achieving one of the sustainable development goals set by the United Nations: “Goal 4: ensure inclusive and quality education for all and promote lifelong learning”. However, the process of IT integration into higher educational institutions must be thoroughly evaluated, identifying the vital data access points. In this chapter, Section 1 provides an introduction, including the evolution of various database systems, data models, and the emergence of multidatabase systems and their importance. Section 2 discusses component integration services (CIS), OmniConnect and considering heterogeneous relational distributed local databases from the perspective of academics, Section 3 discusses the Sybase Adaptive Server Enterprise (ASE), Section 4 discusses the role of component integration services and OmniConnect of Sybase ASE under the Multidatabase System, Section 5 shows the database architectural framework, Section 6 provides an implementation overview of the global conceptual schema in the multidatabase system, Section 7 discusses query processing in the CIS, and finally, Section 8 concludes the chapter. The chapter will help our students a lot, as we have discussed well the evolution of databases and data models and the emergence of multidatabases. Since some additional useful information is cited, the source of information for each citation is properly mentioned in the references column.

A dynamic crash recovery scheme for distributed real-time database systems

Recovery performance in the event of failures is very important for distributed real-time database systems. This paper presents a time-cognizant logging-based crash recovery scheme （TCLCRS） that aims at distributed real-time databases, which adopts a main memory database as its ground support. In our scheme, each site maintains a real-time log for local transactions and the subtransactions, which execute at the site, and execte local checkpointing independently. Log records are stored in non-volatile high- speed store, which is divided into four different partitions based on transaction classes. During restart recovery after a site crash, partitioned crash recovery strategy is adopted to ensure that the site can be brought up before the entire local secondary database is reloaded in main memory. The partitioned crash recovery strategy not only guarantees the internal consistency to be recovered, but also guarantee the temporal consistency and recovery of the sates of physical world influenced by uncommitted transactions. Combined with two- phase commit protocol, TCLCRS can guarantee failure atomicity of distributed real-time transactions.

Weak Serializable Concurrency Control in Distributed Real-Time Database Systems

Most of the proposed concurrency control protocols for real time database systems are based on serializability theorem. Owing to the unique characteristics of real time database applications and the importance of satisfying the timing constraints of transactions, serializability is too strong as a correctness criterion and not suitable for real time databases in most cases. On the other hand, relaxed serializability including epsilon serializability and similarity serializability can allow more real time transactions to satisfy their timing constraints, but database consistency may be sacrificed to some extent. We thus propose the use of weak serializability(WSR) that is more relaxed than conflicting serializability while database consistency is maintained. In this paper, we first formally define the new notion of correctness called weak serializability. After the necessary and sufficient conditions for weak serializability are shown, corresponding concurrency control protocol WDHP(weak serializable distributed high priority protocol) is outlined for distributed real time databases, where a new lock mode called mask lock mode is proposed for simplifying the condition of global consistency. Finally, through a series of simulation studies, it is shown that using the new concurrency control protocol the performance of distributed real time databases can be greatly improved.

An architecture for mobile database management system

In order to design a new kind of mobile database management system (DBMS)more suitable for mobile computing than the existent DBMS, the essence of database systems in mobilecomputing is analyzed. An opinion is introduced that the mobile database is a kind of dynamicdistributed database, and the concept of virtual servers to translate the clients' mobility to theservers' mobility is proposed. Based on these opinions, a kind of architecture of mobile DBMS, whichis of versatility, is presented. The architecture is composed of a virtual server and a local DBMS,the virtual server is the kernel of the architecture and its functions are described. Eventually,the server kernel of a mobile DBMS prototype is illustrated.

A Distribution Management System for Relational Databases in Cloud Environments

For a transaction processing system to operate effectively and efficiently in cloud environments, it is important to distribute huge amount of data while guaranteeing the ACID （atomic, consistent, isolated, and durable） properties. Moreover, database partition and migration tools can help transplanting conventional relational database systems to the cloud environment rather than rebuilding a new system. This paper proposes a database distribution management （DBDM） system, which partitions or replicates the data according to the transaction behaviors of the application system. The principle strategy of DBDM is to keep together the data used in a single transaction, and thus, avoiding massive transmission of records in join operations. The proposed system has been implemented successfully. The preliminary experiments show that the DBDM performs the database partition and migration effectively. Also, the DBDM system is modularly designed to adapt to different database management system （DBMS） or different partition algorithms.

A Distributed DBMS Based Dynamic Programming Method for Query Optimization

Dynamic programming(DP) is an effective query optimization approach to select an appropriate join order for relational database management system(RDBMS) in multi-table joins. This method was extended and made available in distributed DBMS(D-DBMS). The structure of this optimal solution was firstly characterized according to the distributing status of tables and data, and then the recurrence relations between a problem and its sub-problems were recursively defined. DP in D-DBMS has the same time-complexity with that in centralized DBMS, while it has the capability to solve a much more sophisticated optimal problem of multi-table join in D-DBMS. The effectiveness of this optimal strategy has been proved by experiments.

Designing a Model to Study Data Mining in Distributed Environment

To make business policy, market analysis, corporate decision, fraud detection, etc., we have to analyze and work with huge amount of data. Generally, such data are taken from different sources. Researchers are using data mining to perform such tasks. Data mining techniques are used to find hidden information from large data source. Data mining is using for various fields: Artificial intelligence, Bank, health and medical, corruption, legal issues, corporate business, marketing, etc. Special interest is given to associate rules, data mining algorithms, decision tree and distributed approach. Data is becoming larger and spreading geographically. So it is difficult to find better result from only a central data source. For knowledge discovery, we have to work with distributed database. On the other hand, security and privacy considerations are also another factor for de-motivation of working with centralized data. For this reason, distributed database is essential for future processing. In this paper, we have proposed a framework to study data mining in distributed environment. The paper presents a framework to bring out actionable knowledge. We have shown some level by which we can generate actionable knowledge. Possible tools and technique for these levels are discussed.

Trustworthiness Technologies of DDSS

The most significant strategic development in information technology over the past years has been ＂trusted computing＂ and trusted computers have been produced. In this paper trusted mechanisms adopted by PC is imported into distributed system, such as chain of trust, trusted root and so on. Based on distributed database server system （DDSS）, a novel model of trusted distributed database server system （TDDSS） is presented ultimately. In TDDSS role-based access control, two-level of logs and other technologies are adopted to ensure the trustworthiness of the system.

Scalable and adaptive log manager in distributed systems

On-line transaction processing(OLTP)systems rely on transaction logging and quorum-based consensus protocol to guarantee durability,high availability and strong consistency.This makes the log manager a key component of distributed database management systems(DDBMSs).The leader of DDBMSs commonly adopts a centralized logging method to writing log entries into a stable storage device and uses a constant log replication strategy to periodically synchronize its state to followers.With the advent of new hardware and high parallelism of transaction processing,the traditional centralized design of logging limits scalability,and the constant trigger condition of replication can not always maintain optimal performance under dynamic workloads.In this paper,we propose a new log manager named Salmo with scalable logging and adaptive replication for distributed database systems.The scalable logging eliminates centralized contention by utilizing a highly concurrent data structure and speedy log hole tracking.The kernel of adaptive replication is an adaptive log shipping method,which dynamically adjusts the number of log entries transmitted between leader and followers based on the real-time workload.We implemented and evaluated Salmo in the open-sourced transaction processing systems Cedar and DBx1000.Experimental results show that Salmo scales well by increasing the number of working threads,improves peak throughput by 1.56×and reduces latency by more than 4×over log replication of Raft,and maintains efficient and stable performance under dynamic workloads all the time.

CIMBASE: A Multidatabase Integration Environment

The integration of heterogeneous multidatabases on a network is one of the key issues to be sofved in thedevelopment of CIMS (computer integrated manufacturing system). As a solution to this issue, a multidatabase integration environment, CIMBASE, has been developed. CIMBASE adopts an object-oriented data model and provides users with a series of software tools: a query language, a pre-compiler, a graphical database schema editor,a graphical query interface and a form based query generation tool.This paper discusses in detail the major aspectsof CIMBASE: its object-oriented data model, query language interpreter and the design and implementation of itsprc-compiler. The design and algorithms presented in this paper provide a solid foundation for research on multidatabase integration.

The Catalog Management Strategy of Distributed Data Base Systems

In this paper the catalog management strategy of the successfully integrating andrunning DDBMS C-POREL is summarized. The new catalog management strategyand its implementation scheme are based on the analysis of the catalog managementmethods of the pioneer DDBMS. The goal of the new strategy is to improve the systemefficiency. Analysis and practice show that this strategy is successful.

GDM： A New Graph Based Data Model Using Functional Abstractionx

In this paper, a Graph-based semantic Data Model （GDM） is proposed with the primary objective of bridging the gap between the human perception of an enterprise and the needs of computing infrastructure to organize information in some particular manner for efficient storage and retrieval. The Graph Data Model （GDM） has been proposed as an alternative data model to combine the advantages of the relational model with the positive features of semantic data models. The proposed GDM offers a structural representation for interacting to the designer, making it always easy to comprehend the complex relations amongst basic data items. GDM allows an entire database to be viewed as a Graph （V, E） in a layered organization. Here, a graph is created in a bottom up fashion where V represents the basic instances of data or a functionally abstracted module, called primary semantic group （PSG） and secondary semantic group （SSG）. An edge in the model implies the relationship among the secondary semantic groups. The contents of the lowest layer are the semantically grouped data values in the form of primary semantic groups. The SSGs are nothing but the higher-level abstraction and are created by the method of encapsulation of various PSGs, SSGs and basic data elements. This encapsulation methodology to provide a higher-level abstraction continues generating various secondary semantic groups until the designer thinks that it is sufficient to declare the actual problem domain. GDM, thus, uses standard abstractions available in a semantic data model with a structural representation in terms of a graph. The operations on the data model are formalized in the proposed graph algebra. A Graph Query Language （GQL） is also developed, maintaining similarity with the widely accepted user-friendly SQL. Finally, the paper also presents the methodology to make this GDM compatible with the distributed environment, and a corresponding query processing technique for distributed environment is also suggested for the sake of completeness.

Location-Based Data Dissemination for Spatial Queries in Wireless Broadcast Environments

Most current research on Location-Based Services （LBSs, for short） assumes point-to-point wireless commu- nication, where the server processes a query and returns the query result to the user via a point-to-point wireless channel. However, LBSs via point-to-point wireless channel suffer from a tremendous amount of tramc and service requests from the user and thereby result in poor performance. In this paper, we present broadcast-based spatial query processing algorithms designed to support k-NN （k-Nearest Neighbor） and range queries via a wireless network. The task of the query processor is to selectively monitor the wireless broadcast channel, when the data items are disseminated by the server, according to their locations. Experiments are conducted to evaluate the performance of the proposed algorithms. Comprehensive experiments illustrate that the presented algorithms are highly scalable and are more efficient than the previous techniques in terms of both access time and energy consumption.

TIFAflow: Enhancing Traffic Archiving System with Flow Granularity for Forensic Analysis in Network Security

The archiving of Internet traffic is an essential function for retrospective network event analysis and forensic computer communication. The state-of-the-art approach for network monitoring and analysis involves storage and analysis of network flow statistic. However, this approach loses much valuable information within the Internet traffic. With the advancement of commodity hardware, in particular the volume of storage devices and the speed of interconnect technologies used in network adapter cards and multi-core processors, it is now possible to capture 10 Gbps and beyond real-time network traffic using a commodity computer, such as n2disk. Also with the advancement of distributed file system （such as Hadoop, ZFS, etc.） and open cloud computing platform （such as OpenStack, CloudStack, and Eucalyptus, etc.）, it is practical to store such large volume of traffic data and fully in-depth analyse the inside communication within an acceptable latency. In this paper, based on well- known TimeMachine, we present TIFAflow, the design and implementation of a novel system for archiving and querying network flows. Firstly, we enhance the traffic archiving system named TImemachine＋FAstbit （TIFA） with flow granularity, i.e., supply the system with flow table and flow module. Secondly, based on real network traces, we conduct performance comparison experiments of TIFAflow with other implementations such as common database solution, TimeMachine and TIFA system. Finally, based on comparison results, we demonstrate that TIFAflow has a higher performance improvement in storing and querying performance than TimeMachine and TIFA, both in time and space metrics.

A Non-Blocking Locking Method and Performance Evaluation on Network of Workstations

network of workstation (NOW) can act as a single and scalable powerful computer by building a parallel and distributed computing platformon top of it. WAKASHI is such a platform system that supports persistent objectmanagement and makes full use of resources of NOW for high performance transaction processing. One of the main difficulties to overcome is the bottleneck causedby concurrency control mechanism. Therefore, a non-blocking locking method isdesigned, by adopting several novel techniques to make it outperform the other typical locking methods such as 2PL: 1) an SDG (Semantic Dependency Graph) basednon-blocking locking protocol for fast transaction scheduling; 2) a massively virtualmemory based backup-page undo algorithm for fast restart; and 3) a multi-processorand multi-thread based transaction manager for fast execution. The new mechanismshave been implemented in WAKASHI and the performance comparison experimentswith 2PL and DWDL have been done. The results show that the new method canoutperform 2PL and DWDL under certain conditions. This is meaningful for Choosing effective concurrency control mechanisms for improving transaction- processingperformance in NOW environments.