Improving Integrity Constraints Checking In Distributed Databases by Exploiting Local Checking

Integrity constraints are important tools and useful for specifying consistent states of a database. Checking integrity constraints has proven to be extremely difficult to implement, particularly in distributed database. The main issue concerning checking the integrity constraints in distributed database system is how to derive a set of integrity tests (simplified forms) that will reduce the amount of data transferred, the amount of data accessed, and the number of sites involved during the constraint checking process. Most of the previous approaches derive integrity tests (simplified forms) from the initial integrity constraints with the sufficiency property, since the sufficient test is known to be cheaper to execute than the complete test as it involved less data to be transferred across the network and always can be evaluated at the target site, i.e. only one site is involved during the checking process thus, achieving local checking. The previous approaches assume that an update operation will be executed at a site where the relation specified in the update operation is located (target site), which is not always true. If the update operation is submitted at a different site, the sufficient test is no longer local as it will definitely access data from the remote sites. Therefore, an approach is needed so that local checking can be performed regardless the location of the submitted update operation. In this thesis we proposed an approach for checking integrity constraints in a distributed database system by utilizing as much as possible the information stored at the target site. The proposed constraints simplification approach produces support tests and this is integrated with complete and sufficient tests which are proposed by previous researchers. It uses the initial integrity constraint, the update template, and the other integrity constraints to generate the support tests. The proposed constraints simplification approach adopted the substitution technique and the absorption rules to derive the tests. Since the constraint simplification approach derives several different types of integrity tests for a given update operation and integrity constraint, therefore a strategy to select the most suitable test is needed. We proposed a model to rank and select the suitable test to be checked based on the properties of the tests, the amount of data transferred across the network, the number of sites participated, and the amount of data accessed. Three analyses have been performed to evaluate the proposed checking integrity constraints approach. The first analysis shows that applying different types of integrity tests gives different impacts to the performance of the constraint checking, with respect to the amount of data transferred across the network which is considered as the most critical factor that influences the performance of the checking mechanism. Integrating these various types of integrity tests during constraint checking has enhanced the performance of the constraint mechanisms. The second analysis shows that the cost of checking integrity constraints is reduced when various combinations of integrity tests are selected. The third analysis shows that in most cases localizing integrity checking can be achieved regardless of the location where the update operation is executed when various types of integrity tests are considered

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

A framework for checking and ranking integrity constraints in a distributed database

The essential aim of a database system is to guarantee database consistency, which means that the data contained in a database is both accurate and valid. Checking the consistency of a database state generally involves the execution of integrity tests (query that returns the value true or false) on the database, which verify whether the database is satisfying its constraints or not. The process of checking integrity constraints has proved to be extremely difficult to implement, particularly in distributed database. This paper proposed a framework for checking integrity constraints in a distributed database by utilizing as much as possible the local information stored at the target site. The proposed framework consists of two main processes, namely: (i) simplify the integrity constraints to produce support tests and integrate them with complete and sufficient tests and (ii) select the most suitable test from several alternative tests when an update operation is submitted to the system. Including these processes in the proposed framework has optimized the process of checking the consistency of the distributed database by reducing the amount of data transferred across the network, the amount of data accessed, the number of sites involved, and the number of integrity constraints to be evaluated

A literature review on collaborative caching techniques in MANETs: issues and methods used in serving queries

Collaborative cache management in Mobile Ad Hoc Networks (MANETs) environment is considered as an efficient technique to increase data accessibility and availability, by sharing and coordination among mobile nodes. Due to nodes’ mobility, limited battery power and insufficient bandwidth, researchers addressed these challenges by developing many different collaborative caching schemes. The objective of this paper is to review various collaborative caching techniques in MANETs. Collaborative caching techniques are classified by methods used in serving queries, such as: hop-by-hop discovering, broadcasting messages, flooding, and query service differentiation. This review reveals that techniques utilizing hop-by-hop methods have better performance compared to others, especially techniques using additional strategies

An efficient approach for processing skyline queries in incomplete multidimensional database

In recent years, there has been great attention given to skyline queries that incorporate and provide more flexible query operators that return data items (skylines) which are not being dominated by other data items in all dimensions (attributes) of the database. Many variations in skyline techniques have been proposed in the literature. However, most of these techniques determine skylines by assuming that the values of all dimensions for every data item are available (complete). But this assumption is not always true particularly for large multidimensional database as some values may be missing (not applicable during the computation). In this paper, we proposed an efficient approach for processing skyline queries in incomplete database. The experimental results show that our proposed approach has significantly reduced the number of pairwise comparisons and the processing time in determining the skylines compared to the previous approaches

Performance evaluation of task scheduling using hybrid meta-heuristic in heterogeneous cloud environment

Cloud computing is a ubiquitous platform that offers a wide range of online services to clients including but not limited to information and software over the Internet. It is an essential role of cloud computing to enable sharing of resources on-demand over the network including servers, applications, storage, services, and database to the end-users who are remotely connected to the network. Task scheduling is one of the significant function in the cloud computing environment which plays a vital role to sustain the performance of the system and improve its efficiency. Task scheduling is considered as an NP-complete problem in many contexts, however, the heterogeneity of resources in the cloud environment negatively influence on the job scheduling process. Furthermore, on the other side, the heuristic algorithms have satisfying performance but unable to achieve the desired level of efficiency for optimizing the scheduling in a cloud environment. Thus, this paper aims at evaluating the effectiveness of the hybrid meta-heuristic that incorporate genetic algorithm along with DE algorithm (GA-DE) in terms of make-span. In addition, the paper also intends to enhance the performance of the task scheduling in the heterogeneous cloud environment exploiting the scientific workflows (Cybershake, Montage, and Epigenomics). The proposed algorithm (GA-DE) has been compared against three heuristic algorithms, namely: HEFT-Upward Rank, HEFT – Downward Rank, and HEFT – Level Rank. The simulation results prove that the proposed algorithm (GA-DE) outperforms the other existing algorithms in all cases in terms of make-span

Cloud-based learning system for improving students’ programming skills and self-efficacy

Cloud-based Learning Systems (CBLS) refers to the systems that provide electronic or online content to enable the learning process by offering tools and functionalities through platform available in Cloud. This research seeks to examine the effectiveness of CBLS in improving programming skills among undergraduate students by measuring students’ performance in solving programming problems. This is because there is no empirical evidence on the effectiveness of CBLS when compared with the traditional method of learning programming among student beginners. Traditionally, teaching programming courses has been performed in a classroom setting and it can be very challenging for an instructor to go beyond covering the language’s syntax such as program design skills and problem-solving skills due to the wide variety of students’ background in such bounded class duration. In this study, three single-subject experiments were conducted using 40 undergraduate students enrolled in Web Programming course. The experiments compared the time students spent to solve programming tasks by using traditional learning method and CBLS. A survey to measure students’ selfefficacy was administered before and after the experiments. The findings of this study showed that there is a statistically significant difference in learning programming using CBLS when compared with traditional method. Our results showed that students solve programming problems in less time when using CBLS. The study also found out that CBLS is effective for improving students’ self-efficacy

A model for skyline query processing in a partially complete database

In the recent years, skyline queries become one of the predominant and most frequently used queries among preference queries in the database system. Its main theme is to identify and return those data items that are not dominated by any other data item in the database. In the past decade, a tremendous number of research have been conducted emphasized on skyline queries by proposing many variations of skyline techniques for a different type of database. Most of these techniques claimed that a database has complete data and values are always present when process skyline queries. However, this is not necessary to be always the case, particularly for large databases with a high number of dimensions as some values may be missing. Thus, existing techniques cannot be easily tailored to derive skylines in a database with missing values. Two significant issues might be raised, the issue of losing transitivity property which thus leads to the issue of cyclic dominance. Finding skylines in a database with partially complete data has not received enough attention. This paper proposes an efficient model to identify skylines over a database with partial complete data. Experimental results on various types of datasets demonstrate that the proposed approach outperforms the previous approach in terms of the number of pairwise comparisons

Optimizing skyline query processing in incomplete data

Given the significance of skyline queries, they are incorporated in various modern applications including personalized recommendation systems as well as decision-making and decision-support systems. Skyline queries are used to identify superior data items in the database. Most of the previously proposed skyline algorithms work on a complete database where the data are always present (non-missing). However, in many contemporary real-world databases, particularly those databases with large cardinality and high dimensionality, such assumption is not necessarily valid. Hence, missing data pose new challenges if the processing skyline queries cannot easily apply those methods that are designed for complete data. This is due to the fact that imperfect data cause the loss of the transitivity property of the skyline method and cyclic dominance. This paper presents a framework called Optimized Incomplete Skyline (OIS) which utilizes a technique that simplifies the skyline process on a database with missing data and helps prune the data items before performing the skyline process. The proposed strategy assures that the number of the domination tests is significantly reduced. A set of experiments has been accomplished using both real and synthetic datasets aimed at validating the performance of the framework. The experiment results confirm that the OIS framework is indeed superior and steadily outperforms the current approaches in terms of the number of domination tests required to retrieve the skylines