Centralized Database System Research Articles

Data analysis and review of radiology services at Glasgow 2014 Commonwealth Games.

Medical services at the Glasgow 2014 Commonwealth Games (CWG) were provided though a purpose-built medical polyclinic, which had a fully equipped radiology department along with other services, set up within the main Games Village. Data analysis of radiology services offered at CWG has not been published before. Imaging services within the polyclinic, Athletes Village, Glasgow 2014 CWG. The aim of the paper is to analyse data on radiological investigations and assess the demand and distribution of workload on imaging services at CWG 2014. Data on radiology investigations at the CWG 2014 was retrieved from the Carestream picture archiving and communication system (PACS) and Pharmasys (CWG official centralised electronic database system) and analysed. Six hundred ninety-seven diagnostic and interventional procedures were performed. Of these 37.9% were magnetic resonance imaging (MRI) scans, 22% were diagnostic ultrasound (US) examinations, 33.1% were radiographs, 4.3% were computed tomography (CT) scans and 2.7% were imaging-guided interventional procedures. 88% of imaging was performed on athletes and the remainder were performed on team officials and workforce. Demand on radiology services gradually picked up through the pre-competition period and peaked half way through the CWG. Radiology played a vital role in the successful provision of medical services at the Glasgow 2014 CWG. High demand on imaging services can be expected at major international sporting events and therefore pre-event planning is vital. Having back-up facilities in case of technical failure should be given due importance when planning radiology services at future CWG events.

IJARCCE - Computer and Communication Engineering

Database is the collection of files or table and Database Management System is used to manage the overall activities of the database. We have two approaches for storing and managing database namely Centralised Database management system and Distributed Database management system. Query Processing and its optimization is one of the major key areas of Distributed Database Systems. Query optimization is much more difficult in Distributed Database as compared to the Centralised Database System. This literature review paper is based in the query optimization in Distributed Database System. It mainly focused on to analyse the performance and behaviour of the use of semi-joins and joins. Various factors are considered like CPU cost, I/O cost, Total Cost, Response time and Total time etc. Minimizing the amount of data transmission is important to reduce the query processing cost. To minimize this communication cost, the exhaustive enumerative technique has used to bring dynamism in determining the sub operations (join or semi join) to various sites.

Distributed snapshot isolation: global transactions pay globally, local transactions pay locally

Modern database systems employ Snapshot Isolation to implement concurrency control and isolationbecause it promises superior query performance compared to lock-based alternatives. Furthermore, Snapshot Isolation never blocks readers, which is an important property for modern information systems, which have mixed workloads of heavy OLAP queries and short update transactions. This paper revisits the problem of implementing Snapshot Isolation in a distributed database system and makes three important contributions. First, a complete definition of Distributed Snapshot Isolation is given, thereby extending existing definitions from the literature. Based on this definition, a set of criteria is proposed to efficiently implement Snapshot Isolation in a distributed system. Second, the design space of alternative methods to implement Distributed Snapshot Isolation is presented based on this set of criteria. Third, a new approach to implement Distributed Snapshot Isolation is devised; we refer to this approach as Incremental. The results of comprehensive performance experiments with the TPC-C benchmark show that the Incremental approach significantly outperforms any other known method from the literature. Furthermore, the Incremental approach requires no a priori knowledge of which nodes of a distributed system are involved in executing a transaction. Also, the Incremental approach can execute transactions that involve data from a single node only with the same efficiency as a centralized database system. This way, the Incremental approach takes advantage of sharding or other ways to improve data locality. The cost for synchronizing transactions in a distributed system is only paid by transactions that actually involve data from several nodes. All these properties make the Incremental approach more practical than related methods proposed in the literature.

VIRTUAL HERITAGE ARCHIVES: BUILDING A CENTRALIZED AUSTRALIAN ROCK ART ARCHIVE

Abstract. This paper examines use of multi-media in the curation, presentation and promotion of rock art. It discusses the construction of a centralised Australian rock art database and explores new technologies available for looking at rock art. In 2011, Prof. Taçon Chair in Rock Art Research and Director of PERAHU (Place, Evolution and Rock Art Heritage Unit) called for a national rock art database raising awareness of the importance of preserving rock art as part of Australia's valuable Indigenous heritage (Taçon, 2011). Australia has over 100,000 rock art sites, important heritage places for Indigenous and non-Indigenous Australians and a testament to over 10,000 years of human activity, including interactions with other peoples and the environment. Many of these sites have not been documented or recorded and are threatened by natural and cultural agents. It is becoming increasingly important to develop conservation models for the protection and preservation of sites. Indigenous cultural heritage is difficult to manage on a local government level due to complex human / time / environment relationships and the importance of intangible cultural heritage (SoE SEWPAC, 2011). Currently no centralised database system exists in Australia to curate, present and promote rock art.

SU‐E‐T‐248: A Patient Data Management System for Philips Pinnacle‐3 TPS

Purpose: This abstract presents a Pinnacle TPS data management system for patient data sharing and long‐term archiving. Methods: For institutions deploying Philips Pinnacle‐3 as TPS, data management, such as, patient data sharing and long‐term archiving, is always challenging. Most institutions have multiple cancer centers, each of which has its own separate Pinnacle database. With increasing cooperation and personnel mobility, there is a high demand for patient data sharing among these cancer centers. Meanwhile, for the sake of patient data safety and integrity, once a patient is done with treatments, patient data should be moved out of Pinnacle database instead of continuing to consume limited disk space. In addition, for re‐treatment and research purposes, patient data should be retrievable and searchable. To address these needs, we implemented a solution, which uses a centralized database system with rich web interfaces. In this system, every operation is executed simply by mouse clicks through web and all data is transferred over secure network channels. Any Pinnacle database can join the system as a member. Within its user access control scheme, each user belongs to a user group associated with a specific Pinnacle database. That is, once a user logs on to the system, s/he can only access patient data from the Pinnacle database of which the user has privilege. Patient data in the database can be searched through a variety of criteria and also can be easily retrieved and restored to Pinnacle and other TPS. Furthermore, due to its rich web interfaces, this system can be accessed by mobile devices (e.g., iPad/Android). Results: Conclusion: Our system provides a comprehensive solution for Pinnacle patient data management, which greatly enhances patient data safety/integrity and facilitates cooperation. Its centralized infrastructure also opens up possibilities of advanced features, such as, online planning and patient data visual search.

An intelligent hybrid optimistic/pessimistic concurrency control algorithm for centralized database systems using modified GSA-optimized ART neural model

Concurrency control is the activity of synchronizing operations issued by concurrent executing transactions on a shared database. The aim of this control is to provide an execution that has the same effect as a serial (non-interleaved) one. The optimistic concurrency control technique allows the transactions to execute without synchronization, relying on commit-time validation to ensure serializability. Effectiveness of the optimistic techniques depends on the conflict rate of transactions. Since different systems have various patterns of conflict and the patterns may also change over time, so applying the optimistic scheme to the entire system results in degradation of performance. In this paper, a novel algorithm is proposed that dynamically selects the optimistic or pessimistic approach based on the value of conflict rate. The proposed algorithm uses an adaptive resonance theory–based neural network in making decision for granting a lock or detection of the winner transaction. In addition, the parameters of this neural network are optimized by a modified gravitational search algorithm. On the other hand, in the real operational environments we know the writeset (WS) and readset (RS) only for a fraction of transactions set before execution. So, the proposed algorithm is designed based on optional knowledge about WS and RS of transactions. Experimental results show that the proposed hybrid concurrency control algorithm results in more than 35 % reduction in the number of aborts in high-transaction rates as compared to strict two-phase locking algorithm that is used in many commercial database systems. This improvement is 13 % as compared to pure-pessimistic approach and is more than 31 % as compared to pure-optimistic approach.

C-PASS-PC: A Cloud-driven Prototype of Multi-Center Proactive Surveillance System for Prostate Cancer

Currently there are many clinical trials using paper case report forms as the primary data collection tool. Cloud Computing platforms provide big potential for increasing efficiency through a web-based data collection interface, especially for large-scale multi-center trials. Traditionally, clinical and biological data for multi-center trials are stored in one dedicated, centralized database system running at a data coordinating center (DCC). This paper presents C-PASS-PC, a cloud-driven prototype of multi-center proactive surveillance system for prostate cancer. The prototype is developed in PHP, JQuery and CSS with an Oracle backend in a local Web server and database server and deployed on Google App Engine (GAE) and Google Cloud SQL-MySQL. The deploying process is fast and easy to follow. The C-PASS-PC prototype can be accessed through an SSL-enabled web browser. Our approach proves the concept that cloud computing platforms such as GAE is a suitable and flexible solution in the near future for multi-center clinical trials.

Methods for Structuring Scientific Knowledge from Many Areas Related to Aging Research

Aging and age-related disease represents a substantial quantity of current natural, social and behavioral science research efforts. Presently, no centralized system exists for tracking aging research projects across numerous research disciplines. The multidisciplinary nature of this research complicates the understanding of underlying project categories, the establishment of project relations, and the development of a unified project classification scheme. We have developed a highly visual database, the International Aging Research Portfolio (IARP), available at AgingPortfolio.org to address this issue. The database integrates information on research grants, peer-reviewed publications, and issued patent applications from multiple sources. Additionally, the database uses flexible project classification mechanisms and tools for analyzing project associations and trends. This system enables scientists to search the centralized project database, to classify and categorize aging projects, and to analyze the funding aspects across multiple research disciplines. The IARP is designed to provide improved allocation and prioritization of scarce research funding, to reduce project overlap and improve scientific collaboration thereby accelerating scientific and medical progress in a rapidly growing area of research. Grant applications often precede publications and some grants do not result in publications, thus, this system provides utility to investigate an earlier and broader view on research activity in many research disciplines. This project is a first attempt to provide a centralized database system for research grants and to categorize aging research projects into multiple subcategories utilizing both advanced machine algorithms and a hierarchical environment for scientific collaboration.

Damage assessment and repair in attack resilient distributed database systems

Preventive measures sometimes fail to defect malicious attacks. With attacks on data-intensive applications becoming an ever more serious threat, intrusion tolerant database systems are a significant concern. The main objective of such systems is to detect attacks, and to assess and repair the damage in a timely manner. This paper focuses on efficient damage assessment and repair in distributed database systems. The complexity caused by data partition, distributed transaction processing, and failures makes intrusion recovery much more challenging than in centralized database systems. This paper identifies the key challenges and presents an efficient algorithm for distributed damage assessment and repair.

Design and Implementation of Students’ Information System for Tertiary Institutions Using Neural Networks

This paper identifies the causes associated with delays in processing and releasing results in tertiary institutions. An enhanced computer program for result computation integrated with a database for storage of processed results simplifies a university grading system and overcomes the short-comings of existing packages. The system takes interdepartmental collaboration and alliances into consideration, over a network that speeds up collection of processed results from designated departments through an improved centralized database system. An empirical evaluation of the system shows that it expedites processing of results and transcripts at various levels and management of and access to student results on-line. The technological approach for the implementation of the proposed system is based on open source solutions. Apache is used as Web server extended with PHP for server side processing. In recognition of the confidentiality of data contained in the system, communication networks are protected with open-ssl library for data encryption and role-based authentication. This system increases efficient service delivery and benefits both administration and students.

A meta-index for querying distributed moving object database servers

Distributed moving object database servers offer a feasible solution to the scalability problems of centralized database systems. In these potentially large-scale systems, querying about the time-varying location of specific moving objects can be particularly expensive in terms of running time. This work proposes a meta-index based strategy that can significantly speed up the processing of these queries. The meta-index acts as an entry point for spatio-temporal queries and quickly drives the search process to the database servers that contain solutions. It also enables very fast approximated solutions to queries such as top- k and spatio-temporal range queries.

Database Support for the New Mechanistic-Empirical Pavement Design Guide

The proposed Mechanistic-Empirical Pavement Design Guide (MEPDG) developed under the NCHRP Project 1-37A initiative is a significant advancement in pavement design. However, it is substantially more complex than the 1993 AASHTO design guide and it requires significantly more input from the designer. Some of the required data either are not available or are stored in locations not familiar to designers. In addition, many data sets need to be preprocessed for use in MEPDG. Thus, there was a need to study the data requirements for MEPDG and produce a centralized database system to aid designers. This paper describes the development of a comprehensive database that can be used to store and process climate, traffic, material, and performance data for the state of Arkansas. The tasks undertaken were to (a) identify all the necessary input and analysis parameters required, (b) develop the database structures for uploading the required data, (c) locate the available data sets and begin populating the database, and (d) develop a data interface to the MEPDG software. The completed database will improve the management and accessibility of the MEPDG input data, and its completion is a critical step before the calibration and implementation of MEPDG.

MULTI-KEY INDEX FOR DISTRIBUTED DATABASE SYSTEM

In this paper we present a multi-key index model that enables us to search a record with more than one attribute values in distributed database systems. Indices provide fast and efficient access of data and so become a major aspect in centralized database systems. Most of the centralized database systems use B + tree or other types of index structures such as bit vector, graph structure, grid file etc. But in distributed database systems no index model is found in the literature. Therefore efficient access is a major problem in distributed databases. Our proposed index model avoids the query-flooding problem of existing system and thus optimizes network bandwidth.

Managing uncertainty in sensor database

Sensors are often employed to monitor continuously changing entities like locations of moving objects and temperature. The sensor readings are reported to a centralized database system, and are subsequently used to answer queries. Due to continuous changes in these values and limited resources (e.g., network bandwidth and battery power), the database may not be able to keep track of the actual values of the entities, and use the old values instead. Queries that use these old values may produce incorrect answers. However, if the degree of uncertainty between the actual data value and the database value is limited, one can place more confidence in the answers to the queries. In this paper, we present a frame-work that represents uncertainty of sensor data. Depending on the amount of uncertainty information given to the application, different levels of imprecision are presented in a query answer. We examine the situations when answer imprecision can be represented qualitatively and quantitatively. We propose a new kind of probabilistic queries called Probabilistic Threshold Query , which requires answers to have probabilities larger than a certain threshold value. We also study techniques for evaluating queries under different details of uncertainty, and investigate the tradeoff between data uncertainty, answer accuracy and computation costs.

Performance Evaluation of Database Systems Using Colored Petri Nets

We propose Colored Petri Net (CPN) models for replicated and centralized database systems and conduct a comparative study of their performance. The designed CPN models capture the dynamics of the studied database systems and estimate their expected performance with an appropriate level of abstraction. A number of simulation experiments were performed under various load conditions of varying parameters such as server speed, network speed, and read/write ratio. The simulation results show that under similar operation conditions, replicated systems exhibit higher performance than centralized systems in terms of query response time and system saturation levels. However, centralized systems become more competitive when their network and server speeds are much higher than those of the replicated systems.

Hip fracture incidence rates in Singapore 1991-1998.

In this population-based study, we determined the incidence rates of hip fracture among Singapore residents aged 50 years and above. Information was obtained from a centralized database system which captured admissions with the primary diagnosis of a closed hip fracture (ICD-9 codes 820, 820.0, 820.2 and 820.8, n = 12,927) from all health care establishments in the country from 1991 to 1998 inclusive. After removing duplicates, hospital transfers, readmissions and non-acute care admissions, the total number of hip fractures was 9406. Based on the national population census 1990 (n = 464,100) and yearly population estimates, the age-adjusted hip fracture rates for 1991-1998 (per 100,000) were 152 in men and 402 in women. This was 1.5 and over 5 times higher than corresponding rates in the 1960s. From 1991 to 1998, these hip fracture rates tended to increase by 0.7% annually in men and by 1.2% annually in women. Among the three major racial groups, in men, the Chinese had significantly higher age-adjusted hip fracture rates (per 100,000): 168 (95% confidence interval (CI) 158-178) compared with 128 (95% CI 105-152) for Indians and 71 (95% CI 54-88) for Malays. A similar pattern occurred in women: 410 (95% CI 395-425), for Chinese compared with 361 (95% CI 290-432) for Indians and 264 (95% CI 225-303) for Malays. Since the 1960s, the main increases in hip fracture rates have been seen in the Chinese and Malays, with the rates in Indians appearing to decrease. Hip fracture incidence rates in Singapore have risen rapidly over the past 30-40 years, particularly in women, and are now among the highest in Asia. Significant racial differences in hip fracture rates occur within the same community. Time trends in hip fracture rates differed between races.

Approximation for the mean value performance of locking algorithms for distributed database systems: a partitioned database

Concurrent access to databases must be synchronized for correct execution of transactions and preservation of data consistency. This is usually achieved through use of concurrency control algorithms, amongst which locking algorithms are the most popular both in the literature and in practice. Several analytic methods have been developed for predicting the performance of centralized database systems employing locking algorithms for concurrency control, but very few exist for distributed database systems. This paper proposes a method to approximate the mean value of various performance parameters in distributed database systems using locking for concurrency control. The main contribution of this approach is its ability to model the interaction between resource and data contention and the resulting effect on system performance. System performance is evaluated at a point where the interaction between these two factors is in equilibrium (stable state) and both the data and resource contention equations are simultaneously satisfied. The model involves the solution of a set of simultaneous polynomial equations whose order is dependent on several problem parameters such as the number of nodes and number of locks requested per transaction. These equations are solved by an iterative procedure to evaluate approximate values of relative throughput, utilization of servers and transaction response time. The small computational requirements of the analytical model permit sensitivity analysis on network parameters, and can thus be effectively used by system designers to evaluate choices of communication line speeds, processor capacity, database sizes, etc. The analytic approximations have been extensively verified against simulations for networks with up to 20 nodes. The input traffic was varied from light loads (about 5% utilization of the channels and processors) to heavy loads (about 65% utilization of the processors and channels). The discrepancies between the analytic approximation and the simulation were quite small (2–8%).

The concurrency control problem in multidatabases

A Multidatabase System (MDBS) is a collection of local database management systems, each of which may follow a different concurrency control protocol. This heterogeneity makes the task of ensuring global serializability in an MDBS environment difficult. In this paper, we reduce the problem of ensuring global serializability to the problem of ensuring serializability in a centralized database system. We identify characteristics of the concurrency control problem in an MDBS environment, and additional requirements on concurrency control schemes for ensuring global serializability. We then develop a range of concurrency control schemes that ensure global serializability in an MDBS environment, and at the same time meet the requirements. Finally, we study the tradeoffs between the complexities of the various schemes and the degree of concurrency provided by each of them.

DATAPLEX: an access to heterogeneous distributed databases

Diverse database management systems are used in large organizations. The heterogeneous distributed database system (DDS) can provide a flexible intergration of diverse databases for users and applications. This is because it allows for retrieval and update of distributed data under different data systems giving the illusion of accessing a single centralized database system.

Time and Cost Evaluation Schemes of Multiple Copies of Data in Distributed Database Systems

In comparison to centralized database systems, distributed database systems have certain advantages depending on the manner in which data are redundantly distributed. These advantages are improvement in response time, better data availability, reduction in transmission cost, etc.