4,670 research outputs found
Yellow Tree: A Distributed Main-memory Spatial Index Structure for Moving Objects
Mobile devices equipped with wireless technologies to communicate and positioning systems to locate objects of interest are common place today, providing the impetus to develop location-aware applications. At the heart of location-aware applications are moving objects or objects that continuously change location over time, such as cars in transportation networks or pedestrians or postal packages. Location-aware applications tend to support the tracking of very large numbers of such moving objects as well as many users that are interested in finding out about the locations of other moving objects. Such location-aware applications rely on support from database management systems to model, store, and query moving object data. The management of moving object data exposes the limitations of traditional (spatial) database management systems as well as their index structures designed to keep track of objects\u27 locations. Spatial index structures that have been designed for geographic objects in the past primarily assume data are foremost of static nature (e.g., land parcels, road networks, or airport locations), thus requiring a limited amount of index structure updates and reorganization over a period of time. While handling moving objects however, there is an incumbent need for continuous reorganization of spatial index structures to remain up to date with constantly and rapidly changing object locations. This research addresses some of the key issues surrounding the efficient database management of moving objects whose location update rate to the database system varies from 1 to 30 minutes. Furthermore, we address the design of a highly scaleable and efficient spatial index structure to support location tracking and querying of large amounts of moving objects. We explore the possible architectural and the data structure level changes that are required to handle large numbers of moving objects. We focus specifically on the index structures that are needed to process spatial range queries and object-based queries on constantly changing moving object data. We argue for the case of main memory spatial index structures that dynamically adapt to continuously changing moving object data and concurrently answer spatial range queries efficiently. A proof-of concept implementation called the yellow tree, which is a distributed main-memory index structure, and a simulated environment to generate moving objects is demonstrated. Using experiments conducted on simulated moving object data, we conclude that a distributed main-memory based spatial index structure is required to handle dynamic location updates and efficiently answer spatial range queries on moving objects. Future work on enhancing the query processing performance of yellow tree is also discussed
Scalable and dynamically balanced shared-everything OLTP with physiological partitioning
Scaling the performance of shared-everything transaction processing systems to highly parallel multicore hardware remains a challenge for database system designers. Recent proposals alleviate locking and logging bottlenecks in the system, leaving page latching as the next potential problem. To tackle the page latching problem, we propose physiological partitioning (PLP). PLP applies logical-only partitioning, maintaining the desired properties of sharedeverything designs, and introduces a multi-rooted B+Tree index structure (MRBTree) that enables the partitioning of the accesses at the physical page level. Logical partitioning and MRBTrees together ensure that all accesses to a given index page come from a single thread and, hence, can be entirely latch free; an extended design makes heap page accesses thread private as well. Moreover, MRBTrees offer an infrastructure for easy repartitioning and allow us to have a lightweight dynamic load balancing mechanism (DLB) on top of PLP. Profiling a PLP prototype running on different multicore machines shows that it acquires 85 and 68%fewer contentious critical sections, respectively, than an optimized conventional design and one based on logical-only partitioning. PLP also improves performance up to almost 50 % over the existing systems, while DLB enhances the system with rapid and robust behavior in both detecting and handling load imbalance
Self-organizing strategies for a column-store database
Column-store database systems open new vistas for improved maintenance through self-organization. Individual columns are the focal point, which simplify balancing conflicting requirements. This work presents two workload-driven self-organizing techniques in a column-store, i.e. adaptive segmentation and adaptive replication. Adaptive segmentation splits a column into non-overlapping segments based on the actual query load. Likewise, adaptive replication creates segment replicas. The strategies can support different application requirements by trading off the reorganization overhead for storage cost. Both techniques can significantly improve system performance as demonstrated in an evaluation of different scenarios
Efficient bulk-loading methods for temporal and multidimensional index structures
Nahezu alle naturwissenschaftlichen Bereiche profitieren von neuesten Analyse- und Verarbeitungsmethoden fĂŒr groĂe Datenmengen. Diese Verfahren setzten eine effiziente Verarbeitung von geo- und zeitbezogenen Daten voraus, da die Zeit und die Position wichtige Attribute vieler Daten
sind. Die effiziente Anfrageverarbeitung wird insbesondere durch den Einsatz von Indexstrukturen
ermöglicht. Im Fokus dieser Arbeit liegen zwei Indexstrukturen: Multiversion B-Baum
(MVBT) und R-Baum. Die erste Struktur wird fĂŒr die Verwaltung von zeitbehafteten Daten,
die zweite fĂŒr die Indexierung von mehrdimensionalen Rechteckdaten eingesetzt.
StĂ€ndig- und schnellwachsendes Datenvolumen stellt eine groĂe Herausforderung an die Informatik
dar. Der Aufbau und das Aktualisieren von Indexen mit herkömmlichen Methoden (Datensatz
fĂŒr Datensatz) ist nicht mehr effizient. Um zeitnahe und kosteneffiziente Datenverarbeitung
zu ermöglichen, werden Verfahren zum schnellen Laden von Indexstrukturen dringend benötigt.
Im ersten Teil der Arbeit widmen wir uns der Frage, ob es ein Verfahren fĂŒr das Laden von MVBT
existiert, das die gleiche I/O-KomplexitÀt wie das externe Sortieren besitz. Bis jetzt blieb diese
Frage unbeantwortet. In dieser Arbeit haben wir eine neue Kostruktionsmethode entwickelt und
haben gezeigt, dass diese gleiche ZeitkomplexitÀt wie das externe Sortieren besitzt. Dabei haben
wir zwei algorithmische Techniken eingesetzt: Gewichts-Balancierung und Puffer-BĂ€ume. Unsere
Experimenten zeigen, dass das Resultat nicht nur theoretischer Bedeutung ist.
Im zweiten Teil der Arbeit beschÀftigen wir uns mit der Frage, ob und wie statistische Informationen
ĂŒber Geo-Anfragen ausgenutzt werden können, um die Anfrageperformanz von R-BĂ€umen zu
verbessern. Unsere neue Methode verwendet Informationen wie SeitenverhÀltnis und SeitenlÀngen
eines reprĂ€sentativen Anfragerechtecks, um einen guten R-Baum bezĂŒglich eines hĂ€ufig eingesetzten
Kostenmodells aufzubauen. Falls diese Informationen nicht verfĂŒgbar sind, optimieren
wir R-BĂ€ume bezĂŒglich der Summe der Volumina von minimal umgebenden Rechtecken der Blattknoten.
Da das Problem des Aufbaus von optimalen R-BĂ€umen bezĂŒglich dieses KostenmaĂes
NP-hart ist, fĂŒhren wir zunĂ€chst das Problem auf ein eindimensionales Partitionierungsproblem
zurĂŒck, indem wir die Daten bezĂŒglich optimierte raumfĂŒllende Kurven sortieren. Dann lösen
wir dieses Problem durch Einsatz vom dynamischen Programmieren. Die I/O-KomplexitÀt des
Verfahrens ist gleich der von externem Sortieren, da die I/O-Laufzeit der Methode durch die
Laufzeit des Sortierens dominiert wird.
Im letzten Teil der Arbeit haben wir die entwickelten Partitionierungsvefahren fĂŒr den Aufbau
von Geo-Histogrammen eingesetzt, da diese Àhnlich zu R-BÀumen eine disjunkte Partitionierung
des Raums erzeugen. Ergebnisse von intensiven Experimenten zeigen, dass sich unter Verwendung
von neuen Partitionierungstechniken sowohl R-BĂ€ume mit besserer Anfrageperformanz als
auch Geo-Histogrammen mit besserer SchÀtzqualitÀt im Vergleich zu Konkurrenzverfahren generieren
lassen
Data fragmentation for parallel transitive closure strategies
Addresses the problem of fragmenting a relation to make the parallel computation of the transitive closure efficient, based on the disconnection set approach. To better understand this design problem, the authors focus on transportation networks. These are characterized by loosely interconnected clusters of nodes with a high internal connectivity rate. Three requirements that have to be fulfilled by a fragmentation are formulated, and three different fragmentation strategies are presented, each emphasizing one of these requirements. Some test results are presented to show the performance of the various fragmentation strategie
Towards Intelligent Databases
This article is a presentation of the objectives and techniques
of deductive databases. The deductive approach to databases aims at extending
with intensional definitions other database paradigms that describe
applications extensionaUy. We first show how constructive specifications can
be expressed with deduction rules, and how normative conditions can be defined
using integrity constraints. We outline the principles of bottom-up and
top-down query answering procedures and present the techniques used for
integrity checking. We then argue that it is often desirable to manage with
a database system not only database applications, but also specifications of
system components. We present such meta-level specifications and discuss
their advantages over conventional approaches
Using Actors to Build a Parallel DBMS
In this paper, we present the design and the architecture of a parallel main memory database management system. We focus on concurrency control scheme and recovery. Our prototype is based on the concept of âdatabase actorsâ, an object-oriented data model well suited for parallelmanipulations. The storage sub system is built upon distributed Ram-files using SDDS (Scalable Distributed Data Structures) techniques. A nested transaction model is proposed and used to handle concurrency access and recovery. We have also proposed novel approach, based on wait-die, to implement a distributed deadlock prevention technique for our model of nested transactions
Proceedings of Abstracts Engineering and Computer Science Research Conference 2019
© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care
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