MWAND: A New Early Termination Algorithm for Fast and Efficient Query Evaluation

Nowadays, current information systems are so large and maintain huge amount of data. At every time, they process millions of documents and millions of queries. In order to choose the most important responses from this amount of data, it is well to apply what is so called early termination algorithms. These ones attempt to extract the Top-K documents according to a specified increasing monotone function. The principal idea behind is to reach and score the most significant less number of documents. So, they avoid fully processing the whole documents. WAND algorithm is at the state of the art in this area. Despite it is efficient, it is missing effectiveness and precision. In this paper, we propose two contributions, the principal proposal is a new early termination algorithm based on WAND approach, we call it MWAND (Modified WAND). This one is faster and more precise than the first. It has the ability to avoid unnecessary WAND steps. In this work, we integrate a tree structure as an index into WAND and we add new levels in query processing. In the second contribution, we define new fine metrics to ameliorate the evaluation of the retrieved information. The experimental results on real datasets show that MWAND is more efficient than the WAND approach

Data Structures for Fast Access Control in ECM Systems

While many access control models have been proposed, little work has been done on the efficiency of access control systems. Because the access control sub-system of an Enterprise Content Management (ECM) system may be a bottleneck, we investigate the representation of permissions to improve its efficiency. Observing that there are many browsing-oriented permission request queries, we choose to implement a subject-oriented representation (i.e., maintaining a permission list for each subject). Additionally, we notice that with breadth-first ID numbering we may encounter many contiguous IDs under one object (e.g., folder) . To optimize the efficiency taking into account the above two characteristics, this thesis presents a space-efficient data structure specifically tailored for representing permission lists in ECM systems. Besides the space efficiency, checking, granting or revocation of a permission is very fast using our data structure. It also supports fast union of two or more permission lists (determining the effective permissions inherited from users' groups). In addition, our data structure is scalable to support any increase in the number of objects and subjects. We evaluate our representation by comparing it against the bitmap based representation and a hash table based representation while using random ID numbering and breadth-first numbering, respectively. Our experimental tests on both synthetic and real-world data show that the hash table outperforms our representation for regular permission queries (i.e., querying permissions on a single object each time) as well as browsing-oriented queries with random ID numbering. However, our tests also show that 1) our representation supports faster browsing-oriented queries with breadth-first ID numbering applied while consuming only half the space when compared to the hash table based representation, and 2) our representation is much more space and time efficient than the bitmap based representation for our application

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Σημείωση: διατίθεται συμπληρωματικό υλικό σε ξεχωριστό αρχείο

Parallel Mesh Processing

Die aktuelle Forschung im Bereich der Computergrafik versucht den zunehmenden Ansprüchen der Anwender gerecht zu werden und erzeugt immer realistischer wirkende Bilder. Dementsprechend werden die Szenen und Verfahren, die zur Darstellung der Bilder genutzt werden, immer komplexer. So eine Entwicklung ist unweigerlich mit der Steigerung der erforderlichen Rechenleistung verbunden, da die Modelle, aus denen eine Szene besteht, aus Milliarden von Polygonen bestehen können und in Echtzeit dargestellt werden müssen. Die realistische Bilddarstellung ruht auf drei Säulen: Modelle, Materialien und Beleuchtung. Heutzutage gibt es einige Verfahren für effiziente und realistische Approximation der globalen Beleuchtung. Genauso existieren Algorithmen zur Erstellung von realistischen Materialien. Es gibt zwar auch Verfahren für das Rendering von Modellen in Echtzeit, diese funktionieren aber meist nur für Szenen mittlerer Komplexität und scheitern bei sehr komplexen Szenen. Die Modelle bilden die Grundlage einer Szene; deren Optimierung hat unmittelbare Auswirkungen auf die Effizienz der Verfahren zur Materialdarstellung und Beleuchtung, so dass erst eine optimierte Modellrepräsentation eine Echtzeitdarstellung ermöglicht. Viele der in der Computergrafik verwendeten Modelle werden mit Hilfe der Dreiecksnetze repräsentiert. Das darin enthaltende Datenvolumen ist enorm, um letztlich den Detailreichtum der jeweiligen Objekte darstellen bzw. den wachsenden Realitätsanspruch bewältigen zu können. Das Rendern von komplexen, aus Millionen von Dreiecken bestehenden Modellen stellt selbst für moderne Grafikkarten eine große Herausforderung dar. Daher ist es insbesondere für die Echtzeitsimulationen notwendig, effiziente Algorithmen zu entwickeln. Solche Algorithmen sollten einerseits Visibility Culling1, Level-of-Detail, (LOD), Out-of-Core Speicherverwaltung und Kompression unterstützen. Anderseits sollte diese Optimierung sehr effizient arbeiten, um das Rendering nicht noch zusätzlich zu behindern. Dies erfordert die Entwicklung paralleler Verfahren, die in der Lage sind, die enorme Datenflut effizient zu verarbeiten. Der Kernbeitrag dieser Arbeit sind neuartige Algorithmen und Datenstrukturen, die speziell für eine effiziente parallele Datenverarbeitung entwickelt wurden und in der Lage sind sehr komplexe Modelle und Szenen in Echtzeit darzustellen, sowie zu modellieren. Diese Algorithmen arbeiten in zwei Phasen: Zunächst wird in einer Offline-Phase die Datenstruktur erzeugt und für parallele Verarbeitung optimiert. Die optimierte Datenstruktur wird dann in der zweiten Phase für das Echtzeitrendering verwendet. Ein weiterer Beitrag dieser Arbeit ist ein Algorithmus, welcher in der Lage ist, einen sehr realistisch wirkenden Planeten prozedural zu generieren und in Echtzeit zu rendern

Multi-Version Search and Cache-Conscious Ranking Optimization

Organizations and companies archive many versions of digital data such as web pages, internal emails and so on. Such data is critical for internal investigation, regulatory compliance, and electronic discovery. It is estimated that electronic discovery market that leverages archival data will reach $9.9 billions globally in 2017. It is not uncommon for many businesses to retain archived collections for 10 to 15 years. How to archive these versioned data is worth to study and we are facing many challenges including 1) traditional index occupies too much space for versioned data, 2) traditional search is too slow on versioned data, and 3) how to guarantee high accuracy when improving efficiency in new architecture.In this dissertation, we take the opportunity of the fast development of information retrieval and tackle the problem by proposing a new multi-version search architecture with cache-conscious ranking optimization framework. Specifically, we will first discuss our new versioned search architecture. Then, we will talk about a cache-conscious online ranking algorithm to improve the online part. Finally, we will describe a framework to select best blocking methods and parameters for our algorithm to achieve best performance.Firstly, we present our new multi-version search architecture. We propose an approach that uses cluster-based retrieval to quickly narrow the search scope guided by version representatives at Phase 1 and develops a hybrid index structure with adaptive runtime data traversal to speed up Phase 2 search. The hybrid scheme exploits the advantages of forward index and inverted index based on the term characteristics to minimize the time in extracting positional and other feature information during runtime search. We compare several indexing and data traversal options with different time and space tradeoffs and describe evaluation results to demonstrate their effectiveness. The experiment results show that the proposed scheme can be up-to about 4x as fast as the previous work on solid state drives while retaining good relevance.Secondly, we talk about our 2D blocking algorithm to optimize the online ranking part of the system. Multi-tree ensemble models have been proven to be effective for document ranking. Using a large number of trees can improve accuracy, but it takes time to calculate ranking scores of matched documents. We investigate data traversal methods for fast score calculation with a large ensemble and propose a 2D blocking scheme for better cache utilization with simpler code structure compared to previous work. The experiments with several benchmarks show significant acceleration in score calculation without loss of ranking accuracy.Lastly, we describe a framework to fast select best blocking methods and parameters for our 2D blocking algorithm with the help of a full cache analysis. 2D blocking method is very helpful to improve online search efficiency. However, different traversal methods and blocking parameter settings can exhibit different cache and cost behavior depending on data and architectural characteristics. It is very time-consuming to conduct exhaustive search for performance comparison and optimum selection. We provide an analytic comparison of cache blocking methods on their data access performance for an approximation and propose a fast guided sampling scheme to select a traversal method and blocking parameters for effective use of memory hierarchy. The evaluation studies with three datasets show that within a reasonable amount of time, the proposed scheme can identify a highly competitive solution that significantly accelerates score calculation.In summary, we have proposed a new multi-version search architecture with cache-conscious ranking optimization for the online search part and a framework to help fast select best blocking methods and parameters with full cache analysis for the 2D blocking method. By proposing this new versioned search system, we can meet challenges from scalability, efficiency and accuracy in multi-version search, and we believe this work would be useful to future researchers in this direction