Ubiquitous B-Tree

Comer, Douglas E.

doi:10.1145/356770.356776

Cited by 1,482 publications

(651 citation statements)

References 22 publications

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“…To partition the spatial domain covered by vector objects, kinds of decomposing methods had been used. Specifically, related methods could be divided into four classes [32]: (1) approaches based on the minimum bounding rectangles, such as B-tree [33], R-Tree [34]; (2) disjoint decompositions, such as R+Tree [35], cell tree [36]; (3) uniform grid approaches [37]; and (4) quadtree-based approaches [38]. The first two classes of approaches depended more on the data, and had been widely used in spatial queries, but not applicable to the grouping and spatial operations, such as the union operation [32].…”

Section: Spatial Locality In Surface Area Estimationmentioning

confidence: 99%

A Stream Tilling Approach to Surface Area Estimation for Large Scale Spatial Data in a Shared Memory System

et al. 2017

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Surface area estimation is a widely used tool for resource evaluation in the physical world. When processing large scale spatial data, the input/output (I/O) can easily become the bottleneck in parallelizing the algorithm due to the limited physical memory resources and the very slow disk transfer rate. In this paper, we proposed a stream tilling approach to surface area estimation that first decomposed a spatial data set into tiles with topological expansions. With these tiles, the one-to-one mapping relationship between the input and the computing process was broken. Then, we realized a streaming framework towards the scheduling of the I/O processes and computing units. Herein, each computing unit encapsulated a same copy of the estimation algorithm, and multiple asynchronous computing units could work individually in parallel. Finally, the performed experiment demonstrated that our stream tilling estimation can efficiently alleviate the heavy pressures from the I/O-bound work, and the measured speedup after being optimized have greatly outperformed the directly parallel versions in shared memory systems with multi-core processors.

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Section: Spatial Locality In Surface Area Estimationmentioning

confidence: 99%

A Stream Tilling Approach to Surface Area Estimation for Large Scale Spatial Data in a Shared Memory System

et al. 2017

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“…The decision variables a 1 , d 1 , d 2 , d 4 determining the speed profiles are retrieved from the database. The data within the database is indexed in a B-tree structure (Comer, 1979). In this tree-like structure, data is sorted into hierarchical levels using the following keys: weight class, segment type, segment length, discretisation, as illustrated in Fig.…”

Section: Database Formation and Speed Profile Retrievalmentioning

confidence: 99%

A real-time Active Routing approach via a database for airport surface movement

Weiszer

Chen

Stewart

2015

Transportation Research Part C: Emerging Technologies

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Airports face challenges due to the increasing volume of air traffic and tighter environmental restrictions which result in a need to actively integrate speed profiles into conventional routing and scheduling procedure. However, only until very recently, the research on airport ground movement has started to take into account such a speed profile optimisation problem actively so that not only time efficiency but also fuel saving and decrease in airport emissions can be achieved at the same time. It is envisioned that the realism of planning could also be improved through speed profiles. However, due to the multi-objective nature of the problem and complexity of the investigated models (objective functions), the existing speed profile optimisation approach features high computational demand and is not suitable for an on-line application. In order to make this approach more competitive for real-world application and to meet limits imposed by International Civil Aviation Organization for on-line decision time, this paper introduces a pre-computed database acting as a middleware to effectively separate the planning (routing and scheduling) module and the speed profile generation module. Employing a database not only circumvents duplicative optimisation for the same taxiway segments, but also completely avoids the computation of speed profiles during the on-line decision support owing a great deal to newly proposed database initialization procedures. Moreover, the added layer of database facilitates, in the future, more complex and realistic models to be considered in the speed profile generation module, without sacrificing on-line decision time. The experimental results carried out using data from a major European hub show that the proposed approach is promising in speeding up the search process.

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“…A CF tree represents a height-balanced tree which is similar to a B+ tree [2]. A node of a CF tree represents a CF vector, which corresponds to an abstracted expression of a set of examples.…”

Section: Birchmentioning

confidence: 99%

Iterative Data Squashing for Boosting Based on a Distribution-Sensitive Distance

Choki

Suzuki

2002

Principles of Data Mining and Knowledge Discovery

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Abstract. This paper proposes, for boosting, a novel method which prevents deterioration of accuracy inherent to data squashing methods. Boosting, which constructs a highly accurate classification model by combining multiple classification models, requires long computational time. Data squashing, which speeds-up a learning method by abstracting the training data set to a smaller data set, typically lowers accuracy. Our SB (Squashing-Boosting) loop, based on a distribution-sensitive distance, alternates data squashing and boosting, and iteratively refines an SF (Squashed-Feature) tree, which provides an appropriately squashed data set. Experimental evaluation with artificial data sets and the KDD Cup 1999 data set clearly shows superiority of our method compared with conventional methods. We have also empirically evaluated our distance measure as well as our SF tree, and found them superior to alternatives.

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Ubiquitous B-Tree

Cited by 1,482 publications

References 22 publications

A Stream Tilling Approach to Surface Area Estimation for Large Scale Spatial Data in a Shared Memory System

A Stream Tilling Approach to Surface Area Estimation for Large Scale Spatial Data in a Shared Memory System

A real-time Active Routing approach via a database for airport surface movement

Iterative Data Squashing for Boosting Based on a Distribution-Sensitive Distance

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