42020510
An Efficient Technique for Nearest-Neighbor Query Processing on the SPY-TEC
The SPY-TEC (spherical pyramid-technique) was proposed as a new indexing method for high-dimensional data spaces using a special partitioning strategy that divides a d-dimensional data space into 2d spherical pyramids. In the SPY-TEC, an efficient algorithm for processing hyperspherical range queries was introduced with a special partitioning strategy. However, the technique for processing k-nearest-neighbor queries, which are frequently used in similarity search, was not proposed. In this paper, we propose an efficient algorithm for processing nearest-neighbor queries on the SPY-TEC by extending the incremental nearest-neighbor algorithm. We also introduce a metric that can be used to guide an ordered best-first traversal when finding nearest neighbors on the SPY-TEC. Finally, we show that our technique significantly outperforms the related techniques in processing k-nearest-neighbor queries by comparing it to the R*-tree, the X-tree, and the sequential scan through extensive experiments.
15086505
A fast content-based indexing and retrieval technique by the shape information in large image database
Abstract In this paper, we present an efficient content-based image retrieval (CBIR) system which employs the shape information of images to facilitate the retrieval process. For efficient feature extraction, we extract the shape feature of images automatically using edge detection and wavelet transform which is widely used in digital signal processing and image compression. To facilitate speedy retrieval, we also propose the Spherical Pyramid-Technique (SPY-TEC), a new indexing method for similarity search in high-dimensional data space. The SPY-TEC is based on a special space partitioning strategy, which is to divide the d-dimensional data space first into 2d spherical pyramids, and then cut the single spherical pyramid into several spherical slices. This partition provides a transformation of d-dimensional space into 1-dimensional space. Thus, we are able to use a B+-tree to manage the transformed 1-dimensional data. We show that our image indexing method supports faster retrieval than other multi-dimensional indexing methods such as the R*-tree through various experiments. Finally, we show the retrieval effectiveness of our CBIR system using the measure proposed by the QBIC (C. Faloutsos et al., 1994) system.
42364168
An Algorithm for Incremental Nearest Neighbor Search in High-Dimensional Data Spaces
The SPY-TEC (Spherical Pyramid-Technique) [8] was proposed as a new indexing method for high-dimensional data spaces using a special partitioning strategy that divides a d-dimensional data space into 2d spherical pyramids. Although the authors of [8] proposed an efficient algorithm for processing hyperspherical range queries, they did not propose an algorithm for processing k-nearest neighbor queries that are frequently used in similarity search. In this paper, we propose an efficient algorithm for processing exact nearest neighbor queries on the SPY-TEC by extending the incremental nearest neighbor algorithm proposed in [10]. We also introduce a metric that can be used to guide an ordered best-first traversal when finding nearest neighbors on the SPYTEC. Finally, we show that our technique significantly outperforms the related techniques in processing k-nearest neighbor queries by comparing it to the R*-tree, the X-tree, and the sequential scan through extensive experiments.
36572676
An efficient algorithm for hyperspherical range query processing in high-dimensional data space
Recently, similarity search on high-dimensional feature vectors has become an important search paradigm for various multimedia retrieval applications. The technique used is to map the data items as points into a high-dimensional feature space. The feature space is usually indexed using a multi-dimensional index structure. Similarity search then corresponds to the hyperspherical range query that returns all objects within a threshold level of similarity to the query object [1]. The hyperspherical range query for similarity search can be defined as follows:
36612071
SPY-TEC: An efficient indexing method for similarity search in high-dimensional data spaces
Most of all index structures based on the R-tree have failed to support eAcient indexing mechanisms for similarity search in high-dimensional data spaces. This is due to the fact that most of the index structures commonly use balanced split strategy in order to guarantee storage utilization and the shape of queries for similarity search is a hypersphere in high-dimensional spaces. In this paper, we propose the Spherical Pyramid-Technique (SPY-TEC), an eAcient indexing method for similarity search in high-dimensional data space. The SPY-TEC is based on a special partitioning strategy, which is to divide the d-dimensional data space first into 2d spherical pyramids, and then cut the single spherical pyramid into several spherical slices. This partition provides a transformation of d-dimensional space into one-dimensional space as the Pyramid-Technique [14] does. Thus, we are able to use a B a -tree to manage the transformed one-dimensional data. We also propose the algorithms to process hyperspherical range queries on the data space partitioned by this partitioning strategy. Finally, we show that the SPY-TEC clearly outperforms other related techniques including the Pyramid-Technique in processing hyperspherical range queries through various experiments using synthetic and real data. ” 2000 Elsevier Science B.V. All rights reserved.
6127186
An efficient nearest neighbor search in high-dimensional data spaces
Similarity search in multimedia databases requires an efficient support of nearest neighbor search on a large set of high-dimensional points. A technique applied for similarity search in multimedia databases is to transform important properties of the multimedia objects into points of a high-dimensional feature space. The feature space is usually indexed using a multidimensional index structure. Then, similarity search corresponds to a range search which returns all objects within a threshold level of similarity to the query objects, and a k-nearest neighbor search that returns the k most similar objects to the query object. Initially, traditional multidimensional data structures (e.g., R-tree [1], kd-tree [5]), which were designed for indexing low-dimensional spatial data, were used for indexing high-dimensional feature vectors. However, recent research activities [10,9,8] reported
37965905
Rectilinear Paths among Rectilinear Obstacles
Given a set of obstacles and two distinguished points in the plane the problem of finding a collision-free path subject to a certain optimization function is a fundamental problem that arises in many fields, such as motion planning in robotics, wire routing in VLSI and logistics in operations research. In this survey we emphasize its applications to VLSI design and limit ourselves to the rectilinear domain in which the goal path to be computed and the underlying obstacles are all rectilinearly oriented, i.e., the segments are either horizontal or vertical. We consider different routing environments, and various optimization criteria pertaining to VLSI design, and provide a survey of results that have been developed in the past, present current results and give open problems for future research.
7800252
Imprecise data computation for high performance asynchronous processors
Instruction level parallelism(ILP) is strictly limited by various dependencies. In particular , data dependency is the major performance bottleneck of data intensive applications. To accelerate the execution of sequential code serialized due to data dependencies, this paper proposes an imprecise computation as a fast data computing technique for a high-performance asynchronous processor. To show the performance benefits of the suggested computing model, simulation results are presented. The imprecise computation can be used effectively in data intensive processing with a microprocessor, a Digital Signal Processor or a multimedia processor.
7765148
A formal approach for passive testing of protocol data portions
Passive testing is a process of detecting faults in a system under test by passively observing its input/output behaviors only without interrupting its normal operations, and proves to be a promising technique for network fault management. We study passive testing of data portions of network protocols and present two algorithms, using an event-driven extended finite state machine model. Experimental results on the Internet routing protocol OSPF (open shortest path first) are reported.
36921568
A Study on Key Distribution and ID Registration in the AAA System for Ubiquitous Multimedia Environments
Media environment has been rapidly changed these days. Internet provides multimedia environment and has become a part of our everyday life as a new advertisement media. Authentication methods typically involve an authentication server in the home network from the authentication server of the external network, and then the external network is notified with the authentication result in the home authentication server. This paper discusses and proposes a key distribution protocol that ca be used when the user moves the external network and to ensure secure communication with the external authentication server. As the proposed technology does not receive the reissue of authentication from the home authentication server in case moving between the external authentications servers, authentication server overload can be reduced and the home network can be made to issue the key using the registered password.
19612327
Instruction level redundant number computations for fast data intensive processing in asynchronous processors
Instruction level parallelism (ILP) is strictly limited by various dependencies. In particular, data dependency is a major performance bottleneck of data intensive applications. In this paper we address acceleration of the execution of instruction codes serialized by data dependencies. We propose a new computer architecture supporting a redundant number computation at the instruction level. To design and implement the scheme, an extended data-path and additional instructions are also proposed. The architectural exploitation of instruction level redundant number computations (IL-RNC) makes it possible to eliminate carry propagations. As a result execution of instructions which are serialized due to inherent data dependencies is accelerated. Simulations have been performed with data intensive processing benchmarks and the proposed architecture shows about a 1.2-1.35 fold speedup over a conventional counterpart. The proposed architecture model can be used effectively for data intensive processing in a microprocessor, a digital signal processor and a multimedia processor.