18316669
On Linear-Spline Based Histograms
Approximation is a very effective paradigm to speed up query processing in large databases. One popular approximation mechanism is data size reduction. There are three reduction techniques: sampling, histograms, and wavelets. Histogram techniques are supported by many commercial database systems, and have been shown very effective for approximately processing aggregation queries. In this paper, we will investigate the optimal models for building histograms based on linear spline techniques. We will firstly propose several novel models. Secondly, we will present efficient algorithms to achieve these proposed optimal models. Our experiment results showed that our new techniques can greatly improve the approximation accuracy comparing to the existing techniques.
3994784
Error minimization for approximate computation of range aggregates
Histogram techniques are widely used in commercial database management systems for an estimation of query results. Recently, they have been also used in approximately, processing database queries, especially aggregation queries. Existing research results in this area have been mainly focused on constructing a histogram to approximately represent, as accurate as possible on an intuitive base, the original data frequencies. We propose a novel histogram construction method aiming to minimize the average approximate aggregation errors; and we have developed an efficient algorithm to construct near optimal histograms to achieve this goal. Our experiment results showed that the new histogram construction techniques lead to more accurate results than those by existing histogram techniques, and also out-perform the existing wavelet techniques.
3992721
Error minimization in approximate range aggregates
Histogram techniques have been used in many commercial database management systems to estimate a query result size. Recently, it has been shown that they are very effective to support approximation of query processing especially aggregates. In this paper, we investigate the problem of minimizing average errors of approximate aggregates using histogram techniques. Firstly, we present a novel linear-spline histogram model that is more accurate than the existing models. Secondly, we propose a novel histogram construction technique for minimizing such average errors, which is shown to generate a near optimal histogram. Our experiment results demonstrate that the new histogram construction techniques lead to a great accuracy improvement on the existing techniques.
2285434
Towards multidimensional subspace skyline analysis
The skyline operator is important for multicriteria decision-making applications. Although many recent studies developed efficient methods to compute skyline objects in a given space, none of them considers skylines in multiple subspaces simultaneously. More importantly, the fundamental problem on the semantics of skylines remains open: Why and in which subspaces is (or is not) an object in the skyline? Practically, users may also be interested in the skylines in any subspaces. Then, what is the relationship between the skylines in the subspaces and those in the super-spaces? How can we effectively analyze the subspace skylines? Can we efficiently compute skylines in various subspaces and answer various analytical queries?In this article, we tackle the problem of multidimensional subspace skyline computation and analysis. We explore skylines in subspaces. First, we propose the concept of Skycube, which consists of skylines of all possible nonempty subspaces of a given full space. Once a Skycube is materialized, any subspace skyline queries can be answered online. However, Skycube cannot fully address the semantic concerns and may contain redundant information. To tackle the problem, we introduce a novel notion of skyline group which essentially is a group of objects that coincide in the skylines of some subspaces. We identify the decisive subspaces that qualify skyline groups in the subspace skylines. The new notions concisely capture the semantics and the structures of skylines in various subspaces. Multidimensional roll-up and drill-down analysis is introduced. We also develop efficient algorithms to compute Skycube, skyline groups and their decisive subspaces. A systematic performance study using both real data sets and synthetic data sets is reported to evaluate our approach.
2460253
Approximate processing of massive continuous quantile queries over high-speed data streams
Quantile computation has many applications including data mining and financial data analysis. It has been shown that an /spl epsi/-approximate summary can be maintained so that, given a quantile query (/spl phi/,/spl epsi/), the data item at rank /spl lceil//spl phi/N/spl rceil/ may be approximately obtained within the rank error precision /spl epsi/N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different /spl phi/ and /spl epsi/ poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.
3022359
CVSSearch: searching through source code using CVS comments
CVSSearch is a tool that searches for fragments of source code by using CVS comments. CVS is a version control system that is widely used in the open source community. Our search tool takes advantage of the fact that a CVS comment typically describes the lines of code involved in the commit and this description will typically hold for many future versions. In other words, CVSSearch allows one to better search the most recent version of the code by looking at previous versions to better understand the current version. In this paper we describe our algorithm for mapping CVS comments to the corresponding source code, present a search tool based on this technique, and discuss preliminary feedback.
14103418
Front Tracking: A Parallelized Approach for Internal Boundaries and Interfaces
Internal boundaries and interfaces are an important part of many fluid and solid modeling problems. Front Tracking contains a general interface framework, closely related to the non-manifold geometry used in CAD solid modeling packages, to support numerical simulation of such fluid problems. It can thus be considered to be a systematic application of the ideas of computational geometry to computational fluid dynamics. It is based on the principle that finite differences behave best when applied to differentiable functions, and that weak derivatives of nondifferentiable functions can be replaced by regularized expressions such as jump conditions. Front Tracking offers superior resolution for fluid problems with important discontinuities and interfaces, and in some cases, it has provided the unique method to obtain correct answers. Here we present Computer Science issues which have contributed to the success of Front Tracking: software design and organization — modularity, data structures and data hiding.
11623385
Resource allocation for multimedia streaming over the Internet
This paper addresses the resource allocation problem for multiple media streaming over the Internet. First, we present an end-to-end transport architecture for multimedia streaming over the Internet. Second, we propose a new multimedia streaming TCP-friendly protocol (MSTFP), which combines forward estimation of network conditions with information feedback control to optimally track the network conditions. Third, we propose a novel resource allocation scheme to adapt media rate to the estimated network bandwidth using each media's rate-distortion function under various network conditions. By dynamically allocating resources according to network status and media characteristics, we improve the end-to-end quality of services (QoS). Simulation results demonstrate the effectiveness of our proposed schemes.
16216432
A Multiobjective Differential Evolution Based on Decomposition for Multiobjective Optimization with Variable Linkages
Although a number of multiobjective evolutionary algorithms have been proposed over the last two decades, not much effort has been made to deal with variable linkages in multiobjective optimization. Recently, we have suggested a general framework of multiobjective evolutionary algorithms based on decomposition (MOEA/D) [1]. MOEA/D decomposes a MOP into a number of scalar optimization subproblems by a conventional decomposition method. The optimal solution to each of these problems is a Pareto optimal solution to the MOP under consideration. An appropriate decomposition could make these individual Pareto solutions evenly distribute along the Pareto optimal front. MOEA/D aims at solving these scalar optimization subproblems simultaneously. In this paper, we propose, under the framework of MOEA/D, a multiobjective differential evolution based decomposition (MODE/D) for tackling variable linkages. Our experimental results show that MODE/D outperforms several other MOEAs on several test problems with variable linkages.
7426259
Modelling the Population Distribution in Multi-objective Optimization by Generative Topographic Mapping
Under mild conditions, the Pareto set of a continuous multi-objective optimization problem exhibits certain regularity. We have recently advocated taking into consideration such regularity in designing multi-objective evolutionary algorithms. Following our previous work on using Local Principal Component Analysis for capturing the regularity, this paper presents a new approach for acquiring and using the regularity of the Pareto set in evolutionary algorithms. The approach is based on the Generative Topographic Mapping and can be regarded as an Estimation of Distribution Algorithm. It builds models of the distribution of promising solutions based on regularity patterns extracted from the previous search, and samples new solutions from the models thus built. The proposed algorithm has been compared with two other state-of-the-art algorithms, NSGA-II and SPEA2 on a set of test problems.
1741788
A Compound TCP Approach for High-Speed and Long Distance Networks
Many applications require fast data transfer over high speed and long distance networks. However, standard TCP fails to fully utilize the network capacity due to the limitation in its conservative congestion control (CC) algorithm. Some works have been proposed to improve the connection 鈂s throughput by adopt- ing more aggressive loss-based CC algorithms. These algorithms, although can effectively improve the link utilization, have the weakness of poor RTT fairness. Further, they may severely de- crease the performance of regular TCP flows that traverse the same network path. On the other hand, pure delay-based ap- proaches that improve the throughput in high-speed networks may not work well when the traffic is mixed with both delay- based and greedy loss-based flows. In this paper, we propose a novel Compound TCP (CTCP) approach, which is a synergy of delay-based and loss-based approach. Specifically, we add a scal- able delay-based component into the standard TCP Reno conges- tion avoidance algorithm (a.k.a., the loss-based component). The sending rate of CTCP is controlled by both components. This new delay-based component can rapidly increase sending rate when network path is under utilized, but gracefully retreat in a busy network when bottleneck queue is built. Augmented with this delay-based component, CTCP provides very good bandwidth scalability with improved RTT fairness, and at the same time achieves good TCP-fairness, irrelevant to the windows size. We developed an analytical model of CTCP and implemented it on the Windows operating system. Our analysis and experiment results verify the properties of CTCP.