A/sup */ search: an efficient and flexible approach to materialized view selection

Decision support systems issue a large number of online analytical processing (OLAP) queries to access very large databases. A data warehouse needs to precompute or materialize some of such OLAP queries in order to improve the system throughput, since many coming queries can benefit greatly from these materialized views. Materialized view selection with resource constraint is one of the most important issues in the management of data warehouses. It addresses how to fully utilize the limited resource, disk space, or maintenance time to minimize the total query processing cost. This paper revisits the problem of materialized view selection under a disk-space constraint S. Many efficient greedy algorithms have been developed to address this problem. The quality of greedy solutions is guaranteed by a lower bound. However, it is observed that, when S is small, this lower bound can be very small and even be negative. In such cases, their solution quality will not be guaranteed well. In order to improve further the solution quality in such cases, a new competitive A/sup */ algorithm is proposed. It is shown that it is just the distinctive topological structure of the dependent lattice that makes the A/sup */ search a very competitive strategy for this problem. Both theoretical and experimental results show that the proposed algorithm is a powerful, efficient, and flexible approach to this problem.     

An approach to computer control research in a university environment

The general problem of research in the university environment is outlined with specific reference to research in the area of computer control of systems. An approach is presented based on experience with the industrially supported research program at Case Western Reserve University in the control of complex systems. The paper is organized around five aspects of the Case program as follows: 1) definition of scope, research direction, and overall objectives; 2) relationship with students: how a typical study is formulated and carried out; 3) relationship with sponsors: funding and two-way information flow; 4) relationship with the University: the Systems Research Center provides motivation, administrative support, and facilities for interdisciplinary activity; 5) historical development. A specific case history is presented to illustrate some of the above points and, in particular, show how the program has evolved along new directions in response to inputs from members of the group and from the outside community.     

An evolutionary approach to visual sensing for vehicle navigation

This paper presents an evolutionary approach able to process a digital image and detect tracks left by preceding vehicles on ice and snow in Antarctica. Biologically inspired by a colony of ants able to interact and cooperate to determine the shortest path to the food, this approach is based on autonomous agents moving along the image pixels and iteratively improving an initial coarse solution. The unfriendly Antarctic environment makes this image analysis problem extremely challenging, since light reflections, abruptly varying brightness conditions, and different terrain slopes must be considered as well. The ant-based approach is compared to a more traditional Hough-based solution and the results are discussed.     

An integrated approach to project evaluation and selection

Effective project evaluation necessitates incorporating the many conflicting objectives of decision maker(s) into decision models. Among the many proposed methodologies of multicriteria decision making, goal programming is perhaps the most popular and widely used. Although it incorporates multiple objectives and arrives at an optimal solution, its major drawback is that the decision maker(s) must specify goals and priorities a priori. To overcome this problem the Delphi method is suggested to be applied prior to goal programming formulation so that the objectives and their corresponding aspiration levels can be identified. Another drawback of goal programming is that it does not provide a systematic approach to set priorities and trade-offs among objectives. For this purpose an analytical hierarchy process is used. The application of the proposed methodology is then discussed and illustrated through an example     

An evolutionary approach to designing complex spreading codes for DS-CDMA

This paper proposes a novel evolutionary approach to spreading code design in direct sequence code division multiple access (DS-CDMA). Specifically, a multiobjective evolutionary algorithm (EA) is used to generate complex spreading sequences that are optimized with respect to the average mean-square cross- and/or autocorrelation (CC and/or AC) properties. A theoretical model is developed in order to demonstrate the optimality of the generated codes. The proposed algorithm enables spreading code design with no constraints on the code length. Furthermore, it is possible to generate K/spl ges/N codes of length N with very little cost in correlation properties. This results in significant capacity enhancement in DS-CDMA systems.     

An evolutionary approach for gene expression patterns

This study presents an evolutionary algorithm, called a heterogeneous selection genetic algorithm (HeSGA), for analyzing the patterns of gene expression on microarray data. Microarray technologies have provided the means to monitor the expression levels of a large number of genes simultaneously. Gene clustering and gene ordering are important in analyzing a large body of microarray expression data. The proposed method simultaneously solves gene clustering and gene-ordering problems by integrating global and local search mechanisms. Clustering and ordering information is used to identify functionally related genes and to infer genetic networks from immense microarray expression data. HeSGA was tested on eight test microarray datasets, ranging in size from 147 to 6221 genes. The experimental clustering and visual results indicate that HeSGA not only ordered genes smoothly but also grouped genes with similar gene expressions. Visualized results and a new scoring function that references predefined functional categories were employed to confirm the biological interpretations of results yielded using HeSGA and other methods. These results indicate that HeSGA has potential in analyzing gene expression patterns.     

An expert system-based approach to capacity allocation in amultiservice application environment

The problem of bandwidth allocation for multiservice packet networks is discussed, and an expert system solution approach for solving it is described. The approach requires a minimal amount of processing, is very efficient, and has a fast response time. The implementation is based on modular capacity expansions and a priori limits on the number of connections for each service type. This approach can perform near-optimal capacity allocation in real time by using heuristic knowledge to virtually eliminate the required computations in this process. This implementation strategy ensures that each service demand meets its objectives. Concurrency control of this distributed expert system is considered. The advantages of the implementation in providing the ability to make rational decisions in an environment of uncertainty and imprecision, such as in the presence of nonsystematic overloads and network failures, are discussed     

An evolutionary spectrum approach to modeling non‐stationary fading channels

To evaluate mobile communication systems, it is important to develop accurate and concise fading channel models. However, fading encountered in mobile communication is usually non‐stationary, and the existing methods can only model quasi‐stationary or piecewise‐stationary fading instead of general non‐stationary fading. To address this, this paper proposes an evolutionary spectrum (ES)‐based approach to modeling non‐stationary fading channels. Our ES approach is more general than the existing piecewise‐stationary models and is capable of characterizing a general non‐stationary fading channel that has an arbitrary ES (or time‐varying power spectral density); our ES approach is parsimonious and is also able to generate stationary fading processes. As an example, we show how to apply our ES approach to generating stationary and non‐stationary correlated Nakagami‐m fading channel processes. Simulation results show that the ES of the channel gain process produced by our ES‐based channel model agrees well with the user‐specified ES, indicating the accuracy of our ES‐based channel model. Copyright © 2011 John Wiley & Sons, Ltd.     

An interactive approach to R&D project selection andtermination

A decision support tool is developed that can be used by the R&D manager to effectively update his or her portfolio when a review is called for. The approach is interactive and builds on two sets of critical factors. Initially, projects are screened to see if they are at an acceptable level, and if they are making reasonable progress toward completion. Those failing the test are terminated, those remaining are weighed with candidate projects to determine which should be included in the portfolio. This is achieved with a mathematical programming routine that maximizes expected returns. A case study centering on a peripheral equipment manufacturer is presented to demonstrate the methodology     

多专业网连接性业务管理研究

根据多专业网连接性业务的管理需求,基于电信运营图(TOM,Telecom Operations Map),提出了连接性业务的管理框架,以实现多专业网连接性业务配置和维护的自动化;讨论了多专业网连接性业务管理框架中多专业网综合网管系统和专业网网管系统之间的管理接口;提出了配置和故障管理的管理接口功能需求和信息模型;以及基于 CORBA的实现。     

一种室内环境下机器人同时定位与地图构建方法

介绍了一种移动机器人室内环境下同时定位与地图构建方法，给出了整个系统的结构框图。将从激光传感信息中提取出的直线特征作为主要的环境描述特征，用EKF算法更新机器人位姿和直线特征的估计值，用一种新的数据关联方法以实现地图的最小描述。直线特征提取采改进的IE2F算法，能够快速地从数据点中得到较为精确的直线参数。实验证明整个系统具有良好的性能。     

A fuzzy-logic-based approach to project selection

When making decisions we need to consider the possible alternatives and then choose the optimal alternative. The uncertainty of subjective judgment is present during this selection process. Also, decision making becomes difficult when the available information is incomplete or imprecise. This kind of problem exists while selecting a project. There are also several critical factors that are involved in the selection process, including market conditions, availability of raw materials, etc. The decision mechanism is constrained by the uncertainty inherent in the determination of the relative importance of each attribute element. In this paper, me develop a system for the project selection using fuzzy logic. Fuzzy logic enables us to emulate the human reasoning process and make decisions based on vague or imprecise data. Our approach is based on uncertainty reduction. The optimal alternative is formed by the relative weights of each attribute's elements combined over all the attribute membership functions. We also do a case study for the selection of software packages. Our system could be easily applied to other project selection problems under uncertainty     

Automated network selection in a heterogeneous wireless network environment

Service delivery in a heterogeneous all-IP wireless network environment requires the selection of an optimal access network. Selection of a non-optimal network can result in undesirable effects such as higher costs or poor service experience. Network selection in such an environment is influenced by several factors, and currently a complete solution is not available to solve this problem. This article describes a comprehensive decision making process to rank candidate networks for service delivery to the terminal. The proposed mechanism is based on a unique decision process that uses compensatory and non-compensatory multi-attribute decision making algorithms jointly to assist the terminal in selecting the top candidate network     

An evolutionary bargaining‐based approach for incentivized cooperation in opportunistic networks

Opportunistic networking enables users to communicate in an environment where connectivity is intermittent or unstable. However, such networking scheme assumes that mobile nodes voluntary cooperate, which cannot be guaranteed. Some nodes can simply exhibit selfish behavior and thus diminish the effectiveness of the approach. In this paper, a game scenario is formulated in which the nodes try to convince each other to participate in packets forwarding. Each node is considered as a player in this game. When a node comes in the communication range of another, a bargaining game starts between them as part of the message forwarding process. Both players try to have a mutual agreement on a price for message forwarding. We present a new incentive mechanism called evolutionary bargaining‐based incentive scheme (EBIS) to motivate selfish nodes to cooperate in data forwarding. In EBIS, a node negotiates with other nodes to obtain an agreeable amount of credit for its forwarding service. Nodes apply a sequential bargaining game and then adapt their strategies using an evolutionary model to maximize the probability of reaching an agreement. Unlike classical bargaining games, nodes in our model are boundedly rational. In addition, we use the evolutionary stable strategy (ESS) concept to determine the adaptive strategies for the nodes. The comparison of EBIS with a benchmarked model demonstrates that EBIS performs better in terms of packet delivery ratio and average latency.     

A vector space approach to direction finding in a coherent multipath environment

The superresolution methods of spatial spectrum estimation heretofore reported are known to break down when arriving signals from different directions are coherent. It is shown here that this deficiency can be overcome by replacing the direction-of-arrival (DOA) search vector ordinarily used with a linear combination of such vectors. Particular attention is here given to extending the multiple signal classification (MUSIC) method to cover such cases. A procedure for determining the proper linear combination is presented so that determination of the separate coherent signal arrival angles involves a multidimensional search in angle only. Such a search is demonstrated for coherent two-ray and three-ray multipath environments.     

A combinatorial approach to content-based music selection

Accessing large digital music catalogues raises a problem for both users and content providers. We propose a novel approach to music selection called RecitalComposer, which is based on computing coherent sequences of music titles. This amounts to solving a combinatorial pattern generation problem by using constraint satisfaction techniques     

A cross-layer approach to transmit antenna selection

In this paper, we investigate a cross-layer approach to transmit antenna selection capable of adapting the number of active antennas to varying channel conditions. We address a cross-layer methodology in the sense that the criterion for the selection of antenna subsets is the maximization of link layer throughput which takes into account characteristics both at the physical and link layers. In order to enhance system performance, adaptive modulation is included to jointly perform antenna selection and rate adaptation. Performance assessment is conducted in terms of link layer throughput and transmission delay.     

Power density aware application mapping in mesh-based network-on-chip architecture: An evolutionary multi-objective approach

In the era of many-core chips, the problem of power density is a serious challenge. This is particularly important in Network-on-Chip (NoC)-based systems, where application mapping determines the resulting power patterns and the workload distribution across the entire chip. Despite this fact, the majority of mapping algorithms focus on performance, and the resulting power patterns are largely ignored. This work investigates this problem. Three different power pattern metrics with different scopes are defined, namely, power peak, power range, and regional power density. The results of using them as mapping objectives together with communication cost using a multi-objective evolutionary mapping approach are investigated. Results show that employing power patterns results-in Pareto fronts with different power patterns and features. Results are analysed and discussed. Moreover, a case study of thermal analysis of the resulting power patterns is performed. Results show that using communication cost only results-in large hotspots which translates into higher peak and range of chip temperatures. The proposed mapping objectives are shown to significantly improve thermal balancing (up to 55%) and peak temperature (up to 7.77%). These results indicate the importance of considering power patterns in the design of NoC-based many-core systems and their direct impact on the reliability and performance of such systems.     

A neural network approach to MMSE receivers in a DS-CDMA multipath fading environment

This letter deals with an advanced minimum mean-squared error receiver for applications to uplink transmissions in a multiuser code-division multiple-access system. The receiver is implemented by means of a suitable neural network in order to enhance the receiver convergence speed in the case of fast fading. Performance comparisons with classical approaches highlights a better behavior for the proposed scheme.