20308502
Object signatures for supporting efficient navigation in object-oriented databases
Most methods that have been proposed to improve query processing in object-oriented databases are designed for the aggregation hierarchy. Although the structure of the generalization hierarchy is similar to the aggregation hierarchy, techniques developed for the aggregation hierarchy cannot fully use the characteristics of the generalization hierarchy to improve performance. We devise a new object signature for the generalization hierarchy. The object signature consists of two parts: a reference signature and a structure signature. The former can be used to eliminate objects that do not match the nested predicates specified in the query, and the latter can be used to eliminate objects that do not belong to the target classes. We propose some processing methods using the object signatures for queries that involve generalization hierarchies. In addition, we define cost models of the object signature and then compare the performance of the traditional query processing method with the object signature method. The results show that using the object signatures can effectively reduce the number of disk accesses in a query.
31930663
Minimization of resource consumption for multidatabase query optimization
Due to the autonomy of individual databases, a multidatabase system (MDBS) has no control over the task execution within each database system. This complicates the issue of query optimization in a MDBS. Past researchers tackled this problem mainly by regenerating the cost model of each participating database systems. However a completely autonomous participating database system does nor own the information (data) as well as the mechanism (software) for converting data of one database to another to resolve the data type conflict problems that can occur in any MDBS environment. In addition, unpredictable factors that can drastically deviate the accuracy of a regenerated cost model (in the past research) come into play at unknown time. This confines the processing of an intersite operation (such as a join over two relations of different databases) to the MDBS only. The participating database systems will not be able to share the workload of the MDBS under this circumstance. Hence, minimizing the consumption of system resources of the MDBS is an urgent problem. The authors propose three scheduling algorithms that are used in the MDBS to reduce the processing cost of a multidatabase query. A major difference between the strategies and the past methods is that ours do not require the knowledge of the cost models of the participating databases.
18796888
Design and Performance Evaluation of Broadcast Algorithms for Time-Constrained Data Retrieval
We refer "time-constrained services" to those requests that have to be replied to within a certain client-expected time duration. If the answer cannot reach the client within this expected time, the value of the information may seriously degrade or even become useless. On-demand channels may not be able to handle all time-constrained services without degrading the performance. How to handle these services in broadcast channels becomes crucial to balance the load of wireless systems. In this paper, we study this problem and find the minimum number of broadcast channels required for such a task. Also, we propose solutions for this problem when the available channels are insufficient. Our performance result reveals that only a moderate number of channels is required to promote these time-constrained services
2862791
A data delivery strategy in ubiquitous computing systems
Browsing Web pages through wireless devices will become more and more popular in the near future. However, accessing a large chunk of Web data incurs a great amount of access latency while a mobile user migrates across cells. This paper investigates this problem and proposes an effective way of delivering such data to a mobile user in a ubiquitous computing system. Our data delivery (/spl Dscr//sup 2/) strategy is based on the dynamic programming skill needed to pre-assign the user-requested data on the possible cells to be visited in order to reduce the access latency. We first design an encoding method for the cells and then derive the properties of the encoding scheme. These properties are then used in our algorithm to deliver the data. Finally, experiments are conducted to demonstrate the feasibility and efficiency of the proposed method.
34408109
Modeling GIS Data Using OMEGA
9253270
Query Optimization in Multidatabase Systems Considering Schema Conflicts
In a multidatabase system, the participating databases are autonomous. The schemas of these databases may be different in various ways, while the same information is represented. A global query issued against the global database needs to be translated to a proper form before it can be executed in a local database. Since data requested by a query (or a part of a query) is sometimes available in multiple sites, the site (database) that processes the query with the least cost is the desired query processing site. The authors study the effect of differences in schemas on the cost of query processing in a multidatabase environment. They first classify schema conflicts to different types. For each type of conflict, they show how much more or less complex a translated query can become in comparison with the originally user-issued global query. Based on this observation, they propose an analytical method that considers the conflicts between local databases and finds the database(s) that renders the least execution cost in processing a global query. This research introduces a new level of query optimization (termed the schema-level optimization) in multidatabase environments. The results provide a new dimension of enhancement for the capability of a query optimizer in multidatabase systems.
32239506
An intelligent fuzzy agent for meeting scheduling decision support system
Abstract An Intelligent Fuzzy Agent for Meeting Scheduling Decision Support System is proposed in this paper. The proposed Intelligent Fuzzy Agent including Meeting Negotiation Agent, Fuzzy Inference Agent and Genetic Learning Agent can search and decide the suitable meeting time for the specified meeting in an organization. When a meeting host requests a meeting, the Meeting Negotiation Agent immediately sends the invitees’ names to Meeting Scheduling Decision Support System for retrieving their schedules from Group Calendar Data Base, then Meeting Scheduling Decision Support System will compute the possible meeting time and respond the results to Meeting Negotiation Agent. Moreover, the Fuzzy Inference Agent infers the adequate meeting time based on the information provided by Meeting Negotiation Agent and Personalized Knowledge Base, and sends the computing result back to Meeting Scheduling Decision Support System. The meeting host will decide the final meeting time based on Meeting Scheduling Decision Support System and announce the meeting information by various devices including PDA, WAP, FAX, or E-mail. Furthermore, the invitees’ decisions for attending the meeting or not will be stored into Meeting Information Knowledge Base, then the Genetic Learning Agent will adjust the Personalized Knowledge Base for the next meeting. By the experimental results, the proposed Intelligent Fuzzy Agent can work efficiently and effectively for Meeting Scheduling Decision Support System.
2595872
Schedulability Envelope for Real-Time Radar Dwell Scheduling
This paper proposes novel techniques for scheduling radar dwells in phased array radar systems. In order to handle complex physical characteristics such as dwell interleaving, transmitting duty cycle constraint, and energy constraint, we propose a notion of schedulability envelope. The schedulability envelope designed offline hides the details of complex radar dwell scheduling and provides a simple measure for the schedulability check. Using the schedulability envelope, the proposed technique can efficiently perform the admission control for dynamic target tracking tasks. The simulation results show that the proposed approach can significantly improve the system utilization by taking advantage of dwell interleaving while guaranteeing the schedulability and physical constraints
2900634
Radar dwell scheduling considering physical characteristics of phased array antenna
This paper proposes novel techniques for scheduling radar dwells in phased array radar systems. In order to handle complex physical characteristics such as dwell interleaving, transmitting duty cycle constraint, and energy constraint, we propose a notion of schedulability envelope. The schedulability envelope designed offline hides the details of complex radar dwell scheduling and provides a simple measure for the schedulability check. Using the schedulability envelope, the proposed technique can efficiently perform the admission control for dynamic target tracking tasks. The simulation results show that the proposed approach can significantly improve the system utilization by taking advantage of dwell interleaving while guaranteeing the schedulability and physical constraints.
207558887
Self-adaptive neuro-fuzzy systems for autonomous underwater vehicle control
This paper presents a systematic approach for developing a concise self-adaptive neurofuzzy inference system (SANFIS) with a fast hybrid parameter learning algorithm for on-line learning of the control knowledge for autonomous underwater vehicle (AUV) control. The multi-layered network structure of SANFIS incorporates fuzzy basis functions for better function approximations. We investigate three SANFIS structures with three different types of fuzzy IF-THEN rule-based models and cast the rule formation problem as a clustering problem. A recursive least-squares algorithm and a modified Levenberg-Marquardt algorithm with limited memory are exploited to accelerate the parameter learning process. This hybrid parameter learning algorithm together with an on-line clustering technique and rule examination provide SANFIS with the capability of selforganizing and self-adapting its internal structure (i.e. the fuzzy rules and term sets) for learning the required control knowledge for an AUV to follow desired trajectories. Computer simulations for modeling a control system for an AUV have been conducted to validate the effectiveness of the proposed SANFIS.
14565413
Performance Modeling of HPC Applications
Publisher Summary This chapter discusses the performance modeling of high performance computing (HPC) applications. Performance models of applications enable HPC system designers and centers to gain insight into the most optimal hardware for their applications, giving them valuable information into the components of hardware that for a certain investment of time/money will give the most benefit for the applications slated to run on the new system. The task of developing accurate performance models for scientific application on such complex systems can be difficult. The chapter briefly review a framework developed that provides an automated means for carrying out performance modeling investigations. The ongoing work to lower the overhead required for obtaining application signatures is discussed, and how one can increased the level-of-detail of convolutions with resulting improvements in modeling accuracy is explained. The chapter discusses how these technology advances enabled performance studies to explain why performance of applications, such as POP (Parallel Ocean Program), NLOM (Navy Layered Ocean Model), and Cobalt60, vary on different machines and quantifies the performance effect of various components of the machines. The chapter concludes by generalizing these results to show how this application's performance would likely improve if the underlying target machines were improved in various dimensions.