9837737
Attribute-Pair Range Rules
This paper examines the properties of metadata in the form of IF THEN rules which contain two predicates on attributes of a relational database table. For example: a(15. 30) ⟹ d(243. 271), which means “if the value of attribute ‘a’ in a tuple is in the range 15 to 30 then the value of attribute ‘d’ will be in the range 243 to 271.” Metadata of this kind is useful in Semantic Query Optimisation and Remote Cache Management. The two predicates (antecedent and consequent) in each rule are Selection Conditions or constraints of the type found in database queries. Each condition therefore denotes a subset of a database table. Rules can be cascaded, using subrange containment as the link between successive rules. The set of rules can therefore be regarded as a set of edges in a Condition Dependency Graph, and using the rule-set is path discovery in the graph. The purpose of the current paper is to introduce some of the properties of attribute-pair range rules.
11146897
Constructing Inter-relational Rules for Semantic Query Optimisation
Semantic query optimisation is the process by which a user query is transformed into a set of alternative queries each of which returns the same answer as the original. The most efficient of these alternatives is then selected, for execution, using standard cost estimation techniques. The query transformation process is based on the use of semantic knowledge in the form of rules which are generated either during the query process itself or are constructed according to defined heuristics. Previous research has tended to focus on constructing rules applicable to single relations and does not take advantage of the additional semantic knowledge, inherent in most databases, associated with relational joins. Our paper seeks to address this weakness by showing how the rule derivation process may be extended to the generation of inter-relational rules using an approach based on inductive learning.
955470
Improved Data Retrieval Using Semantic Transformation
Semantic query optimisation uses knowledge about properties of the data, represented as a set of subset descriptor rules, to transform a query into another form that can be executed in a more efficient manner but still yields the same result as the original query. Commonly this ’semantic knowledge’ in the form of rules is generated either during the query process itself or else is constructed in advance according to defined heuristics. Over a period of time the rule set may, therefore, become very large and the number of semantically equivalent queries that may be derived rises exponentially. Each rule use creates a new equivalent query. The problem is to identify one near optimal alternative query in a time that is minimal and also short relative to the overall query execution time. In this paper we propose a method for measuring the effectiveness of each rule and present a fast algorithm which selects the most cost effective transformations to directly yield the optimal alternative query. Experiments carried out on a large publicly available dataset show worthwhile savings using the approach.
6242831
Distributing the Derivation and Maintenance of Subset Descriptor Rules
This draft paper describes a solution to the rule maintenance problem for data descriptor rules derived from data that may subsequently change. The method utilises any available computers in the local area network, to derive and maintain rule sets.
14933774
Using a Network of Workstations to Enhance Database Query Processing Performance
Query processing in database systems may be improved by applying parallel processing techniques. One reason for improving query response time is to support the increased number queries when databases are made accessible from the Internet.
15093463
Arithmetic for Parallel Linear Recursive Query Evaluation in Deductive Databases
An arithmetic approach, such as the Level-Finding method described in this paper for evaluating linear recursive queries in deductive database systems provides great potential for parallel processing. It has advantages over other approaches using state-of-the-art parallel processing technology to improve processing speed. In the arithmetic approach, we identify two kind of parallelism, namely bridge node parallelism and formula parallelism. In this paper, the arithmetic foundations and algorithm to exploit formula parallelism were given. The algorithm is fully parallel.
17448440
Effective implementation of cycle time reduction strategies for semiconductor back-end manufacturing
Using discrete event simulation models, a study was conducted to evaluate the current production practices of a high volume semiconductor back-end operation. The overall goal was to find potential areas for productivity improvement that would collectively yield a 60% reduction in manufacturing cycle time. The paper presents the simulation methodology and findings pertaining to analysis of the Assembly, Burn-In, and Test operations. Many of the recommendations identified can be implemented at no additional cost to the factory. The most significant opportunities for improvement are in the Test area, the system constraint. Additionally, the model is extremely sensitive to changes in operator staffing levels, an accurate reflection of many back-end operations. The model shows that the cumulative impact of these recommendations is a 41% reduction in average cycle time, a significant contribution to the overall goal.
14389185
A Machine-Oriented Logic Based on the Resolution Principle
:tb.~tract. Theorem-proving on the computer, using procedures based on the fund~mental theorem of Herbrand concerning the first-order predicate etdeulus, is examined with ~ view towards improving the efticieney and widening the range of practical applicability of these procedures. A elose analysis of the process of substitution (of terms for variables), and the process of t ruth-funct ional analysis of the results of such substitutions, reveals that both processes can be combined into a single new process (called resolution), i terating which is vastty more ef[ieient than the older cyclic procedures consisting of substitution stages alternating with truth-functional analysis stages. The theory of the resolution process is presented in the form of a system of first<~rder logic with .just one inference principle (the resolution principle). The completeness of the system is proved; the simplest proof-procedure based oil the system is then the direct implementation of the proof of completeness. Howew~r, this procedure is quite inefficient, ~nd the paper concludes with a discussion of several principles (called search principles) which are applicable to the design of efficient proof-procedures employing resolution as the basle logical process.
12209685
Measurement driven deployment of a two-tier urban mesh access network
Multihop wireless mesh networks can provide Internet access over a wide area with minimal infrastructure expenditure. In this work, we present a measurement driven deployment strategy and a data-driven model to study the impact of design and topology decisions on network-wide performance and cost. We perform extensive measurements in a two-tier urban scenario to characterize the propagation environment and correlate received signal strength with application layer throughput. We find that well-known estimates for pathloss produce either heavily overprovisioned networks resulting in an order of magnitude increase in cost for high pathloss estimates or completely disconnected networks for low pathloss estimates. Modeling throughput with wireless interface manufacturer specifications similarly results in severely underprovisioned networks. Further, we measure competing, multihop flow traffic matrices to empirically define achievable throughputs of fully backlogged, rate limited, and web-emulated traffic. We find that while fully backlogged flows produce starving nodes, rate-controlling flows to a fixed value yields fairness and high aggregate throughput. Likewise, transmission gaps occurring in statistically multiplexed web traffic, even under high offered load, remove starvation and yield high performance. In comparison, we find that well-known noncompeting flow models for mesh networks over-estimate network-wide throughput by a factor of 2. Finally, our placement study shows that a regular grid topology achieves up to 50 percent greater throughput than random node placement.
6721869
A Performance Study of Deployment Factors in Wireless Mesh Networks
We present a measurement-parameterized performance study of deployment factors in wireless mesh networks using three performance metrics: client coverage area, backhaul tier connectivity, and fair mesh capacity. For each metric, we identify and study topology factors and architectural features which strongly influence mesh performance via an extensive set of Monte Carlo simulations capturing realistic physical layer behavior. Our findings include: (i) A random topology is unsuitable for a large-scale mesh deployment due to doubled node density requirements, yet a moderate level of perturbations from ideal grid placement has a minor impact on performance. (ii) Multiple backhaul radios per mesh node is a cost-effective deployment strategy as it leads to mesh deployments costing 50% less than with a single-radio architecture, (iii) Dividing access and backhaul connections onto two separate radios does not use the second radio efficiently as it only improves fair mesh capacity 40% to 80% for most users. This is in contrast to using the second radio to move half the user population to a new network operated on the second radio. This work adds to the understanding of mesh deployment factors and their general impact on performance, providing further insight into practical mesh deployments.
5441653
Integrating targeted cycle-time reduction into the capital planning process
This paper describes the development and application of an integrated static capacity and dynamic simulation analysis methodology for purchasing equipment capacity. The goal of the study is to address targeted cycle time objectives in a start up recording head wafer manufacturing facility at Seagate Technology, Minneapolis, MN. The short product cycle time, coupled with the competitive nature of the disc drive industry, has made cycle time reduction one of the most important objectives of production capacity planning. This paper describes an equipment procurement strategy in which static capacity analysis is used to identify an initial equipment set with a low slack capacity variable on each tool group. Simulation analysis is then used to identify the critical tool groups that contribute to cycle time delays. The Seagate Industrial Engineering team used the simulation analysis tool Factory Explorer(R) from Wright, Williams and Kelly to perform the cycle time reduction analysis. This targeted approach is compared to the traditional static capacity planning approach of globally applying reserve capacity buffers of 20% or more to achieve the same cycle time reduction goal. Overall, the targeted approach has proven to be efficient in terms of minimizing capital equipment expenditures and also effective on the factory floor.