28568598
Cascade Graphs: Design, Analysis and Algorithms for Relational Joins
The focus of this work is on join optimization in relational database systems. The importance of join optimization is critically underscored by the high cost of relational joins and their frequent needs in traditional as well as emerging database applications. We demonstrate that the sequence in which the pages of the relations are accessed to process a join is a critical determinant of the join execution cost and an optimization of this sequence can lead to a significant improvement in performance over the traditional approaches. We initially develop three network structures to represent a join on two relations:page connectivity graph, cascade andblock tree cascade. A page connectivity graph is a bipartite representation of the set of connected pages in the two relations according to the join predicate. To reveal the structural properties of the join, the nodes of the bipartite graph are ordered into a set of levels, and the resulting isomorphic structure is termed acascade. From the cascade, a tree structure termed ablock tree cascade is derived by selectively grouping nodes at each level of the cascade intoblocks. We formulate the join as a tree traversal process, and accordingly develop efficient tree traversal algorithms. We develop a compact data structure to store the resulting access path, and provide a comprehensive analysis of the algorithms with detailed assessments of their performance. The performance evaluation demonstrates that the proposed approach can result in significant cost savings over the current join processing methods, for low to modest values of the join selectivity factor.
120648016
Theory of convex cones in multicriteria decision making
We develop the theory of convex polyhedral cones in the objective-function space of a multicriteria decision problem. The convex cones are obtained from the decision-maker's pairwise judgments of decision alternatives and are applicable to any quasiconcave utility function. Therefore, the cones can be used in any progressively articulated solution procedure that employs pairwise comparisons. The cones represent convex sets of solutions that are inferior to known solutions to a multicriteria problem. Therefore, these convex sets can be eliminated from consideration while solving the problem. We develop the underlying theory and a framework for representing knowledge about the decision-maker's preference structure using convex cones. This framework can be adopted in the interactive solution of any multicriteria problem after taking into account the characteristics of the problem and the solution procedure. Our computational experience with different multicriteria problems shows that this approach is both viable and efficient in solving practical problems of moderate size.
13648716
EARS: An online bibliographic search and retrieval system based on ordered explosion
Abstract Ergonomics Abstracts Retrieval System (EARS) is an online bibliographic information search and retrieval system using the hierarchical subject classification of the Ergonomics Abstracts . EARS is designed using an inverted file organization and is implemented on CDC-Cyber. The data base of abstracts is organized using a fixed-length record format, where each logical record corresponds to a variable number of fixed-length physical records. Accordingly, an index for the identification of physical records from the logical records is used. The data base is inverted on a three-level hierarchical classification scheme and postings files are used for data base inversion. The data base is accessed after selectively traversing a 4-layer structure of indexes and postings files. EARS provides facilities to perform combinations of searches, limited searches, and certain editing functions. The system is currently used extensively by the Western New York Human Factors research community. The logical and physical designs of EARS, its interactive operational features, and its current expansions are described in this paper.
32066139
Topographically discounted Internet infrastructure resources: a panel study and econometric analysis
The Internet infrastructure is increasingly utilized for the provision and delivery of a variety of services. The rapid growth and substantial demand fluctuations of the supported services are placing strain on the service providers to effectively manage their infrastructure resources. Capacity Provision Network (CPN) is a market-driven mechanism that enables the service providers to efficiently allocate, share and trade service capabilities. Central to the operation of CPN is the notion of discounted capacities which capture the underlying topology of the Internet. It serves as a practical instrument for service providers to evaluate the utility of capacity services available at remote sites vis-à-vis the capacities available locally and from the content providers. We conducted an Internet based longitudinal field experiment to empirically assess and validate the critical properties of discount factors. Our analysis reveals that discount factors exhibit markedly lower volatility than network delays, and are more stable over seasonal and temporal trend patterns. The results related to size effects suggest that sharing and trade agreements with larger content can be particularly effective. Our finding on the existence of the concavity property points to the ability of intermediation services to enhance the overall gains from resource sharing arrangements.
62235624
An efficient approach to stochastic jobshop scheduling: algorithms and empirical investigations
Abstract Jobshop scheduling is one of the important classes of problems planning. The jobshop represents a common manufacturing environment, in which a set of machines is used to process a stream of jobs arriving randomly. The stochastic arrival pattern of the jobs, their processing sequences, and processing times render the scheduling of jobs a complex and difficult task. Furthermore, the scheduling task involves multiple conflicting objectives such as the minimization of the flow time, lateness and the number of late jobs among others. In this research,we develop a framework for the efficient scheduling of jobs considering these multiple objectives. The motivation for this research arises from the good performance of the interactive man-machine scheduling systems in achieving significant levels of attainment in the set of objectives, simultaneously. We develop scheduling strategies to the man-machine approach in this research. The algorithms developed in this research have been extensively tested and evaluated against the traditional scheduling methods using simulation studies. The results show that the proposed approach is efficient and viable for solving practical scheduling problems in the presence of multiple objectives.
6732453
Enterprise computing environments and cost assessment
31851172
Automata-Driven Efficient Subterm Unification
Syntactic unification has widespread use in computing. There are several operations used in deductive computing such as critical pair generation, paramodulation and narrowing that require unifying a term s with every subterm of another term p. This subterm unification problem can be solved naively by repeatedly unifying s with each subterm of p in isolation. The drawback of doing unification in isolation is that commonality among subterms of p is ignored. We present an algorithm for efficient subterm unification by exploiting this commonality. The central idea used in our algorithm is to reduce the common part computation in unification into a string-matching problem and solve it efficiently using a string-matching automaton. The automaton succinctly captures the commonality between subterms of p. The string-matching approach, in conjunction with two new techniques called bidirectional-reduce and marking enables efficient unification of s with every subterm of p.
14332724
Simultaneous Optimization of Design Tolerance and Total Cost for a Piston and Cylinder Assembly
Rapid changes in the market place have led designers and manufacturers to continuously develop new products to satisfy the demands of more exigent customers. Therefore, to be competitive, designers and manufacturers have to perform those steps accurately to ensure final Product quality and manufacturing cost. So Product quality and manufacturing cost have a significant impact on Tolerance. A more scientific approach is often desirable for better performance to overcome this Tolerance problem. In this paper, Design and machining tolerances have been allocated based on optimum total machining cost. New global nonlinear optimization techniques called Pattern Search algorithm and Genetic algorithm have been implemented to find the optimal tolerance allocation and total cost. Finally with respect to total cost both the methods have been compared.
6112702
Nonlinear pattern matching in trees
Tree pattern matching is a fundamental operation that is used in a number of programming tasks such as mechanical theorem proving, term rewriting, symbolic computation, and nonprocedural programming languages. In this paper, we present new sequential algorithms for nonlinear pattern matching in trees. Our algorithm improves upon know tree pattern matching algorithms in important aspects such as time performance, ease of integration with several reduction strategies and ability to avoid unnecessary computation steps on match attempts that fail. The expected time complexity of our algorithm is linear in the sum of the sizes of the two trees.
100663548
La 0.5 Sr 0.5 CoO 3 electrode technology for Pb(Zr,Ti)O 3 thin film nonvolatile memories
Abstract Oxide electrode technology is investigated for optimization of Pb(Zr,Ti)O 3 (PZT) thin film capacitor properties for high density nonvolatile memory applications. PZT thin film capacitors with RF sputter deposited La 0.5 Sr 0.5 CoO 3 (LSCO) electrodes have been characterized with respect to the following parameters: initial dielectric hysteresis loop characteristics, fatigue performance, microstructure and imprint behavior. Our studies have determined that the fatigue of PZT capacitors with LSCO electrodes is less sensitive to B site cation ratio and underlying electrode stack technology than with RuO 2 electrodes. Doping PZT thin films with Nb (PNZT) improves imprint behavior of LSCO//PZT//LSCO capacitors considerably. We have demonstrated that PNZT 4/30/70 // LSCO capacitors thermally processed at either 550°C or 675°C have almost identical initial hysteresis properties and exhibit essentially no fatigue out to approximately 10 10 cycles.
10316561
Variable-depth trie index optimization: theory and experimental results
We develop an efficient approach to Trie index optimization. A Trie is a data structure used to index a file having a set of attributes as record identifiers. In the proposed methodology, a file is horizontally partitioned into subsets of records using a Trie index whose depth of indexing is allowed to vary. The retrieval of a record from the file proceeds by “stepping through” the index to identify a subset of records in the file in which a binary search is performed. This paper develops a taxonomy of optimization problems underlying variable-depth Trie index construction. All these problems are solvable in polynomial time, and their characteristics are studied. Exact algorithms and heuristics for their solution are presented. The algorithms are employed in CRES-an expert system for editing written narrative material, developed for the Department of the Navy. CRES uses several large-to-very-large dictionary files for which Trie indexes are constructed using these algorithms. Computational experience with CRES shows that search and retrieval using variable-depth Trie indexes can be as much as six times faster than pure binary search. The space requirements of the Tries are reasonable. The results show that the variable-depth Tries constructed according to the proposed algorithms are viable and efficient for indexing large-to-very-large files by attributes in practical applications.