10621466
Regression Cubes with Lossless Compression and Aggregation
As OLAP engines are widely used to support multidimensional data analysis, it is desirable to support in data cubes advanced statistical measures, such as regression and filtering, in addition to the traditional simple measures such as count and average. Such new measures allow users to model, smooth, and predict the trends and patterns of data. Existing algorithms for simple distributive and algebraic measures are inadequate for efficient computation of statistical measures in a multidimensional space. In this paper, we propose a fundamentally new class of measures, compressible measures, in order to support efficient computation of the statistical models. For compressible measures, we compress each cell into an auxiliary matrix with a size independent of the number of tuples. We can then compute the statistical measures for any data cell from the compressed data of the lower-level cells without accessing the raw data. Time- and space-efficient lossless aggregation formulae are derived for regression and filtering measures. Our analytical and experimental studies show that the resulting system, regression cube, substantially reduces the memory usage and the overall response time for statistical analysis of multidimensional data
832740
Constrained genetic algorithms and their applications in nonlinear constrained optimization
The paper presents a problem-independent framework that unifies various mechanisms for solving discrete constrained nonlinear programming (NLP) problems whose functions are not necessarily differentiable and continuous. The framework is based on the first-order necessary and sufficient conditions in the theory of discrete constrained optimization using Lagrange multipliers. It implements the search for discrete-neighborhood saddle points (SP/sub dn/) by performing ascents in the original-variable subspace and descents in the Lagrange-multiplier subspace. Our study on the various mechanisms shows that CSAGA, a combined constrained simulated annealing and genetic algorithm, performs well. Finally, we apply iterative deepening to determine the optimal number of generations in CSAGA.
9555510
Long-Distance Mutual Exclusion for Propositional Planning
The use of mutual exclusion (mutex) has led to significant advances in propositional planning. However, previous mutex can only detect pairs of actions or facts that cannot be arranged at the same time step. In this paper, we introduce a new class of constraints that significantly generalizes mutex and can be efficiently computed. The proposed long-distance mutual exclusion (londex) can capture constraints over actions and facts not only at the same time step but also across multiple steps. Londex provides a powerful and general approach for improving planning efficiency. As an application, we have integrated londex into SATPLAN04, a leading optimal planner. Experimental results show that londex can effectively prune the search space and reduce the planning time. The resulting planner, MaxPlan, has won the First Place Award in the Optimal Track of the 5th International Planning Competition.
5374807
Automated Planning and Scheduling using Calculus of Variations in Discrete Space
In this paper, we propose new dominance relations that can speed up significantly the solution process of planning problems formulated as nonlinear constrained dynamic optimization in discrete time and space. We first show that path dominance in dynamic programming cannot be applied when there are general constraints that span across multiple stages, and that node dominance, in the form of Euler-Lagrange conditions developed in optimal control theory in continuous space, cannot be extended to that in discrete space. This paper is the first to propose efficient node-dominance relations, in the form of local saddle-point conditions in each stage of a discrete-space planning problem, for pruning states that will not lead to locally optimal paths. By utilizing these dominance relations, we present efficient search algorithms whose complexity, despite exponential, has a much smaller base as compared to that without using the relations. Finally, we demonstrate the performance of our approach by integrating it in the ASPEN planner and show significant improvements in CPU time and solution quality on some spacecraft scheduling and planning benchmarks.
14272034
Optimal Anytime Constrained Simulated Annealing for Constrained Global Optimization
In this paper we propose an optimal anytime version of constrained simulated annealing (CSA) for solving constrained nonlinear programming problems (NLPs). One of the goals of the algorithm is to generate feasible solutions of certain prescribed quality using an average time of the same order of magnitude as that spent by the original CSA with an optimal cooling schedule in generating a solution of similar quality. Here, an optimal cooling schedule is one that leads to the shortest average total number of probes when the original CSA with the optimal schedule is run multiple times until it finds a solution. Our second goal is to design an anytime version of CSA that generates gradually improving feasible solutions as more time is spent, eventually finding a constrained global minimum (CGM). In our study, we have observed a monotonically non-decreasing function relating the success probability of obtaining a solution and the average completion time of CSA, and an exponential function relating the objective target that CSA is looking for and the average completion time. Based on these observations, we have designed CSAAT-ID the anytime CSA with iterative deepening that schedules multiple runs of CSA using a set of increasing cooling schedules and a set of improving objective targets. We then prove the optimality of our schedules and demonstrate experimentally the results on four continuous constrained NLPs. CSAAT-ID can be generalized to solving discrete, continuous, and mixed-integer NLPs, since CSA is applicable to solve problems in these three classes. Our approach can also be generalized to other stochastic search algorithms, such as genetic algorithms, and be used to determine the optimal time for each run of such algorithms.
12806220
Temporal Planning using Subgoal Partitioning and Resolution in SGPlan
In this paper, we present the partitioning of mutual-exclusion (mutex) constraints in temporal planning problems and its implementation in the SGPlan4 planner. Based on the strong locality of mutex constraints observed in many benchmarks of the Fourth International Planning Competition (IPC4), we propose to partition the constraints of a planning problem into groups based on their subgoals. Constraint partitioning leads to significantly easier subproblems that are similar to the original problem and that can be efficiently solved by the same planner with some modifications to its objective function. We present a partition-and-resolve strategy that looks for locally optimal subplans in constraint-partitioned temporal planning subproblems and that resolves those inconsistent global constraints across the subproblems. We also discuss some implementation details of SGPlan4, which include the resolution of violated global constraints, techniques for handling producible resources, landmark analysis, path finding and optimization, search-space reduction, and modifications of Metric-FF when used as a basic planner in SGPlan4. Last, we show results on the sensitivity of each of these techniques in quality-time trade-offs and experimentally demonstrate that SGPlan4 is effective for solving the IPC3 and IPC4 benchmarks.
8613363
Mining Frequent Itemsets for Protein Kinase Regulation
Protein kinases, a family of enzymes, have been viewed as an important signaling intermediary by living organisms for regulating critical biological processes such as memory, hormone response and cell growth. The unbalanced kinases are known to cause cancer and other diseases. With the increasing efforts to collect, store and disseminate information about the entire kinase family, it not only leads to valuable data set to understand cell regulation but also poses a big challenge to extract valuable knowledge about metabolic pathway from the data. Data mining techniques that have been widely used to find frequent patterns in large datasets can be extended and adapted to kinase data as well. This paper proposes a framework for mining frequent itemsets from the collected kinase dataset. An experiment using AMPK regulation data demonstrates that our approaches are useful and efficient in analyzing kinase regulation data.
265743
SOA Collaboration Modeling, Analysis, and Simulation in PSML-C
This paper extends the ebXML Web services development framework to introduce a new collaboration framework, which is based on the collaboration specification language PSML-C (Process Specification and Modeling Language for Collaboration), CCSOA (Consumer-Centric Service-Oriented Architecture), and DDSOS (Dynamic Distributed Service-Oriented Simulation) framework. Since collaborations are inevitable and play a critical role in SOA, an effective framework will greatly reduce the effort for rapid and adaptive service composition, simulation, evaluation, and collaboration. The PSML-C collaboration framework provides a service-oriented infrastructure for process collaboration specification, modeling, design, code generation, simulation, deployment, execution, and management. This paper presents the concepts, architecture, enabling techniques, and illustrative examples that demonstrate the concepts and the techniques
5682504
An Efficient XPath Query Processor for XML Streams
Streaming XPath evaluation algorithms must record a potentially exponential number of pattern matches when both predicates and descendant axes are present in queries, and the XML data is recursive. In this paper, we use a compact data structure to encode these pattern matches rather than storing them explicitly. We then propose a polynomial time streaming algorithm to evaluate XPath queries by probing the data structure in a lazy fashion. Extensive experiments show that our approach not only has a good theoretical complexity bound but is also efficient in practice.
6445970
Integrative Security Management for Web-Based Enterprise Applications
In enterprise environment, security becomes increasingly important and costly. Enterprises are struggling to protect the increasing amount of disparate resources. Simple patchwork of security controls no longer suffices. Enterprises require a comprehensive solution that provides centralized security management, from authentication, to authorization and to auditing. To this end, we present a design and implementation of an integrative security management solution for Web-based enterprise applications, WebDaemon. It provides Single Sign-On to multiple Web applications. It also provides restricted access to Web-based content, portals, and Web applications based on Role-Based Access Control (RBAC) policies. The WebDaemon can help enterprises secure all Web resources with consistency of policy management and reduced administrative costs.
10148394
Generating C Code from LOGS Specifications
This paper introduces a tool that automatically translates a concrete form of specifications into C code linked with BSPlib. The translation tool is rigorously developed with important safety properties proved. A Logs specification for Bulk-Synchronous Parallelism is a relation of an initial state, a final state and some intermediate states. Nondeterminism and parallelism correspond to disjunction and conjunction respectively. Various advanced specification commands can be derived from the basic ones. The translator checks syntax, freedom of communication interference, type consistency and communication dependencies before generating the target code. Static analysis (including both static checkings and translation) is presented in abstract interpretation. It is shown that a few laws are complete for transforming any specification into a normal form. These laws are satisfied by the abstract functions. We demonstrate the actual effects of the abstract functions by applying them on the normal form. The approach has been implemented using an object-oriented language.