Computing and Informatics (E-Journal - Institute of Informatics, SAS, Bratislava)
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Scalability and Performance Analysis of OpenMP Codes Using the Periscope Toolkit
Get PDFIn this paper, we present two new approaches while rendering necessary extensions to Periscope to perform scalability and performance analysis on OpenMP codes. Periscope is an online-based performance analysis toolkit which consists of a user defined number of analysis agents that automatically search for the performance properties while the application is running. In order to detect the scalability and performance bottlenecks of OpenMP codes using Periscope, a few newly defined performance properties and meta properties are formalized. We manifest our implementation by evaluating NAS OpenMP benchmarks. As shown in our results, our approach identifies the code regions which do not scale well and other performance problems, e.g. load imbalance in NAS parallel benchmarks
An Architecture to Support the Design and Evaluation of Software Platforms for Partially Virtual Communities
Get PDFSeveral researchers have identified the design of collaborative systems as a particularly challenging task, because it has to consider services that are not easily identifiable by software designers. The systems that support the activities of partially virtual communities (PVC) are not an exception. Typically, designers of PVC supporting systems are able to identify services that have a visual representation on the user interface, but they usually overlook those that run in the system back-end. In an attempt to help designers to consider these two types of services, this article proposes a software architecture that can be used for both, designing new PVC supporting systems and evaluating existing ones. The architecture was used in three case studies as a design guideline during the development of PVC supporting platforms, and also as an instrument to evaluate three commercial systems. Although the obtained results are still preliminary, they indicate that the architecture is able to accomplish both roles
Data and Query Adaptation Using DaemonX
Get PDFThe most common applications of the today's IT world are information systems. The problems related to their design and implementation have sufficiently been solved. However, the true problems occur when an IS is already deployed and user requirements change. In this paper we introduce DaemonX - an evolution management framework which enables to manage evolution of complex applications efficiently and correctly. Using the idea of plug-ins, it enables to model almost any kind of a data format (currently XML, UML, ER, and BPMN). Since it preserves also mapping among modeled constructs of modeled formats via a common platform-independent model, it naturally supports propagation of changes to all related and affected parts
Optimal Caching Policy of Stochastic Updating Information in Delay Tolerant Networks
Get PDFTo increase the speed of information retrieval, one message may have multiple replicas in Delay Tolerant Networks (DTN). In this paper, we adopt a discrete time model and focus on the caching policy of stochastic updating information. In particular, the source creates new version in every time slot with certain probability. New version is usually more useful than the older one. We use a utility function to denote the availability of different versions. To constrain the number of replicas, we propose a probabilistic management policy and nodes to discard information with certain probability determined by the version of the information. Our objective is to find the best value of the probability to maximize the total utility value. Because new version is created with certain probability, nodes other than the source may not know whether the information stored in them is the latest version. Therefore, they can make decisions only according to the local state and decisions based on the local state can be seen as local-policy. We also explore the global-policy, that is, nodes understand the real state. We prove that the optimal policies in both cases conform to the threshold form. Simulations based on both synthetic and real motion traces show the accuracy of our theoretical model. Surprisingly, numerical results show that local-policy is better than the global-policy in some cases
Privacy Aware Parallel Computation of Skyline Sets Queries from Distributed Databases
Get PDFA skyline query finds objects that are not dominated by another object from a given set of objects. Skyline queries help us to filter unnecessary information efficiently and provide us clues for various decision making tasks. However, we cannot use skyline queries in privacy aware environment, since we have to hide individual's records values even though there is no ID information. Therefore, we considered skyline sets queries. The skyline set query returns skyline sets from all possible sets, each of which is composed of some objects in a database. With the growth of network infrastructure data are stored in distributed databases. In this paper, we expand the idea to compute skyline sets queries in parallel fashion from distributed databases without disclosing individual records to others. The proposed method utilizes an agent-based parallel computing framework that can efficiently compute skyline sets queries and can solve the privacy problems of skyline queries in distributed environment. The computation of skyline sets is performed simultaneously in all databases which increases parallelism and reduces the computation time
Isomorphism between Linear Codes and Arithmetic Codes for Safe Data Processing in Embedded Software Systems
Get PDFWe present a transformation rule to convert linear codes into arithmetic codes. Linear codes are usually used for error detection and correction in broadcast and storage systems. In contrast, arithmetic codes are very suitable for protection of software processing in computer systems. This paper shows how to transform linear codes protecting the data stored in a computer system into arithmetic codes safeguarding the operations built on this data. Combination of the advantages of both coding mechanisms will increase the error detection capability in safety critical applications for embedded systems by detection and correction of arbitrary hardware faults
Distributed Computation of Generalized One-Sided Concept Lattices on Sparse Data Tables
Get PDFIn this paper we present the study on the usage of distributed version of the algorithm for generalized one-sided concept lattices (GOSCL), which provides a special case for fuzzy version of data analysis approach called formal concept analysis (FCA). The methods of this type create the conceptual model of the input data based on the theory of concept lattices and were successfully applied in several domains. GOSCL is able to create one-sided concept lattices for data tables with different attribute types processed as fuzzy sets. One of the problems with the creation of FCA-based models is their computational complexity. In order to reduce the computation times, we have designed the distributed version of the algorithm for GOSCL. The algorithm is able to work well especially for data where the number of newly generated concepts is reduced, i.e., for sparse input data tables which are often used in domains like text-mining and information retrieval. Therefore, we present the experimental results on sparse data tables in order to show the applicability of the algorithm on the generated data and the selected text-mining datasets
An Empirical Study on Collective Intelligence Algorithms for Video Games Problem-Solving
Get PDFComputational intelligence (CI), such as evolutionary computation or swarm intelligence methods, is a set of bio-inspired algorithms that have been widely used to solve problems in areas like planning, scheduling or constraint satisfaction problems. Constrained satisfaction problems (CSP) have taken an important attention from the research community due to their applicability to real problems. Any CSP problem is usually modelled as a constrained graph where the edges represent a set of restrictions that must be verified by the variables (represented as nodes in the graph) which will define the solution of the problem. This paper studies the performance of two particular CI algorithms, ant colony optimization (ACO) and genetic algorithms (GA), when dealing with graph-constrained models in video games problems. As an application domain, the "Lemmings" video game has been selected, where a set of lemmings must reach the exit point of each level. In order to do that, each level is represented as a graph where the edges store the allowed movements inside the world. The goal of the algorithms is to assign the best skills in each position on a particular level, to guide the lemmings to reach the exit. The paper describes how the ACO and GA algorithms have been modelled and applied to the selected video game. Finally, a complete experimental comparison between both algorithms, based on the number of solutions found and the levels solved, is analysed to study the behaviour of those algorithms in the proposed domain
New Algorithm for Clustering Distributed Data Using k-Means
Get PDFThe internet era and high speed networks have ushered in the capabilities to have ready access to large amounts of geographically distributed data. Individuals, businesses, and governments recognize the value of this available resource to those who can transform the data into information. These databases, though valuable as individual entities, become significantly more valuable when they function as parts of a federated database and their data can be aggregated for collective mining or computations. This requires new algorithms to shift their focus from working with single databases to efficiently working with federated databases. In this paper, we propose a new decomposable version of the popular k-means clustering algorithm that works in this desired manner with a set of networked databases. We show that it is possible to perform global computation in a reasonably secure manner for either horizontally or vertically distributed databases. The computation is completed by only exchanging a few local summaries among the databases. An empirical and analytical validation of our results is also presented
Advanced Information System for Safety-Critical Processes
Get PDFThe paper deals with the design and implementation of an intelligent modular information system (IMIS) for modeling and predictive decision making supervisory control of some important critical processes in a nuclear power plant (nuclear reactor) using selected soft computing methods. The developed IMIS enables monitoring critical states, safety impact analysis and prediction of dangerous situations. It also recommends the operator possibilities how to proceed to ensure safety of operations and humans and environment. The proposed complex IMIS has been tested on real data from a nuclear power plant process primarily used as supervisory information for decision making support and management of critical processes. The core of the proposed IMIS is a general nonlinear neural network mathematical model. For prediction of selected process variables an artificial neural network of multilayer perceptron type (MLP) has been used. The effective Levenberg-Marquardt method was used to train the MLP network. Testing and verification of the neural prediction model were carried out on real operating data measurements obtained from the NPP Jaslovske Bohunice