Abstract processes of place/transition systems

A well-known problem in Petri net theory is to formalise an appropriate causality-based concept of process or run for place/transition systems. The so-called individual token interpretation, where tokens are distinguished according to their causal history, giving rise to the processes of Goltz and Reisig, is often considered too detailed. The problem of defining a fully satisfying more abstract concept of process for general place/transition systems has so-far not been solved. In this paper, we recall the proposal of defining an abstract notion of process, here called BD-process, in terms of equivalence classes of Goltz-Reisig processes, using an equivalence proposed by Best and Devillers. It yields a fully satisfying solution for at least all one-safe nets. However, for certain nets which intuitively have different conflicting behaviours, it yields only one maximal abstract process. Here we identify a class of place/transition systems, called structural conflict nets, where conflict and concurrency due to token multiplicity are clearly separated. We show that, in the case of structural conflict nets, the equivalence proposed by Best and Devillers yields a unique maximal abstract process only for conflict-free nets. Thereby BD-processes constitute a simple and fully satisfying solution in the class of structural conflict nets.     

On the robustness of Type-1 and Interval Type-2 fuzzy logic systems in modeling

Research on the robustness of fuzzy logic systems (FLSs), an imperative factor in the design process, is very limited in the literature. Specifically, when a system is subjected to small deviations of the sampling points (operating points), it is of great interest to find the maximum tolerance of the system, which we refer to as the system’s robustness. In this paper, we present a methodology for the robustness analysis of interval type-2 FLSs (IT2 FLSs) that also holds for T1 FLSs, hence, making it more general. A procedure for the design of robust IT2 FLSs with a guaranteed performance better than or equal to their T1 counterparts is then proposed. Several examples are performed to demonstrate the effectiveness of the proposed methodologies. It was concluded that both T1 and IT2 FLSs can be designed to achieve robust behavior in various applications, and preference one or the other, in general, is application-dependant. IT2 FLSs, having a more flexible structure than T1 FLSs, exhibited relatively small approximation errors in the several examples investigated. The methodologies presented in this paper lay the foundation for the design of FLSs with robust properties that will be very useful in many practical modeling and control applications.     

A fast and robust bulk-loading algorithm for indexing very large digital elevation datasets: I. Algorithm

Digital elevation models (DEMs) constitute a valuable source of data for a number of geoscience-related applications. The Shuttle Radar Topography Mission (SRTM) collected and made available to the public the world's largest DEM (composed of billions of points) until that date. The SRTM DEM is stored on the NASA repository as a well-organized collection of flat files. The retrieval of this stored topographic information about a region of interest involves one selection of a proper list of files, their downloading, data filtering in the desired region, and their processing according to user needs. With the aim to provide an easier and faster access to this data by improving its further analysis and processing, we have indexed the SRTM DEM by means of a spatial indexing based on the kd-tree data structure, called the Q-tree. This paper is the first in a two-part series that describes the method followed to build an index on such huge amounts of data, minimizing the number of insert operations. We demonstrate that our method can build a very efficient space-partitioning index, with good performance in both point and range queries on the spatial data. To the best of our knowledge, this is the only successful spatial indexing proposal in the literature that deals with such a huge volume of data.     

Analytical derivation of traffic patterns in cache-coherent shared-memory systems

This paper presents an analytical method to derive the worst-case traffic pattern caused by a task graph mapped to a cache-coherent shared-memory system. Our analysis allows designers to rapidly evaluate the impact of different mappings of tasks to IP cores on the traffic pattern. The accuracy varies with the application’s data sharing pattern, and is around 65% in the average case and 1% in the best case when considering the traffic pattern as a whole. For individual connections, our method produces tight worst-case bandwidths.     

Priority scheduling of requests to web portals

Web portals work as a point of access to a large volume of information on the web. This paper focuses on the performance of Web portals in an E-commerce environment which involves the processing of a large number of users’ requests. It proposes a class-based priority scheme which classifies users’ requests into high and low priorities. In E-commerce, some requests (e.g. buy) are generally considered more important than others (e.g. search or browse). We contend that the requests received from a Web portal should generally get higher priority as such requests are more likely to lead to purchases. We believe that assigning such priorities at multiple service levels can improve the performance of Web portals’ requests of higher priority. The proposed scheme is formally specified and implemented, and performance results are obtained and compared to a server that does not prioritise requests. The results show significant performance improvements in the processing of high priority requests.     

Adaptable Decentralized Service Oriented Architecture

In the Service Oriented Architecture (SOA), BPEL specified business processes are executed by non-scalable centralized orchestration engines. In order to address the scalability issue, decentralized orchestration engines are applied, which decentralize BPEL processes into static fragments at design time without considering runtime requirements. The fragments are then encapsulated into runtime components such as agents. There are a variety of attitudes towards workflow decentralization; however, only a few of them produce adaptable fragments with runtime environment. In this paper, producing runtime adaptable fragments is presented in two aspects. The first one is frequent-path adaptability that is equal to finding closely interrelated activities and encapsulating them in the same fragment to omit the communication cost of the activities. Another aspect is proportional-fragment adaptability, which is analogous to the proportionality of produced fragments with number of workflow engine machines. It extenuates the internal communication among the fragments on the same machine. An ever-changing runtime environment along with the mentioned adaptability aspects may result in producing a variety of process versions at runtime. Thus, an Adaptable and Decentralized Workflow Execution Framework (ADWEF) is introduced that proposes an abstraction of adaptable decentralization in the SOA orchestration layer. Furthermore, ADWEF architectures Type-1 and Type-2 are presented to support the execution of fragments created by two decentralization methods, which produce customized fragments known as Hierarchical Process Decentralization (HPD) and Hierarchical Intelligent Process Decentralization (HIPD). However, mapping the current system conditions to a suitable decentralization method is considered as future work. Evaluations of the ADWEF decentralization methods substantiate both adaptability aspects and demonstrate a range of improvements in response-time, throughput, and bandwidth-usage compared to previous methods.     

Predicting the unexpected

Dagstuhl seminar no. 10102 on discrete event logistic systems recognized a network of persistent models to be a “Grand Challenge.” Such on-line model network will offer an infrastructure that facilitates the management of logistic operations. This ambition to create a network of persistent models implies a radical shift for model design activities as the objective is an infrastructure rather than application-specific solutions. In particular, model developers can no longer assume that they know what their model will be used for. It is no longer possible to design for the expected.This paper presents insights in model development and design in the absence of precise knowledge concerning a model's usage. Basically, model developers may solely rely on the presence of the real-world counterpart mirrored by their model and a general idea about the nature of the application (e.g. coordination of logistic operations). When the invariants of their real-world counterpart suffice for models to be valid, these models become reusable and integrate-able. As these models remain valid under a wide range of situations, they become multi-purpose and durable resources rather than single-purpose short-lived components or legacy, which is even worse.Moreover and more specifically, the paper describes how to build models that allow their users to generate predictions in unexpected situations and atypical conditions. Referring to previous work, the paper concisely discusses how these predictions can be generated starting from the models. This prediction-generating technology is currently being transferred into an industrial MES.     

Modeling the permeability of carbonate reservoir using type-2 fuzzy logic systems

In this work, the use of type-2 fuzzy logic systems as a novel approach for predicting permeability from well logs has been investigated and implemented. Type-2 fuzzy logic system is good in handling uncertainties, including uncertainties in measurements and data used to calibrate the parameters. In the formulation used, the value of a membership function corresponding to a particular permeability value is no longer a crisp value; rather, it is associated with a range of values that can be characterized by a function that reflects the level of uncertainty. In this way, the model will be able to adequately account for all forms of uncertainties associated with predicting permeability from well log data, where uncertainties are very high and the need for stable results are highly desirable. Comparative studies have been carried out to compare the performance of the proposed type-2 fuzzy logic system framework with those earlier used methods, using five different industrial reservoir data. Empirical results from simulation show that type-2 fuzzy logic approach outperformed others in general and particularly in the area of stability and ability to handle data in uncertain situations, which are common characteristics of well logs data. Another unique advantage of the newly proposed model is its ability to generate, in addition to the normal target forecast, prediction intervals as its by-products without extra computational cost.     

Finite-time weighted average consensus with respect to a monotonic function and its application

The consensus state is an important and fundamental quantity for consensus problems of multi-agent systems, which indicates where all the dynamical agents reach. In this paper, weighted average consensus with respect to a monotonic function, which means that the trajectories of the monotonic function along the state of each agent reach the weighted average of their initial values, is studied for a group of kinematic agents with time-varying topology. By constructing a continuous nonlinear distributed protocol, such a consensus problem can be solved in finite time even though the time-varying topology involves unconnected graphs. Then the distributed protocol is employed to compute the maximum-likelihood estimation of unknown parameters over sensor networks. Compared with the existing results, the estimate scheme proposed here may reduce the costs of data communication, storage memory, book-keeping and computational overheads.     

Fundamental connections among the stability conditions using higher-order time-derivatives of Lyapunov functions for the case of linear time-invariant systems

It has already been recognized that looking for a positive definite Lyapunov function such that a high-order linear differential inequality with respect to the Lyapunov function holds along the trajectories of a nonlinear system can be utilized to assess asymptotic stability when the standard Lyapunov approach examining only the first derivative fails. In this context, the main purpose of this paper is, on one hand, to theoretically unveil deeper connections among existing stability conditions especially for linear time-invariant (LTI) systems, and from the other hand to examine the effect of the higher-order time-derivatives approach on the stability results for uncertain polytopic LTI systems in terms of conservativeness. To this end, new linear matrix inequality (LMI) stability conditions are derived by generalizing the concept mentioned above, and through the development, relations among some existing stability conditions are revealed. Examples illustrate the improvement over the quadratic approach.