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Life cycle assessment is an environmental method which estimates either a process or a building material within the cradle-to-grave cycle. Presently, it is one of a few tools that include all factors which may influence the environment. The authors used this tool to prove effects connected with potential efficient energy levels and a reduction in CO2 emissions within a building’s life cycle. For the purpose of our analyses, several types of single-family building were chosen and they were subjected to analysis in the fixed location of Warsaw. The research scope included a numerical analysis of the buildings concerning the level of embodied energies and the emission of greenhouse gases. The performed analysis proved that, within a 50-year cycle, the difference between the embodied energy from the best and worst building choices can amount to 14.87%, whereas a reduction in embodied carbon emissions can reach 20.65%. Each change in the building’s form and the type of building materials used, regardless of the usable area, influence the environmental impact. Therefore, this paper concludes that LCA, as a management tool, should be used cyclically as part of each phase of the design process. A multi-criteria method for selecting architectural solutions was proposed which considered minimum cumulative primary energy, minimum cumulative carbon emission and minimum cost of constructing a building.

One of the central elements in systems biology is the interaction between mathematical modeling and measured quantities. Typically, biological phenomena are represented as dynamical systems, and they are further analyzed and comprehended by identifying model parameters using experimental data. However, all model parameters cannot be found by gradient-based optimization methods by fitting the model to the experimental data due to the non-differentiable character of the problem. Here, we present POPI4SB, a Python-based framework for population-based parameter identification of dynamic models in systems biology. The code is built on top of PySCeS that provides an engine to run dynamic simulations. The idea behind the methodology is to provide a set of derivative-free optimization methods that utilize a population of candidate solutions to find a better solution iteratively. Additionally, we propose two surrogate-assisted population-based methods, namely, a combination of a k-nearest-neighbor regressor with the Reversible Differential Evolution and the Evolution of Distribution Algorithm, that speeds up convergence. We present the optimization framework on the example of the well-studied glycolytic pathway in Saccharomyces cerevisiae.

© 2020 The Authors. Validation, verification, and uncertainty quantification (VVUQ) of simulation workflows are essential for building trust in simulation results, and their increased use in decision‐making processes. The EasyVVUQ Python library is designed to facilitate implementation of advanced VVUQ techniques in new or existing workflows, with a particular focus on high‐performance computing, middleware agnosticism, and multiscale modeling. Here, the application of EasyVVUQ to five very diverse application areas is demonstrated: materials properties, ocean circulation modeling, fusion reactors, forced human migration, and urban air quality prediction. Horizon 2020 Framework Programme. Grant Number: 800925; Engineering and Physical Sciences Research Council

One of the most critical application areas for many operational High-Performance Computing systems worldwide is a numerical weather prediction. Such complex predictions and corresponding computing models have to solve a large number of Partial Differential Equations using stencil computations on structured grids within tight production schedules. A stencil kernel within simulations is often the most demanding computing part and naturally may impact the energy consumption of the whole HPC system. In this paper, we introduce new functional extensions developed for DCworms and GSSIM simulators to predict the energy efficiency of extreme-scale stencil applications on heterogeneous computing resources, in particular consisting of a large number of many-core and GPUs. New energy-efficiency metrics for modeling of heterogeneous computing resources have been successfully added to the simulators thanks to their pluggable and extensible architectures. Our recent improvements related to application-specific performance models in simulators help users to take into account many relevant application parameters, in particular, those related to detailed energy consumption on heterogeneous HPC resources. We show in this paper how to extract stencil application-specific parameters based on real experiments. Moreover, we demonstrate how those parameters can be applied for modeling and simulation experiments to evaluate the overall performance and energy consumption of stencil computations on manycore CPUs and GPUs. Finally, we discuss new DCworms simulator capabilities and demonstrate added-values of performance analysis tools.

In many distributed computing systems, aspects related to security are getting more and more relevant. Security is ubiquitous and could not be treated as a separated problem or a challenge. In our opinion it should be considered in the context of resource management in distributed computing environments like Grids and Clouds, e.g. scheduled computations can be much delayed because of cyber-attacks, inefficient infrastructure or users valuable and sensitive data can be stolen even in the process of correct computation. To prevent such cases there is a need to introduce new evaluation metrics for resource management that will represent the level of security of computing resources and more broadly distributed computing infrastructures. In our approach, we have introduced a new metric called reputation, which simply determines the level of reliability of computing resources from the security perspective and could be taken into account during scheduling procedures. The new reputation metric is based on various relevant parameters regarding cyber-attacks (also energy attacks), administrative activities such as security updates, bug fixes and security patches. Moreover, we have conducted various computational experiments within the Grid Scheduling Simulator environment (GSSIM) inspired by real application scenarios. Finally, our experimental studies of new resource management approaches taking into account critical security aspects are also discussed in this paper.

Differential evolution (DE) is a well-known type of evolutionary algorithms (EA). Similarly to other EA variants it can suffer from small populations and loose diversity too quickly. This paper presents a new approach to mitigate this issue: We propose to generate new candidate solutions by utilizing reversible linear transformation applied to a triplet of solutions from the population. In other words, the population is enlarged by using newly generated individuals without evaluating their fitness. We assess our methods on three problems: (i) benchmark function optimization, (ii) discovering parameter values of the gene repressilator system, (iii) learning neural networks. The empirical results indicate that the proposed approach outperforms vanilla DE and a version of DE with applying differential mutation three times on all testbeds., Code: https://github.com/jmtomczak

In this paper, discrete-continuous project scheduling problems with preemptable activities are considered. In these problems, activities of a project simultaneously require discrete and continuous resources for their execution. The activities are preemptable, and the processing rate of each activity is a continuous, increasing function of the amount of a single continuous resource allotted to the activity at a time. The problem is to find a precedence- and discrete resource-feasible schedule and, simultaneously, continuous resource allocation that would minimize the project duration. Convex and concave processing rate functions are considered separately. We show that for convex functions the problem is simple, whereas for concave functions a special methodology has to be developed. We discuss the methodology for three cases of the problem: no discrete resource constraints, one discrete resource being a set of parallel, identical machines, and an arbitrary number of discrete resources. In each case we analyze separately independent and precedence-related activities. Some conclusions and directions for future research are given.

Consider scheduling tasks on dedicated processors or machines. We assume that tasks belong to a set of n jobs, each of which is characterized by the same machine sequence.

In scheduling theory the basic model assumes that all machines are continuously available for processing throughout the planning horizon.

The previous chapters focused on various scheduling models, such as single or parallel processors (Chapters 4, 5) and shop systems (Chapters 8, 9, 10), and presented results for different performance measures.

The formulation of an open shop scheduling problem is the same as for the flow shop problem except that the order of processing tasks comprising one job may be arbitrary.

Logistic and transportation related problems are crucial for various human activities, since moving people, items

Constraint propagation is an elementary method for reducing the search space of combinatorial search and optimization problems which has become more and more important in the last decades.

In Chapters 4 and 5 we analyzed scheduling problems in which the task performance is subject to temporal restrictions such as release times or deadlines.

In previous chapters we have always assumed that the processing times of tasks are fixed and described by numbers.

We consider a problem of scheduling independent preemptable jobs on parallel identical machines to minimize a makespan. The processing rate of a job depends on a temporal allocation of limited power. Moreover, we assume that energy consumption is also constrained. Thus power/energy is treated as a doubly-constrained resource. In consequence the problem is to find a sequence of jobs on machines and simultaneously to determine an allocation of power to jobs that lead to a feasible schedule of minimal length. A complex non-linear mathematical programming problem has to be solved in a general case. In this paper we propose a solution procedure that utilizes an observation that usually only one limit for doubly-constrained resource is active in an optimal schedule.

This chapter describes the concept of an expert system supporting improvements in a building's energy efficiency. An expert system is a computer program or group of programs that facilitates using knowledge and decision making. The main elements of an expert system are the knowledgebase and a conclusion system. The knowledgebase collects information about a particular area, which was beforehand written in using particular rules. The conclusion system uses the knowledgebase and user input facts to generate conclusions or prove the user's hypothesis. The proposed expert system contains information on building technology, modernization and installation activities, and the values for financial, environmental, and technical indicators characterising these technologies. The user of an expert system defines the problem to be solved using questions. Using the knowledgebase, the system will present the optimal solution or information that the technologies in the existing knowledgebase will be applicable in the case defined by the user.

Heterogeneous many-core computing resources are increasingly popular among users due to their improved performance over homogeneous systems. Many developers have realized that heterogeneous systems, e.g. a combination of a shared memory multi-core CPU machine with massively parallel Graphics Processing Units (GPUs), can provide significant performance opportunities to a wide range of applications. However, the best overall performance can only be achieved if application tasks are efficiently assigned to different types of processor units in time taking into account their specific resource requirements. Additionally, one should note that available heterogeneous resources have been designed as general purpose units, however, with many built-in features accelerating specific application operations. In other words, the same algorithm or application functionality can be implemented as a different task for CPU or GPU. Nevertheless, from the perspective of various evaluation criteria, e.g. the total execution time or energy consumption, we may observe completely different results. Therefore, as tasks can be scheduled and managed in many alternative ways on both many-core CPUs or GPUs and consequently have a huge impact on the overall computing resources performance, there are needs for new and improved resource management techniques. In this paper we discuss results achieved during experimental performance studies of selected task scheduling methods in heterogeneous computing systems. Additionally, we present a new architecture for resource allocation and task scheduling library which provides a generic application programming interface at the operating system level for improving scheduling polices taking into account a diversity of tasks and heterogeneous computing resources characteristics.

There are two main ideas in this paper: (a) regional-sector strategy could be created by a ‘bottom-up’ planning process and (b) the foresight methodology (and especially the mix of its methods) are the support tools for the regulation process on the regional level. We base our work on previous experiences and on the results of the research project named ‘Energy Development Strategy for Lower Silesia by Using Foresight Methods’ and carried out by our team from Wroclaw University of Technology (Poland). First of all, we present the idea of regulation in economies and the ‘bottom-up’ approach in programming regional development in the energy sector. The next part of the article concerns the key issues of foresight methodology and the range of its use. The results of our project are presented in the last part of this paper. The main idea is to show how foresight methods and main experts' methods, e.g. the Delphi method, can successfully support a ‘bottom up’ approach.

The problem of scheduling n tasks in a multiprocessor system with m processors to minimize the makespan is studied. Tasks are malleable, which means that a task can be executed by several processors at a time, its processing speed depends on the number of allocated processors, and a set of processors allocated to the same task can change over time. The processing speed of a task is a strictly increasing function of the number of processors allocated to this task. The earlier studies considered the case n ≤ m. This paper presents results for arbitrary n and m including characterizations of a feasible domain and an optimal solution, polynomial time algorithms for strictly increasing convex and concave processing speed functions, and a combinatorial exponential algorithm for arbitrary strictly increasing functions.

The article presents calculations and power flow of a real virtual power plant (VPP), containing a fragment of low and medium voltage distribution network. The VPP contains a hydropower plant (HPP), a photovoltaic system (PV) and energy storage system (ESS). The purpose of this article is to summarize the requirements for connection of generating units to the grid. Paper discusses the impact of the requirements on the maximum installed capacity of distributed energy resource (DER) systems and on the parameters of the energy storage unit. Firstly, a comprehensive review of VPP definitions, aims, as well as the characteristics of the investigated case study of the VPP project is presented. Then, requirements related to the regulation, protection and integration of DER and ESS with power systems are discussed. Finally, investigations related to influence of DER and ESS on power network condition are presented. One of the outcomes of the paper is the method of identifying the maximum power capacity of DER and ESS in accordance with technical network requirements. The applied method uses analytic calculations, as well as simulations using Matlab environment, combined with real measurement data. The obtained results allow the influence of the operating conditions of particular DER and ESS on power flow and voltage condition to be identified, the maximum power capacity of ESS intended for the planed VPP to be determined, as well as the influence of power control strategies implemented in a PV power plant on resources available for the planning and control of a VPP to be specified. Technical limitations of the DER and ESS are used as input conditions for the economic simulations presented in the accompanying paper, which is focused on investigations of economic efficiency.

In the recent years, energy-efficiency of computing infrastructures has gained a great attention. For this reason, proper estimation and evaluation of energy that is required to execute data center workloads became an important research problem. In this paper we present a Data Center Workload and Resource Management Simulator (DCworms) which enables modeling and simulation of computing infrastructures to estimate their performance, energy consumption, and energy-efficiency metrics for diverse workloads and management policies. We discuss methods of power usage modeling available in the simulator. To this end, we compare results of simulations to measurements of real servers. To demonstrate DCworms capabilities we evaluate impact of several resource management policies on overall energy-efficiency of specific workloads executed on heterogeneous resources.

Due to high energy costs, fine-grained power consumption accounting and capability of making users of High Performance Computing (HPC) clusters aware of the cost of their computation is becoming more and more important. Hardware power measurement solutions can be very expensive, hence the appeal of software-based estimation methods. In this paper we present a practical approach to power consumption estimation of both individual application executions and whole computing nodes. We compare it to existing state-of-the-art solutions, provide accuracy figures, and discuss possible deployment scenarios. Highlights? We explore existing methods for measuring HPC machine power use. ? We propose general method for software estimation of power consumption. ? We discuss both application and machine-level power estimation. ? We provide practical application scenarios for both methods.

This paper deals with a power-aware scheduling of preemptable independent jobs on identical parallel processors where ready time for each job is given and its completion time has to meet a given deadline. Jobs are described by (different) continuous, strictly concave functions relating their processing speeds at a time to the amount of power allotted at the moment. Power is a continuous, doubly constrained resource, i.e. both: its availability at each time instant and consumption over scheduling horizon are constrained. A methodology based on properties of minimum-length schedules is utilized to determine the existence of a feasible schedule for given amounts of energy and power. The question about minimum levels of power and energy ensuring the existence of a feasible schedule for a given set of jobs is also studied.

The aim of the article is to present a critical comparison of different business models of Virtual Power Plant and pointing out both the common and the unique features for each model. Therefore, the American, German, Finnish, Danish and Australian VPP’s business models are described in the article. The VPP is an IT structure which integrates different types of distributed energy sources, flexible consumers and energy storage with each other and with other market segments in real time through a smart grid. The VPP gives positive effects on electricity grid like ensuring energy security, improving grid stability and reliability, optimization of energy resources use, lowering the load - demand response, regulation of frequency, using operational reserves, management of peak demand. The business model is perceived as a method of increasing and exploitation of company’s resources for preparing new products or services for customers in order to obtain added value (expanding the competition advantage or increasing profitability). A potential VPP’s business model in Polish conditions was proposed in case of two different types of customers.

A problem of allocating resources of a grid to workflow applications is considered. The problem consists, generally, in allocating distributed grid resources to tasks of a workflow in such a way that the resource demands of each task are satisfied. Grid resources are divided into computational resources and network resources. Computational tasks and transmission tasks of a workflow are distinguished. We present a model of the problem, and an algorithm for finding feasible resource allocations. A numerical example is included, showing the importance of the resource allocation phase on a grid. Some conclusions and directions for future research are given.

In this paper, we propose a new method for multi-user, multicriteria job scheduling in Grid environments with QoS guarantees concerning time and cost. The main goal of our method is to find a fair schedule of jobs that were submitted by multiple users. To obtain a schedule which is satisfactory for each user we aim at finding a set of advance reservations (ARs) for multiple users at once. This goal is achieved by adequate use of the Ordered Weighted Averaging (OWA) operator and Multiobjective Evolutionary Algorithm (MOEA) with carefully designed problem representation and operators. We also propose a data structure and algorithm used to manage and search for resource availability time slots. Efficiency and usefulness of our approach was demonstrated by computational experiments conducted within a simulation environment.

On job models in power management problemsIn the paper a model of job processing is presented where processing speed is related to the amount of power allotted to this job at a moment. Basic time-optimal results are showed assuming that energy is treated as a scarce doubly-constrained resource in a computer system. The proposed approach is applicable to the practical power management problems appearing in modern portable device systems.

In this paper we address a multicriteria scheduling problem for computational Grid systems. We focus on the two-level hierarchical Grid scheduling problem, in which at the first level (the Grid level) a Grid broker makes scheduling decisions and allocates jobs to Grid nodes. Jobs are then sent to the Grid nodes, where local schedulers generate local schedules for each node accordingly. A general approach is presented taking into account preferences of all the stakeholders of Grid scheduling (end-users, Grid administrators, and local resource providers) and assuming a lack of knowledge about job time characteristics. A single-stakeholder, single-criterion version of the approach has been compared experimentally with the existing approaches.

PurposeThe paper aims to present the concept of the functionality of metadata harvesting for regional digital libraries, based on the OAI‐PMH protocol. This functionality is a part of regional digital libraries platform created in Poland. The platform was required to reach one of main objectives of the Polish PIONIER Programme – to enrich the content‐based services in the Polish NREN.Design/methodology/approachIn order to create the regional digital libraries platform with metadata harvesting feature, digital library low‐level services provided by the dLibra Digital Library Framework in a service‐oriented architecture (SOA) are deployed. The approach for defining the set of services started with splitting the whole set of advanced digital library features into coherent functional groups, which covered functionality related to digital content, metadata, searching, etc. Then each functional group implicated the creation of a respective digital library service. Additionally, a couple of supporting services like “system” or “event services” were defined.FindingsThe exploration of metadata and information about libraries' structure enables the creation of higher‐level, content‐based services like virtual collections or metadata searching, which are described in the paper. The approach for building distributed regional digital libraries in the National Research and Education Network is suitable for larger scale systems, like international digital libraries. This issue is very important for research networking, especially in the context of European Commission's announcement promoting digital access to Europe's heritage through the European Digital Library.Research limitations/implicationsThe implementation of the communication protocol between different instances of digital libraries is the basis for the development of content‐based services. It presents examples of such services that are enabled through the PIONIER platform for distributed regional digital libraries, and that are provided for research and education users. The next step that will allow for the creation of even more sophisticated services, will offer the possibility to search through content gathered in PIONIER digital libraries. This will be achieved by combining the OAI‐PMH protocol together with the MPEG‐21 DIDL standard for the exchange of the digital content and content‐related metadata. Another group of complementary services also covers information services provided by grid environments.Practical implicationsThe installation of regional digital libraries in the PIONIER network is currently providing access to more than 15,000 of digital publications. This paper presents a working implementation of the communication between digital libraries in the sense of the exploration of metadata and information about the library structure. This service is seen by us as one of the crucial mechanisms of the information infrastructure, which provides access to scientific and cultural content as well as common middleware services, which should be both distributed and platform‐independent.Originality/valueThe paper is providing the case study for those who are building the large‐scale distributed digital library systems. The definition of services based on metadata harvesting provides an example of core digital library services, which are transforming digital libraries into digital infrastructure for social sciences.

The problem of optimal scheduling n tasks in a parallel processor system is studied. The tasks are malleable, i.e., a task may be executed by several processors simultaneously and the processing speed of a task is a nonlinear function of the number of processors allocated to it. The total number of processors is m and it is an upper bound on the number of processors that can be used by all the tasks simultaneously. It is assumed that the number of processors is sufficient to process all the tasks simultaneously, i.e. n≤m. The objective is to find a task schedule and a processor allocation such that the overall task completion time, i.e. the makespan, is minimized. The problem is motivated by real-life applications of parallel computer systems in scientific computing of highly parallelizable tasks. An O(n) algorithm is presented to solve this problem when all the processing speed functions are convex. If these functions are all concave and the number of tasks is a constant, the problem can be solved in polynomial time. A relaxed problem, in which the number of processors allocated to each task is not required to be integer, can be solved in O(nmax {m,nlog 2 m}) time. It is proved that the minimum makespan values for the original and relaxed problems coincide. For n=2 or n=3, an optimal solution for the relaxed problem can be converted into an optimal solution for the original problem in a constant time.

We consider the problem of scheduling preemptable, dependent tasks on parallel, identical machines to minimize the makespan. The computational complexity of this problem remains open if the number of machines is fixed and larger than 2. The aim of this paper is to compare two heuristic algorithms on a basis of a computational experiment. The solutions generated by the heuristics are compared with optimal solutions obtained by a branch-and-bound algorithm. Computational results show that the heuristic based on node ordering finds optimal schedules for 99.9% of instances with the maximum relative deviation from optimum of 4.8%.

A problem of scheduling jobs on parallel, identical machines under an additional continuous resource to minimize the makespan is considered. Jobs are non-preemtable and independent and all are available at the start of the process. The total amount of the continuous resource available at a time is limited and the resource is a renewable one. Each job simultaneously requires for its processing a machine and an amount (unknown in advance) of the continuous resource. The processing rate of a job depends on the amount of the resource allotted to this job at a time. The problem is to find a sequence of jobs on machines and, simultaneously, a continuous resource allocation which minimize the makespan. A heuristic approach to allocating the continuous resource is proposed. A tabu search algorithm to solve the considered problem is presented and the results for the algorithms with exact and heuristic procedures for allocating the continuous resource are compared on the basis of some computational experiments. Copyright © 2002 John Wiley & Sons, Ltd.

In this paper the resource-constrained project scheduling problem with multiple execution modes for each activity and the makespan as the minimization criterion is considered. A simulated annealing approach to solve this problem is presented. The feasible solution representation is based on a precedence feasible list of activities and a mode assignment. A comprehensive computational experiment is described, performed on a set of standard test problems constructed by the ProGen project generator. The results are analyzed and discussed and some final remarks are included.

In this paper a discrete-continuous project scheduling problem is considered. In this problem activities simultaneously require discrete and continuous resources. The processing rate of each activity depends on the amount of the continuous resource allotted to this activity at a time. All the resources are renewable ones. The activities are nonpreemtable and the objective is to minimize the makespan. Discretization of this problem leading to a classical (i.e. discrete) project scheduling problem in the multi-mode version is presented. A simulated annealing (SA) approach to solving this problem is described and tested computationally in two versions: with and without finding an optimal continuous resource allocation for the final schedule. In the former case a nonlinear solver is used for solving a corresponding convex programming problem. The results are compared with the results obtained using SA for the discrete-continuous project scheduling problem where the nonlinear solver is used for exact solving the continuous part in each iteration. The results of a computational experiment are analyzed and some conclusions are included.

A class of discrete-continuous scheduling problems is considered when each nonpreemptable, independent job simultaneously requires for its processing a machine from a set of m identical, parallel machines and an amount, arbitrary within interval [0,1], of a continuously divisible, renewable resource available in amount 1. Job processing rates are described by power functions of the resource amount allotted at a time. Some properties of optimal schedules are proved which allow to find such schedules analytically in some cases and to construct efficient heuristics in the general case. Results of a computational experiment are described.

The modern computer and networking infrastructure for science in Poland consists of 20 MANs and 5 high power computer centres. It requires an appropriate country backbone network. POL34 is the ATM Polish countrywide academic network, based on the SDH 34 Mbps trunks. The goal of the POL34 initiative is to give new opportunities for development of science-oriented applications: interconnecting library servers, an access to databases and countrywide licence servers, and also creating a new class of services offered to science based on multimedia and metacomputing applications. This activity is in accordance with the concept of Internet2, and in fact can be considered as its Polish version. The paper describes the current state of POL34 development, its activity within the Polish academic and scientific community and plans for the future.

Discrete–continuous problems of scheduling nonpreemptable jobs on parallel machines are considered. The problems arise e.g. when jobs are assigned to multiple parallel processors driven by a common electric, hydraulic or pneumatic power source. Existing models have assumed job processing rates as a function of the number of jobs currently being processed, or equivalently the number of machines currently in operation. In this paper a more general model is proposed in which processing rates of a job assigned to a machine depend on the amount of a continuous, i.e. continuously divisible resource (e.g. power) allotted to this job at a time. Thus the problem consists of two interrelated subproblems: (i) to sequence jobs on machines, and (ii) to allocate the continuous resource among jobs already sequenced. We provide a comprehensive analysis of the problem. This includes properties of optimal schedules, efficiently (in particular analytically) solvable cases, formulations of the possibly simplest mathematical programming problems for finding optimal schedules in the general case, heuristics and the worst-case analysis. Although our objective function in this paper is to minimize makespan of a set of independent jobs, the presented methodology can be applied to other criteria, precedence-related jobs, and many resource types (apart from, or instead of machines).

In this paper we propose a methodology underlying a development of system-wide energy consumption models for servers, which is based on the analysis of performance counters. It enables to estimate the power usage of a machine under any load at runtime. By clustering applications we extract groups of programs having similar characteristics. This allows us to create more specialized and accurate power usage models. By using decision trees it is possible to automatically select an appropriate model to current system load. Training and test sets of programs were used to test the estimates. The presented models are accurate within an error of 4% as verified on servers from different vendors, including the latest pre-production one.

In the paper authors present the general idea of software correlator in e-VLBI system. The e-VLBI idea is undoubtedly the future of radio astronomy which allows accelerate both measurement and post-processing procedures. Software correlation idea is a new approach to the space observation base on very long baseline interferometry method. It significantly reduces processing time of obtained data from 6 months up to few minutes so the scientists can almost immediately familiarize with results of their tests. That is why finding (sub)optimal solutions for designing and working of software correlator is essential for radio astronomy society. The paper touches many important and up-to-date aspects from e-VLBI domain including preparation phase to the correlation process. Moreover, experimental results are presented concerning different aspects of data availability which proof that quasi real time software correlation process is possible.

A rapid development of semantic technologies and a growing awareness of a potential of semantic data has a great influence and effects on an increasing number of semantic data repositories. However, the abundance of these repositories is hidden behind sophisticated data schemas. At the same time, the lack of user-friendly tools for presenting data makes this collected knowledge unavailable for average users. In this paper we present our concept of creating a convenient semantic environment for ordinary users as well as maintaining rich functionality available for professionals. Our adaptation of a classic three-layer architecture for the semantic data sharing and presentation purpose reveals how the great usability and accessibility of data can be achieved. We also pay special attention to the standards and cooperation issues, which makes our system available for other tools implementing semantic data sharing concepts and keeps it open for Linked Open Data environment integration.

One of the tasks undertaken in PSNC in the frame of the SYNAT project is the design of architecture for the scientific information system allowing to integrate heterogeneous distributed services necessary to build knowledge base and innovative applications based on it. This paper contains overall description of the designed architecture with the analysis of its most important technical aspects, features and possible weak points. It also presents initial results from the test deployment of the first prototype of several architecture components, including initial aggregation and processing of several millions of metadata records from several tenths of network services.

This book will focus on new Remote Instrumentation aspects related to middleware architecture, high-speed networking, wireless Grid for acquisition devices and sensor networks, QoS provisioning for real-time control, measurement instrumentation and methodology. Moreover, it will provide knowledge about the automation of mechanisms oriented to accompanying processes that are usually performed by a human. Another important point of this book is focusing on the future trends concerning Remote Instrumentation systems development and actions related to standardization of remote instrumentation mechanisms.

This paper describes the transformation of the metadata schema used by the Polish Digital Libraries Federation to the CIDOC CRM model implemented in OWL as Erlangen CRM. The need to transform the data from a flat schema to a full-fledged ontology arose during preliminary works in the Polish research project SYNAT. The Digital Libraries Federation site offers aggregated metadata of more than 600,000 publications that constitute the first portion of data introduced into the Integrated Knowledge System - one of the services developed in the SYNAT project. To be able to perform the desired functions, IKS needs heavily linked data that can be searched semantically. The issue is not only one of mapping one schema element to another, as the conceptualization of CIDOC is significantly different from that of the DLF schema. In the paper we identify a number of problems that are common to all such transformations and propose solutions. Finally, we present statistics concerning the mapping process and the resulting knowledge base.

Platon TV is a country-wide platform that supports HD content production, processing and delivery for research and educational purposes. The scope of operation and a wide area of scientific subjects covered, in combination with the technological requirements of high resolution, high quality content makes design of such a platform a challenging task. In this paper we present how the intended functionality is implemented by Platon TV for various stages of content lifecycle. We describe the platform architecture and mechanisms that ensure required security and reliability.

We present a knowledge—based multiobjective project scheduling system which handles a class of nonpreemptive scheduling problems characterized by (i) renewable, nonrenewable and doubly—constrained resources of many types, (ii) multiple performing modes of tasks and (iii) multiple project performance measures. Knowledge concerning different aspects of technology, resources and schedules is stored in several knowledge sources which are separated and communicate through a blackboard. The knowledge is represented by production rules and frames. Rules operate on objects (represented by frames) which instances are stored in the blackboard.