Grid Services for Measurements on Digital Wireless Communications Systems

Digital signal processing algorithms are nowadays playing a more and more important role in most measurement processes. Also in the presence of poor digitized data, reliable and repeatable results can often be assured by complementing the adopted measurement procedure with a suitable processing stage. The realization of a collection of measurement algorithms to be shared among researchers and technicians working on similar topics should thus be advisable. Complex algorithms, however, suffer from critical drawbacks, in terms of computational burden and hardware resources requested, when applied to very long acquired records. The authors suggest hereinafter the adoption of GRID service as an innovative solution in order to provide researchers with the collection of measurement algorithms and concurrently overcome the cited drawbacks. A GRID Service is a new hardware/software approach capable of merging the higher computational performance of parallel GRID computing with key mechanisms and standards of Web Service. It would be so possible to migrate complex measurement algorithms into services available and accessible on Internet. As an application example, the authors present a GRID Service implementing a method for power measurement in digital wireless communication systems.

The aim of this thesis is to design and implement a new Grid Resource Management methodology, where non-massive resources owners would be able to share their resources and integrate human collaboration across multiple domains regardless of network technology, operative platform or administrative domain.<br/>This thesis proposes a distributed and heuristic policy-based resource management architecture for large-scale Grids. The resource management architecture proposed herein is composed of four main building blocs: services management, resource discovery and monitoring, resource scheduling and jobs allocation and activation. The Grid Services Management (GSM) and Jobs Allocation and Activation (JAA) are supported by means of a Policy-based Grid Resource Management Architecture (PbGRMA). This architecture is able to identify service needs arising from diverse sources during the deployment and management of Grid Services, such as requirements demanded by customers, applications and network conditions. Afterwards, the PbGRMA merges these requirements into deployment policies for the corresponding Grid Services. The Grid Resource Discovery and Monitoring (GRDM) is supported by the introduction of the SNMP-based Balanced Load Monitoring Agents for Resource Scheduling (SBLOMARS), in which network and computational resources are monitored by distributed agents. This allows for a flexible, heterogeneous and scalable monitoring system. The Grid Resource Scheduling (GRS) is based on the Balanced Load Multi-Constrained Resource Scheduler (BLOMERS). This heuristic scheduler represents an alternate way of solving the inherent NP-hard problem for resource scheduling in large-scale distributed networks by means of the implementation of a Genetic Algorithm.<br/>Finally, based on the outcome of both the GRDM and GRS, the PbGRMA allocates the corresponding Grid Services by means of its interfaces with Globus ToolKit Middleware and Unix-based CLI commands along of any large-scale Grid Infrastructure. <br/>The synergy obtained by these components allows Grid administrators to exploit the available resources with predetermined levels of Quality of Service (QoS), reducing computational costs and makespan in resource scheduling while ensuring that the resource load is balanced throughout the Grid. The makespan of a schedule is the time required for all jobs to be processed when no one job could be interrupted during its execution and each node can perform at most one operation at any time.<br/>This new approach has been successfully tested in a real large-scale scenario such as Grid5000. The results presented along this Thesis show that our general solution is a reliable, flexible and scalable architecture to deploy and manage Grid Services in large-scale Grid Infrastructures. Moreover, the substitution of the heuristic algorithm approach used into the Grid Resource Scheduling (GRS) phase by other non-heuristics selection algorithms could make our solution useful in smaller Grid Infrastructures.

Grid technology is widely used in recent years, it has solved the real sharing of resources, make each node of unified command and use of resources, the information grid is on the basis of computational grid, using data mining. Information fusion and search engine technology and building are advantageous for the collection and sharing of grid resources. The goal to create a build on OS and Web is based on the new generation of Internet information platform. In this platform, the distribution of the information processing is the collaboration and intelligent. Focus crawler sets according to the target subject. In the form of intelligent collection topics come from the Web page, and then adopt the method of machine learning. The information retrieval on the collected information intelligent need process and analyze. Finally, the effective retrieval way is to meet the demand of the user's information retrieval.

Grid computing is becoming a research focus in distributed and parallel systems. The idea of the grid service being a kernel of the whole grid architecture is accepted by the researchers. The grid service has the characteristics of high scalability and dynamic. By analyzing the resource management in heterogeneous environment and agent-based hierarchy model, this paper presents an agent-based distributed model on grid service advertisement and discovery. It can’t only satisfy the scalability and dynamic of grid service, but may also reduce the system overhead comparing to central management of service advertisement

Objective To verify the accuracy of the results of special visual measurement instruments for heterphoric testing.Methods In this cross-sectional study,fifty healthy students served as subjects.The degree of heterphoria was measured by a special visual measurement instrument,the Maddox rod and a synoptophore.A one-way ANOVA and paired t test were used to calculate the data.Results ①The Maddox rod and synoptophore measured the highest amounts of esophoria,accounting for 38％ and 34％; hyperphoria was the least,accounting for 2％ and 4％.Measurements with the special visual measurement instrument found the highest amounts of esophoria plus hyperphoria,accounting for 36％; orthophoria was found the least,accounting for 4％.②Esophoria values measured in order from the most to the least were the Maddox rod,measurement instrument and synoptophore (F=3.18,P＜0.05).There was a significant difference between the Maddox rod and synoptophore (P＜0.05),but there were no significant differences between the Maddox rod and measurement instrument and the measurement instrument and the synoptophore (9＞0.05).Exophoria values measured from high to low were the Maddox,synoptophore and inspection instrument.There were no significant differences among the three methods (F=0.83,P＞0.05).Hyperphoria values measured from high to low were the measurement instrument,Maddox rod and synoptophore (F=6.34,P＜0.05).There were significant differences between the measurement instrument and synoptophore and the Maddox rod and synoptophore (P＜0.05),but there was no significant difference between the measurement instrument and Maddox rod (P＞0.05).③The dominant eye's value was higher than the nondominant eye's in esophoria,exophoria and hyperphoria,but only the Maddox rod measured a significant difference in esophoria (t=2.74,P＜0.01).Conclusion There were differences in the degree of heterphoria measured by the three instruments,but there was no significant difference between the measurement instrument and Maddox rod. Key words: Heterophoria; Visual function test; Com study

The present paper reports on the design of a pilot circulating fluidized bed combustor (CFB) for the conversion of lignin-rich residue derived from a second-generation bioethanol production plant. The designed combustor aims to improve the combustion efficiency of the lignin-rich residue, therefore increasing the heat recovery to partially cover the biorefinery’s heat consumption. Among the existing technologies, the fluidized bed combustion shows several advantages, in particular the fuel flexibility and the higher combustion efficiency mainly due to the presence of an inert material that uniforms the temperature and enhance the reactants mixing. The CFB differs from the bubbling fluidized bed (BFB) for the higher velocity of the oxidizer in the reactor, resulting in a better gas-solid mixing and higher burning rate (Basu 2015). Hence, by providing enhanced fuel conversion rate is and reduced reaction time, the characteristics of this apparatus meet the requirements for a more efficient combustion of the lignin-rich residue. The CFB combustor is mainly composed by a vertical combustion chamber (riser), a solid gas-particle separator (cyclone) and a solid particles recirculation system (recirculation valve or loop seal valve). The design process followed some consequential steps. The first step involved the theoretical 1D modeling of thereactor. Considering the project constraints of maximum plant capacity (5 kg h-1) and the consequentmaximum thermal power, the geometry was chosen correlating some literature data to obtain a riser diameter of DN100 and a riser height of 3500 mm. Besides, energy and mass balances were carried out to obtain air mass flowrate data, which has an impact on the hydrodynamic study of the fluidized bed. After the geometry selection and the stoichiometric calculation, a mono-dimensional empirical model was implemented to estimate the physical behavior of the bed particles (Basu 2015), (Kunii & Levenspiel 1991). The main output of the model is the voidage fraction profile along the riser. Further important outcomes of the model are the pressure drop along the riser and the solid recirculating rate. The latter is the main input parameter for the design of the cyclone and the loop seal valve. The second step was focused on the realization of the Piping and Instrumentation Diagram selecting the measurement instruments (thermocouples, pressure transducers and flowmeters) and the ancillary equipment (blower pumps, valves and pipes). In the third step, a three- dimensional CAD model was drawn for the design of the mechanical parts including the choice of the materials and the layout. The last step involved the project of the control logic and the hardware for the data acquisition system. The results of combustion tests on the circulating fluidized bed prototype will be used to gain insights into the combustion process of the lignin-rich residue, in the perspective of an industrial scale up to increase the efficiency of the energy recovery.

Large-scale cooperation support for learners becomes even more important, when e-Learning is implemented in scalable, open, dynamic and heterogeneous environment. We have designed grid architecture and implemented grid middleware and higher CSCW services for establishing collaborative platform for e-Learning. A Learning Assessment Grid, abbreviated as LAGrid, is built on top of these services. This paper introduces the layered LAGrid architecture and presents how to implement grid middleware to support collaborative platform for e-Learning using Web services technologies. The work shows service-oriented grid middleware layer provides a good middleware platform for collaborative applications in large-scale cross-organization environment.

In the research area of grid computing and workflow technology, workflow products based on Web-service technology can work as grid services in grid architecture. A new algorithm of scheduling grid resource with workflow engine is discussed in this paper. The QoS, executing time of process, cost and workload of grid resources are the key factors in grid resources scheduling. Dynamic feed back mechanism and executing time estimation are applied in this algorithm, which can keep the grid resources in a good balance and advance the whole performance of the grid application with workflow service.

To be effectively adopted in different application domains, next‐generation Grids need to address different issues such as: an increasing complexity and distribution of applications; different goals, skills and habits of Grid users; availability of different programming and deployment models; heterogeneous capabilities and performances of access networks and devices. Moreover, scientific and commercial applications, as well as Grid middleware, will increasingly produce an overwhelming quantity of application and usage data. Although the ongoing convergence between Grids, Web Services, and the Semantic Web constitutes a milestone towards a service‐oriented Grid architecture, which has the potential to face important issues such as application programming and business modelling, many other issues need research and development efforts. The great availability of data and information at the different layers of Grids, the maturity of data exploration techniques able to extract and synthesize knowledge, such as data mining, text summarization, semantic modelling, and knowledge management, and the demand for intelligent services in different phases of application life cycle are the driving forces towards novel knowledge‐based Grid services. Guided by those considerations, the paper first introduces main requirements of next‐generation Grids and then describes some representative knowledge‐based Grid services for both applications support and system management. Simple cases study showing how such services could be employed are discussed. Copyright © 2005 John Wiley & Sons, Ltd.

This work concentrates on appropriate set-up and initial validation of a mobile WIMAX testbed that will be used to validate the performance of modern video-streaming solutions for surveillance and multimedia deployment. Detailed discussion of the testbed and measurement instrumentation is made together with careful validation of tools in this paper. Especially a reliable but low-cost approach to precise time synchronization is presented. Authors provide the reference measurements in a WiMAX test network using IP performance metrics. The tests performed provide preliminary validation of the campus testbed and validates measurement experience that will be further followed in selected commercial WiMAX networks in Poland. It has been shown that (irrespective of the WIMAX modem) given two sample locations within a 1km range from base station, for tests with mobility there is a trend of decreasing delay (ca. 50% decrease) when the throughput increases. The scenario shows that from the delay perspective, the speed ranges between 10-30 km/h do not influence measurements significantly.

Over the last ∼10 years, advanced instrumentation onboard several spacecraft (e.g., WIND, SAMPEX, SOHO, and ACE), extended our ability to explore energy spectra, elemental, isotopic, and ionic charge composition of solar energetic particle (SEP) events in a wide energy range from ∼10 keV/nuc to ∼100 MeV/nuc. Due to the much improved sensitivity of the instrumentation, spectral and compositional measurements are now available for a large range of particle intensities, i.e. not only for large SEP events generally associated with coronal mass ejections (CMEs) and coronal/interplanetary shocks, but also for small, flare associated events. Originally, these two types of events were classified as gradual and impulsive, based on the duration of the associated soft X-ray emission, but this two-class paradigm of SEP events was also useful to distinguish differences in the acceleration processes involved. However, in the last few years, the two-class paradigm has been challenged by several observations, as, for example, significant enrichment of 3 He and heavy ions and high Fe charge states of ∼20 at high energies, were found in interplanetary shock related events. In this paper the recent observations on ion composition will be reviewed and their implications for our understanding of the different acceleration scenarios will be discussed.

Grid computing provides a robust paradigm to aggregate disparate resources in a secure and controlled environment. Grid architectures require an underpinning Quality of Service (QoS) support in order to manage complex data and computation intensive applications. However, QoS guarantees in the Grid context have not been given the attention they merit. In order to enhance the functionality offered by computational Grids, we overlay the Grid framework with an advanced QoS architecture, called G-QoSM. The G-QoSM framework provides a new service-oriented QoS management model that leverages the Open Grid Service Architecture (OGSA) and has a number of interesting features: (1) Grid service discovery based on QoS attributes, (2) policy-based admission control for advance reservation support, and (3) Grid service execution with QoS constraints. This paper discusses the different components of the G-QoSM framework, in the context of OGSA architectures.

Storage Grid is a new model for deploying and managing the heterogeneous, dynamic, large-scale, and geographically distributed storage resources. This chapter discusses the challenges and solutions involved in building a Service Oriented Storage (SOS) Grid. By wrapping the diverse storage resources into atomic Grid services and federating multiple atomic Grid services into composite services, the SOS Grid can tackle the heterogeneity and interoperability. Peer-to-peer philosophy and techniques are employed in the SOS Grid to eliminate the system bottleneck and single point of failure of the traditional centralized or hierarchical Grid architecture, while providing dynamicity and scalability. Because Grid service is not designed for critical and real-time applications, the SOS Grid adopts Grid service to glue the distributed and heterogeneous storage resources, while using binary code to transfer data. The proposed methods strike a good balance among the heterogeneity, interoperability, scalability and performance of the SOS Grid.

This report delves into the critical aspects of grid services provided by solar inverter-based resources (IBRs), with an emphasis on the evolving landscape of microgrids, virtual power plants (VPPs), aggregators, and distributed energy resource management systems (DERMS). As the energy sector undergoes a transformative shift towards more decentralized and resilient grid architectures, understanding the multifaceted risks associated with these technologies becomes paramount. The report categorizes these risks into organizational, technical, and procedural domains, providing a thorough risk assessment framework that stakeholders can utilize to anticipate and mitigate potential issues. In addressing the increasing complexity of grid interconnections, the report highlights the importance of Cyber-Informed Engineering (CIE). By embedding engineering controls and cybersecurity measures into the early stages of system design, this approach aims to fortify grid infrastructure against emerging cyber threats. The analysis includes an exploration of best practices and strategies for integrating CIE principles to enhance grid security and resilience. To provide practical insights, the report conducts a detailed consequence analysis of various grid services and cyber mitigations that can be applied through the interconnection process. This analysis evaluates the potential impacts of different failure modes and vulnerabilities, offering a clear understanding of the consequences that could arise from disruptions within the energy grid. The findings are further enriched by a series of case studies that illustrate real-world scenarios and lessons learned from past incidents. Through this comprehensive examination of grid services and their criticality, the report aims to prepare industry professionals with the knowledge and tools necessary to navigate the complexities of modern energy systems. By providing a comprehensive approach that includes risk assessment, cybersecurity, and consequence analysis, solar stakeholders can more effectively guarantee the reliability, efficiency, and security of the energy grid.

Knowledge discovery is a compute and data intensive process that allows for finding patterns, trends, and models in large datasets. The Grid can be effectively exploited for deploying knowledge discovery applications because of the high-performance it can offer and its distributed infrastructure. For effective use of Grids in knowledge discovery, the development of middleware is critical to support data management, data transfer, data mining and knowledge representation. To such purpose, we designed the Knowledge Grid, a high-level environment providing for Grid-based knowledge discovery tools and services. Such services allow users to create and manage complex knowledge discovery applications, composed as workflows that integrate data sources and data mining tools provided as distributed Grid services. This chapter describes the Knowledge Grid architecture and describes how its components can be used to design and implement distributed knowledge discovery applications. Then, the chapter describes how the Knowledge Grid services can be made accessible using the Open Grid Services Architecture (OGSA) model.