994 resultados para dynamic configuration


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Due to environmental changes and business trends such as globalisation, outsourcing and virtualisation, more and more companies get involved in business activities that are outside their direct control. This typically occurs by entering into collaborative relationships and joint ventures with specialised companies in order to fulfil the demands of customers quickly (DiMaggio, 2001). Organisational structures that results from such collaborative relationships and joint ventures are referred to in this paper as enterprises and the management of them known as enterprise management. The authors use the definition of the European Commission (2003) that defines an enterprise as “… an entity, regardless of its legal form … including partnerships or associations regularly engaged in economic activities.” Therefore in its most simple form an enterprise could be a single integrated company. However, findings from this research show that enterprises can also be made up of parts of different companies and the structure of the enterprise is contingent upon a variety of different factors. The success of the enterprise as a collaborative venture depends on the ability of companies to intermediate their internal core competencies into other participating companies’ value streams and simultaneously outsource their own peripheral activities to companies that can perform them quicker, cheaper, and more effectively (Lal et al., 1995). In other words, the peripheral activities of one member-company must be complemented by a core competence of another member-company within an overall enterprise.

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Due to environmental changes and business trends such as globalisation, outsourcing and virtualisation, more and more companies get involved in business activities that are outside their direct control. This typically occurs by entering into collaborative relationships and joint ventures with specialised companies in order to fulfil the demands of customers quickly (DiMaggio, 2001). Organisational structures that results from such collaborative relationships and joint ventures are referred to in this paper as enterprises and the management of them known as enterprise management. The authors use the definition of the European Commission (2003) that defines an enterprise as “… an entity, regardless of its legal form … including partnerships or associations regularly engaged in economic activities.” Therefore in its most simple form an enterprise could be a single integrated company. However, findings from this research show that enterprises can also be made up of parts of different companies and the structure of the enterprise is contingent upon a variety of different factors. The success of the enterprise as a collaborative venture depends on the ability of companies to intermediate their internal core competencies into other participating companies’ value streams and simultaneously outsource their own peripheral activities to companies that can perform them quicker, cheaper, and more effectively (Lal et al., 1995). In other words, the peripheral activities of one member-company must be complemented by a core competence of another member-company within an overall enterprise.

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The scarcity and diversity of resources among the devices of heterogeneous computing environments may affect their ability to perform services with specific Quality of Service constraints, particularly in dynamic distributed environments where the characteristics of the computational load cannot always be predicted in advance. Our work addresses this problem by allowing resource constrained devices to cooperate with more powerful neighbour nodes, opportunistically taking advantage of global distributed resources and processing power. Rather than assuming that the dynamic configuration of this cooperative service executes until it computes its optimal output, the paper proposes an anytime approach that has the ability to tradeoff deliberation time for the quality of the solution. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves at each iteration, with an overhead that can be considered negligible.

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The Smart Grid environment allows the integration of resources of small and medium players through the use of Demand Response programs. Despite the clear advantages for the grid, the integration of consumers must be carefully done. This paper proposes a system which simulates small and medium players. The system is essential to produce tests and studies about the active participation of small and medium players in the Smart Grid environment. When comparing to similar systems, the advantages comprise the capability to deal with three types of loads – virtual, contextual and real. It can have several loads optimization modules and it can run in real time. The use of modules and the dynamic configuration of the player results in a system which can represent different players in an easy and independent way. This paper describes the system and all its capabilities.

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Tulevaisuudessa siirrettävät laitteet, kuten matkapuhelimet ja kämmenmikrot, pystyvät muodostamaan verkkoyhteyden käyttäen erilaisia yhteysmenetelmiä eri tilanteissa. Yhteysmenetelmillä on toisistaan poikkeavat viestintäominaisuudet mm. latenssin, kaistanleveyden, virhemäärän yms. suhteen. Langattomille yhteysmenetelmille on myös ominaista tietoliikenneyhteyden ominaisuuksien voimakas muuttuminen ympäristön suhteen. Parhaan suorituskyvyn ja käytettävyyden saavuttamiseksi, on siirrettävän laitteen pystyttävä mukautumaan käytettyyn viestintämenetelmään ja viestintäympäristössä tapahtuviin muutoksiin. Olennainen osa tietoliikenteessä ovat protokollapinot, jotka mahdollistavat tietoliikenneyhteyden järjestelmien välillä tarjoten verkkopalveluita päätelaitteen käyttäjäsovelluksille. Jotta protokollapinot pystyisivät mukautumaan tietyn viestintäympäristön ominaisuuksiin, on protokollapinon käyttäytymistä pystyttävä muuttamaan ajonaikaisesti. Perinteisesti protokollapinot ovat kuitenkin rakennettu muuttumattomiksi niin, että mukautuminen tässä laajuudessa on erittäin vaikeaa toteuttaa, ellei jopa mahdotonta. Tämä diplomityö käsittelee mukautuvien protokollapinojen rakentamista käyttäen komponenttipohjaista ohjelmistokehystä joka mahdollistaa protokollapinojen ajonaikaisen muuttamisen. Toteuttamalla esimerkkijärjestelmän, ja mittaamalla sen suorituskykyä vaihtelevassa tietoliikenneympäristössä, osoitamme, että mukautuvat protokollapinot ovat mahdollisia rakentaa ja ne tarjoavat merkittäviä etuja erityisesti tulevaisuuden siirrettävissä laitteissa.

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Embedded software systems in vehicles are of rapidly increasing commercial importance for the automotive industry. Current systems employ a static run-time environment; due to the difficulty and cost involved in the development of dynamic systems in a high-integrity embedded control context. A dynamic system, referring to the system configuration, would greatly increase the flexibility of the offered functionality and enable customised software configuration for individual vehicles, adding customer value through plug-and-play capability, and increased quality due to its inherent ability to adjust to changes in hardware and software. We envisage an automotive system containing a variety of components, from a multitude of organizations, not necessarily known at development time. The system dynamically adapts its configuration to suit the run-time system constraints. This paper presents our vision for future automotive control systems that will be regarded in an EU research project, referred to as DySCAS (Dynamically Self-Configuring Automotive Systems). We propose a self-configuring vehicular control system architecture, with capabilities that include automatic discovery and inclusion of new devices, self-optimisation to best-use the processing, storage and communication resources available, self-diagnostics and ultimately self-healing. Such an architecture has benefits extending to reduced development and maintenance costs, improved passenger safety and comfort, and flexible owner customisation. Specifically, this paper addresses the following issues: The state of the art of embedded software systems in vehicles, emphasising the current limitations arising from fixed run-time configurations; and the benefits and challenges of dynamic configuration, giving rise to opportunities for self-healing, self-optimisation, and the automatic inclusion of users’ Consumer Electronic (CE) devices. Our proposal for a dynamically reconfigurable automotive software system platform is outlined and a typical use-case is presented as an example to exemplify the benefits of the envisioned dynamic capabilities.

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The resistivity of a field reversed configuration in a theta-pinch with slow rising current was investigated during the turbulent phase from the moment of field reversal until end of plasma radial implosion. This transport coefficient was obtained in a hydrogen plasma by local measurements with magnetic probe and compared to numerical calculations with Chodura resistivity and evolution of lower hybrid drift instability. The values of resistivity are higher than those predicted by classical binary collision. During early phase of confinement, the doubly layer structure of current sheath in the low electric field machine was theoretically well reproduced with anomalous collision frequency calculated with Chodura resistivity that provides appropriate conditions for onset of lower hybrid drift instability and the regular evolution of pinch. The plasma dynamic, radial profiles of magnetic field during the radial compression and resistivity values were equally close to those observed by the measurements. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.3698405]

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Due to dynamic variability, identifying the specific conditions under which non-functional requirements (NFRs) are satisfied may be only possible at runtime. Therefore, it is necessary to consider the dynamic treatment of relevant information during the requirements specifications. The associated data can be gathered by monitoring the execution of the application and its underlying environment to support reasoning about how the current application configuration is fulfilling the established requirements. This paper presents a dynamic decision-making infrastructure to support both NFRs representation and monitoring, and to reason about the degree of satisfaction of NFRs during runtime. The infrastructure is composed of: (i) an extended feature model aligned with a domain-specific language for representing NFRs to be monitored at runtime; (ii) a monitoring infrastructure to continuously assess NFRs at runtime; and (iii) a exible decision-making process to select the best available configuration based on the satisfaction degree of the NRFs. The evaluation of the approach has shown that it is able to choose application configurations that well fit user NFRs based on runtime information. The evaluation also revealed that the proposed infrastructure provided consistent indicators regarding the best application configurations that fit user NFRs. Finally, a benefit of our approach is that it allows us to quantify the level of satisfaction with respect to NFRs specification.

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This paper addresses the use of optimization techniques in the design of a steel riser. Two methods are used: the genetic algorithm, which imitates the process of natural selection, and the simulated annealing, which is based on the process of annealing of a metal. Both of them are capable of searching a given solution space for the best feasible riser configuration according to predefined criteria. Optimization issues are discussed, such as problem codification, parameter selection, definition of objective function, and restrictions. A comparison between the results obtained for economic and structural objective functions is made for a case study. Optimization method parallelization is also addressed. [DOI: 10.1115/1.4001955]

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A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

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Scheduling resolution requires the intervention of highly skilled human problemsolvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. This paper addresses the resolution of complex scheduling problems using cooperative negotiation. A Multi-Agent Autonomic and Meta-heuristics based framework with self-configuring capabilities is proposed.

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In heterogeneous environments, diversity of resources among the devices may affect their ability to perform services with specific QoS constraints, and drive peers to group themselves in a coalition for cooperative service execution. The dynamic selection of peers should be influenced by user’s QoS requirements as well as local computation availability, tailoring provided service to user’s specific needs. However, complex dynamic real-time scenarios may prevent the possibility of computing optimal service configurations before execution. An iterative refinement approach with the ability to trade off deliberation time for the quality of the solution is proposed. We state the importance of quickly finding a good initial solution and propose heuristic evaluation functions that optimise the rate at which the quality of the current solution improves as the algorithms have more time to run.

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Coarse Grained Reconfigurable Architectures (CGRAs) are emerging as enabling platforms to meet the high performance demanded by modern applications (e.g. 4G, CDMA, etc.). Recently proposed CGRAs offer time-multiplexing and dynamic applications parallelism to enhance device utilization and reduce energy consumption at the cost of additional memory (up to 50% area of the overall platform). To reduce the memory overheads, novel CGRAs employ either statistical compression, intermediate compact representation, or multicasting. Each compaction technique has different properties (i.e. compression ratio, decompression time and decompression energy) and is best suited for a particular class of applications. However, existing research only deals with these methods separately. Moreover, they only analyze the compaction ratio and do not evaluate the associated energy overheads. To tackle these issues, we propose a polymorphic compression architecture that interleaves these techniques in a unique platform. The proposed architecture allows each application to take advantage of a separate compression/decompression hierarchy (consisting of various types and implementations of hardware/software decoders) tailored to its needs. Simulation results, using different applications (FFT, Matrix multiplication, and WLAN), reveal that the choice of compression hierarchy has a significant impact on compression ratio (up to 52%), decompression energy (up to 4 orders of magnitude), and configuration time (from 33 n to 1.5 s) for the tested applications. Synthesis results reveal that introducing adaptivity incurs negligible additional overheads (1%) compared to the overall platform area.

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We present a system for dynamic network resource configuration in environments with bandwidth reservation. The proposed system is completely distributed and automates the mechanisms for adapting the logical network to the offered load. The system is able to manage dynamically a logical network such as a virtual path network in ATM or a label switched path network in MPLS or GMPLS. The system design and implementation is based on a multi-agent system (MAS) which make the decisions of when and how to change a logical path. Despite the lack of a centralised global network view, results show that MAS manages the network resources effectively, reducing the connection blocking probability and, therefore, achieving better utilisation of network resources. We also include details of its architecture and implementation

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We present a system for dynamic network resource configuration in environments with bandwidth reservation and path restoration mechanisms. Our focus is on the dynamic bandwidth management results, although the main goal of the system is the integration of the different mechanisms that manage the reserved paths (bandwidth, restoration, and spare capacity planning). The objective is to avoid conflicts between these mechanisms. The system is able to dynamically manage a logical network such as a virtual path network in ATM or a label switch path network in MPLS. This system has been designed to be modular in the sense that in can be activated or deactivated, and it can be applied only in a sub-network. The system design and implementation is based on a multi-agent system (MAS). We also included details of its architecture and implementation