In this paper, we propose an approach for the real-time performance analysis of distributed software with reliability constraints, called Athena. The approach is based on the real-time and reliability performance anal...
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In this paper, we propose an approach for the real-time performance analysis of distributed software with reliability constraints, called Athena. The approach is based on the real-time and reliability performance analysis of distributed program. In Athena, two important factors, imperfect nodes and the links reliability, are introduced. The algorithms proposed in Athena generates sub-graphs, counts the reliability of each sub-graph, calculates the transmission time for all the transmission paths of each data file, and computes response time of each data file with reliability constraint. In this way, the real-time performance of distributed software with reliability constrains can be evaluated.
One of the main properties of today's distributed and parallelsystems, such as mobile ad-hoc networks and grids, is their heterogeneity in the available resources. Further, many applications of such systems are s...
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One of the main properties of today's distributed and parallelsystems, such as mobile ad-hoc networks and grids, is their heterogeneity in the available resources. Further, many applications of such systems are subject to time/Utility Function (TUF) time constraints for jobs, unavoidable variability in job characteristics and arrivals, and statistical assurance requirements on timeliness behaviors. In this paper, we propose an exact analytical solution for performance evaluation of dynamic policies used for routing of TUF-constrained Firm real-time (FRT) jobs among parallel single-processor queues with arbitrary processing rates and capacities. The analytical method can be used for the evaluation of the compliance of some important statistical assurance requirements. Furthermore, we present a utility-aware dynamic routing policy to improve the expected accrued utility of the parallel system. The policy called Maximum Expected Utility (MEU) behaves based on the information gathered from the analytical solution. MEU is compared with some well-known Dynamic Routing (DR) policies for different TUF shapes and both cases of homogeneous and heterogeneous processors of a two-queue system. The comparisons show the efficiency of MEU for the former case and its good behavior in most situations for the latter case.
Field-programmable gate array (FPGA)-based real-time simulators are often applied in simulations of active distribution networks (ADNs) because of their parallel architectures and low cost. The overall performance of ...
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Field-programmable gate array (FPGA)-based real-time simulators are often applied in simulations of active distribution networks (ADNs) because of their parallel architectures and low cost. The overall performance of an FPGA-based real-time simulator is mainly determined by its kernel solver, which solves the nodal equation at each simulation time step. With the increasing scale of ADNs, real-time simulations of fast switching dynamics, along with limited computation hardware, have increased the requirements of the solver in terms of both time and resource consumption. In this study, a highly parallel kernel solver is proposed to improve the simulation efficiency of the FPGA-based real-time simulator. The multi-level parallel design and its implementation, including the parallelism at the system and module and element levels, are presented in detail. A modified IEEE 123-node system with distributed photovoltaics (PVs) is then simulated using a three-FPGA-based real-time simulator. Simulation results are compared with the commercial simulation tool PSCAD/EMTDC to validate the proposed kernel solver.
Continuous innovations in adaptive matched-field processing (MFP) algorithms have presented significant increases in computational complexity and resource requirements that make development and use of advanced paralle...
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Continuous innovations in adaptive matched-field processing (MFP) algorithms have presented significant increases in computational complexity and resource requirements that make development and use of advanced parallel processing techniques imperative. In real-time sonar systems operating in severe underwater environments, there is a high likelihood of some part of systems exhibiting defective behavior, resulting in loss of critical network, processor, and sensor elements, and degradation in beam power pattern. Such real-time sonar systems require high reliability to overcome these challenging problems. In this paper, efficient fault-tolerant parallel algorithms based on coarse-grained domain decomposition methods are developed in order to meet real-time and reliability requirements on distributed array systems in the presence of processor and sensor element failures. The performance of the fault-tolerant parallel algorithms is experimentally analyzed in terms of beamforming performance, computation time, speedup, and parallel efficiency on a distributed testbed. The performance results demonstrate that these fault-tolerant parallel algorithms can provide real-time, scalable, lightweight, and fault-tolerant implementations for adaptive MFP algorithms on distributed array systems.
With the increased degree of miniaturization resulting from the use of modem VLSI technology and the high communication bandwidth available through optical connections, it is now possible to build massively parallel c...
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With the increased degree of miniaturization resulting from the use of modem VLSI technology and the high communication bandwidth available through optical connections, it is now possible to build massively parallel computers based on distributed modules which can be embedded in advanced industrial products. Examples of such future possibilities are ''action-oriented systems'', in which a network of highly parallel modules perform a multitude of tasks related to perception, cognition, and action. The paper discusses questions of architecture on the level of modules and inter-module communication and gives concrete architectural solutions which meet the demands of typical, advanced industrial real-time applications. The interface between the processors arrays and the all-optical communication network is described in some detail. Implementation issues specifically related to the demand for miniaturization are discussed.
A static analysis for reasoning about the temporal behaviors of programs in real-timedistributed programming languages is proposed. The analysis is based on the action set semantics using the pure maximal parallelism...
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A static analysis for reasoning about the temporal behaviors of programs in real-timedistributed programming languages is proposed. The analysis is based on the action set semantics using the pure maximal parallelism model. It is shown how to specify and verify various timing properties of real-time programs. The approach provides only an approximate timing behavior, because the state information is ignored. However, many interesting properties such as parallel actions, deadlocks, livelocks, terminations, temporal errors, and failures, can be identified. Furthermore, the approach is compositional and thus makes it possible to reason about the timing properties incrementally. The method not only leads to efficient algorithms for the static analysis of CSP programs but also applies to many other languages.
This paper addresses workload allocation techniques for two types of sequential jobs that might be found in multicluster systems, namely, non-real-time jobs and soft real-time jobs. Two workload allocation strategies,...
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This paper addresses workload allocation techniques for two types of sequential jobs that might be found in multicluster systems, namely, non-real-time jobs and soft real-time jobs. Two workload allocation strategies, the Optimized mean Response time (ORT) and the Optimized mean Miss Rate (OMR), are developed by establishing and numerically solving two optimization equation sets. The ORT strategy achieves an optimized mean response time for non-real-time jobs, while the OMR strategy obtains an optimized mean miss rate for soft real-time jobs over multiple clusters. Both strategies take into account average system behaviors (such as the mean arrival rate of jobs) in calculating the workload proportions for individual clusters and the workload allocation is updated dynamically when the change in the mean arrival rate reaches a certain threshold. The effectiveness of both strategies is demonstrated through theoretical analysis. These strategies are also evaluated through extensive experimental studies and the results show that when compared with traditional strategies, the proposed workload allocation schemes significantly improve the performance of job scheduling in multiclusters, both in terms of the mean response time (for non-real-time jobs) and the mean miss rate (for soft real-time jobs).
High-speed, wide-area networks have made it both possible and desirable to interconnect geographically distributed lections of scientific data, remote scientific instruments, and high-performance computer systems. His...
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High-speed, wide-area networks have made it both possible and desirable to interconnect geographically distributed lections of scientific data, remote scientific instruments, and high-performance computer systems. Historically, performance analysis has focused on monolithic applications executing on large, stand-alone, parallelsystems. In such a domain, measurement, postmortem analysis, and code optimization suffice to eliminate performance bottlenecks and optimize applications. distributed visualization, data mining, and analysis tools allow scientists to collaboratively analyze and understand complex phenomena. Likewise, real-time performance measurement and immersive performance display systems-that is, systems providing large stereoscopic displays of complex data-enable collaborating groups to interact with executing software, tuning its behavior to meet research and performance goals. To satisfy these demands, the authors designed Virtue, a prototype system that integrates collaborative, immersive performance visualization with real-time performance measurement and adaptive control of applications on computational grids. These tools enable physically distributed users to explore and steer the behavior of complex software in realtime and to analyze and optimize distributed application dynamics.
Of several schemes proposed to handle the propagation of erroneous information among interacting processes in distributed and parallel computer systems, the distributedreal-time conversation (DRC) scheme stands out i...
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ISBN:
(纸本)0818680474
Of several schemes proposed to handle the propagation of erroneous information among interacting processes in distributed and parallel computer systems, the distributedreal-time conversation (DRC) scheme stands out in its fast forward recovery capability which is essential in safety-critical hard-real-time applications. However, previous formulations of the scheme remained at relatively abstract levels and practical models for their implementation in complex safety-critical real-time applications were not established before. The core approach in the DRC scheme is to make a group of computing stations cooperate in recovery from hardware and software faults that may occur during their interaction. In this paper we present a practical implementation model for the DRC scheme. A simple model of an anti-missile defense system is used to illustrate the main structuring principles of the DRC scheme and major components of the practical implementation model.
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