Many different existing technologies and techniques have been developed to accelerate Hyper Text Transfer Protocol (HTTP) with the aim of improving the end-user's web browsing experience. However, there is no stan...
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Many different existing technologies and techniques have been developed to accelerate Hyper Text Transfer Protocol (HTTP) with the aim of improving the end-user's web browsing experience. However, there is no standard methodology for evaluating HTTP performance or for the evaluation of a given HTTP acceleration technology in a multi-user scenario. In this paper we present a framework HTTP-AE (HTTP Automated Evaluation) for measuring the end-user's web browsing quality of experience. We describe how HTTP-AE can be used to automate the evaluation of HTTP performance and for the evaluation of HTTP acceleration technologies in multi-user environments. We present three case studies in which we evaluate three different HTTP acceleration technologies for satellite systems using HTTP-AE. In our first two case studies we show that typical browser HTTP acceleration techniques operate sub-optimally on satellite systems. In our third case study we show that in multi-user scenarios, HTTP acceleration technologies, which break the end-to-end semantics of HTTP, can distribute network resources unfairly to the end-users.
Exploiting locality at run-time is a complementary approach to a compiler approach for those applications with dynamic memory access patterns. This paper proposes a memory-layout oriented approach to exploit cache loc...
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ISBN:
(纸本)0818686502
Exploiting locality at run-time is a complementary approach to a compiler approach for those applications with dynamic memory access patterns. This paper proposes a memory-layout oriented approach to exploit cache locality for parallel loops at run-time on symmetric multi-processor (SMP) systems. Guided by application-dependent hints and the targeted cache architecture, it reorganizes and partitions a parallel loop through shrinking and partitioning the memory-access space of the loop at run-time. In the generated task partitions, the data sharing among partitions is minimized and the data reuse in a partition is maximized. The execution of tasks in partitions is scheduled in an adaptive and locality-preserved way to achieve balanced execution, for minimizing the execution time of applications by trading off load balance and locality. Based on simulation and measurement, we show our run-time approach can achieve comparable performance with the compiler optimizations for two applications, whose load balance and cache locality can be well optimized by the tiling and other program transformations. However our experimental results also show that our approach is able to significantly improve the memory performance for the applications with dynamic memory access patterns. This type of programs are usually hard to be optimized by compilers.
Diagnostic tests are used to determine anomalies in complex systems such as organisms or built structures. Once a set of tests is performed, the experts interpret their results and make decisions based on them. This p...
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Unlike most existing works that focus on a conventional omni-directional sensor network, we investigate the sensing coverage problem in a directional sensor network through mathematically modeling, analysis, and compu...
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Unlike most existing works that focus on a conventional omni-directional sensor network, we investigate the sensing coverage problem in a directional sensor network through mathematically modeling, analysis, and computer-based simulation evaluation. Research results show: 1) A factor of (2π/θ) more sensors will be required to provide the same sensing coverage in a θ(θ α = ln(1-α)-ln(1-f)/ln(1-f), is solely determined by the sensing coverage requirement in an application and is independent of sensor features. Simulation results validate the modeling, derivation, and analysis.
The world is facing an extreme crisis due to the COVID-19 pandemic. The COVID-19 virus interrupts the world's economy and social factors;thus, many countries fall into poverty. Also, they lack expertise in this fi...
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This study aims to enhance the performance of the Proximal Policy Optimization (PPO) algorithm in continuous control tasks, particularly in the Pendulum-v1 environment. We introduce a clustering-based approach to simp...
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We present a modular framework designed to enable a robot hand-arm system to learn how to catch flying objects, a task that requires fast, reactive, and accurately-timed robot motions. Our framework consists of five c...
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Current reinforcement learning algorithms struggle in sparse and complex environments, most notably in long-horizon manipulation tasks entailing a plethora of different sequences. In this work, we propose the Intrinsi...
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This paper presents a computer-aided diagnosis scheme for the detection of prostate cancer. The pattern recognition scheme proposed, utilizes fused dynamic and morphological features extracted from magnetic resonance ...
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This paper presents a computer-aided diagnosis scheme for the detection of prostate cancer. The pattern recognition scheme proposed, utilizes fused dynamic and morphological features extracted from magnetic resonance images (MRIs). The performance of the proposed scheme has been evaluated through extensive training and testing on several patient cases, where the staging of their condition has been previously evaluated by both ultrasoundguided biopsy and radiological assessment. The classification scheme is based on Probabilistic Neural Networks (PNNs), whose parameters are estimated using the Expectation-Maximization (EM) algorithm during a training phase. Fusion of the image characteristics is performed by properly aligning the respective T1-weighted dynamic and T2-weighted morphological images, allowing accurate feature selection from both images. The proposed classification scheme as well as the effect of fusion on the extracted features is tested, with respect to the correct classification rate (CCR) of each case.
The use of higher-order functions, as a method of abstraction and re-use in EC encodings, has been the subject of relatively little research. In this paper we introduce and give motivation for the ideas of higher-orde...
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The use of higher-order functions, as a method of abstraction and re-use in EC encodings, has been the subject of relatively little research. In this paper we introduce and give motivation for the ideas of higher-order functions, and describe their general advantages in EC encodings. We implement grammars using higher-order ideas for two problem domains, music and 3D architectural design, and use these grammars in the grammatical evolution paradigm. We demonstrate four advantages of higher-order functions (patterning of phenotypes, non-entropic mutations, compression of genotypes, and natural expression of artistic knowledge) which lead to beneficial results on our problems.
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