Graph isomorphism problem has always been mathematics and engineering technology community concern, the reason mainly from two aspects: First, in theory, is generally believed that the problem is NP-complete problem; ...
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Graph isomorphism problem has always been mathematics and engineering technology community concern, the reason mainly from two aspects: First, in theory, is generally believed that the problem is NP-complete problem; Second, the graph isomorphism the problem with good prospects, in chemistry, operations research, computerscience, electronics, network theory has applications in many fields, but the exponential complexity of the algorithm and the algorithm itself makes the limitations applicable to the object involved with complex graphics the application of structure is difficult to determine the start. In this paper, class tree is proposed based on the node to delete the exact graph isomorphism problem, you can quickly determine the graph isomorphism problem, and theoretical analysis and experiments show that the algorithm can determine the class in polynomial time tree isomorphism problem.
SNNs have achieved great attention in recent years as they contain neurons more like those in the brain and use spikes to encode and transmit information efficiently among neurons with lower energy consumption. A Reti...
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ISBN:
(纸本)9781450385893
SNNs have achieved great attention in recent years as they contain neurons more like those in the brain and use spikes to encode and transmit information efficiently among neurons with lower energy consumption. A Retina-LGN-V1 structure-like spiking neuron network (RLVSL-SNN) is proposed in this paper. It is inspired by the structure of mammalian primary visual pathway, and simulates different biological structures of Retina, LGN and V1. Noise reduction circuit and light adaptation circuit are also simulated for enhancing the robustness of its extracted features. RLVSL-SNN is a bio-plausible neuron network as it has firing rates of neurons in each layer that are similar to those of biological experiments. Besides, a full-connected SNN (FC SNN) is implemented following RLVSL-SNN for classification to evaluate the extracted features. The additive spiking timing dependent plasticity (STDP) learning rules and the ANN-to-SNN conversion method are utilized to train RLVSL-SNN and FC SNN, respectively. The experiments on MNIST dataset have verified that RLVSL-SNN is comparable to AlexNet for classification by features from spikes.
Nowadays, more and more scientific applications are moving to cloud computing. The optimal deployment of scientific applications is critical for providing good services to users. Scientific applications are usually to...
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Nowadays, more and more scientific applications are moving to cloud computing. The optimal deployment of scientific applications is critical for providing good services to users. Scientific applications are usually topology-aware applications. Therefore, considering the topology of a scientific application during the development will benefit the performance of the application. However, it is challenging to automatically discover and make use of the communication pattern of a scientific application while deploying the application on cloud. To attack this challenge, in this paper, we propose a framework to discover the communication topology of a scientific application by pre-execution and multi-scale graph clustering, based on which the deployment can be optimized. Comprehensive experiments are conducted by employing a well-known MPI benchmark and comparing the performance of our method with those of other methods. The experimental results show the effectiveness of our topology-aware deployment method.
Cloud computing provides a new paradigm for resource utilization and sharing. However, the reliability problems, like system failures, often happen in cloud systems and bring enormous loss. Trace-oriented monitoring i...
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Cloud computing provides a new paradigm for resource utilization and sharing. However, the reliability problems, like system failures, often happen in cloud systems and bring enormous loss. Trace-oriented monitoring is an important runtime method to improve the reliability of cloud systems. In this paper, we propose to bring runtime verification into trace-oriented monitoring, to facilitate the specification of monitoring requirements and to improve the efficiency of monitoring cloud systems. Based on a data set collected from a cloud storage system in a real environment, we validate our approach by monitoring the critical properties of the storage system. The preliminary experimental results indicate the promise of our approach.
Virtualization is the foundation for cloud computing, and the virtualization can not be achieved without software defined, elastic, flexible and scalable virtual layers. Unfortunately, if multiple virtual storage devi...
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Virtualization is the foundation for cloud computing, and the virtualization can not be achieved without software defined, elastic, flexible and scalable virtual layers. Unfortunately, if multiple virtual storage devices are chained together, the system may be subject to severe performance degradation. While the read-ahead (RA) mechanism in storage devices plays a very important role to improve I/O performance, RA may not be effective as expected for multiple virtualization layers, since it is originally designed for one layer only. When I/O requests are passed through a long I/O path, they may trigger a chain reaction and lead to unnecessary data transmission and thus bandwidth waste. In this paper, we study the dynamic behavior of RA through multiple I/O layers and demonstrate that if controlled well, RA can greatly accelerate I/O speed. We present RAFlow, a RA control mechanism, to effectively improve I/O performance by strategically expanding RA window at each layer. Our real-world experiments show that it can achieve 20% to 50% performance improvement in I/O paths with up to 8 virtualized storage devices.
Recently, Cloud computing, as one of the hottest words in IT world, has drawn great attention. Many IT companies such as IBM, Google, Amazon, Microsoft, Yahoo and others vigorously develop cloud computing systems and ...
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Recently, Cloud computing, as one of the hottest words in IT world, has drawn great attention. Many IT companies such as IBM, Google, Amazon, Microsoft, Yahoo and others vigorously develop cloud computing systems and related products to customers. However, there are still some difficulties for customers to adopt cloud computing, in which many security issues exist, because data for a customer is stored and processed in cloud, not in a local machine. This paper briefly introduces cloud computing and its key concepts. In particularly, we intend to discuss security requirements and security issues involving data, application and virtualization in cloud computing, as well as current solutions to these issues.
Maximum common sub-graph isomorphism (MCS) is a famous NP-hard problem in graph processing. The problem has found application in many areas where the similarity of graphs is important, for example in scene matching, v...
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Maximum common sub-graph isomorphism (MCS) is a famous NP-hard problem in graph processing. The problem has found application in many areas where the similarity of graphs is important, for example in scene matching, video indexing, chemical similarity and shape analysis. In this paper, a novel algorithm Qwalk is proposed for approximate MCS, utilizing the discrete-time quantum walk. Based on the new observation that isomorphic neighborhood group matches can be detected quickly and conveniently by the destructive interference of a quantum walk, the new algorithm locates an approximate solution via merging neighborhood groups. Experiments show that Qwalk has better accuracy, universality and robustness compared with the state-of-the-art approximate MCS methods. Meanwhile, Qwalk is a general algorithm to solve the MCS problem approximately while having modest time complexity.
In China, the expressway isn’t free. When a vehicle exits, the exit toll station needs to calculate the toll according to the vehicle trajectory obtained by sending a trajectory query task to the trajectory center re...
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