Knowledge representation learning (KRL) is one of the important research topics in artificial intelligence and Natural language processing. It can efficiently calculate the semantics of entities and relations in a low...
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With the rapid development and application of cloud computing, there exist plenty of clouds that are distributed on the open Internet, decentralized in the management, evolving with various services providing diverse ...
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Currently, the performance problems of software systems gets more and more attentions. Among various diagnosis methods based on system traces, principal component analysis (PCA) based methods are widely used due to th...
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Functional programming languages have a long history and receive more and more attention today. The paper focuses on the development of functional languages and aims to introduce the concepts, such as higher-order fun...
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According to Moore's law the complexity of VLSI circuits has doubled approximately every two years, resulting in simulation becoming the major bottleneck in the circuit design process. parallel and distributed sim...
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Interconnection network plays an essential role in the architecture of large-scale high performance computing (HPC) systems. In the paper, we construct a novel family of lowdiameter topologies, Galaxyfly, using techni...
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Decision trees are famous machine learning classifiers which have been widely used in many areas, such as healthcare, text classification and remote diagnostics, etc. The service providers usually host a decision tree...
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Cooperation of CPU and hardware accelerator on SoC FPGA to accomplish computational intensive tasks, provides significant advantages in performance and energy efficiency. However, current operating systems provide lit...
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The key escrow problem and high computational cost are the two major problems that hinder the wider adoption of hierarchical identity-based signature (HIBS) scheme. HIBS schemes with either escrow-free (EF) or online/...
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Existing routing protocols for Wireless Mesh Networks (WMNs) are generally optimized with statistical link measures, while not addressing on the intrinsic uncertainty of wireless links. We show evidence that, with the...
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ISBN:
(纸本)9781424459889
Existing routing protocols for Wireless Mesh Networks (WMNs) are generally optimized with statistical link measures, while not addressing on the intrinsic uncertainty of wireless links. We show evidence that, with the transient link uncertainties at PHY and MAC layers, a pseudo-deterministic routing protocol that relies on average or historic statistics can hardly explore the full potentials of a multi-hop wireless mesh. We study optimal WMN routing using probing-based online anypath forwarding, with explicit consideration of transient link uncertainties. We show the underlying connection between WMN routing and the classic Canadian Traveller Problem (CTP) [1]. Inspired by a stochastic recoverable version of CTP (SRCTP), we develop a practical SRCTP-based online routing algorithm under link uncertainties. We study how dynamic next hop selection can be done with low cost, and derive a systematic selection order for minimizing transmission delay. We conduct simulation studies to verify the effectiveness of the SRCTP algorithms under diverse network configurations. In particular, compared to deterministic routing, reduction of end-to-end delay (51:15∼73:02%) and improvement on packet delivery ratio (99:76%) are observed.
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