1055819
Virtual Burst Assembly - A Solution to Out-of-Sequence Delivery in Optical Burst Switching Networks
Optical burst switching (OBS) has been considered the most promising optical switching technology. To the best of authors' knowledge, this is the first paper that identifies the out- of-sequence delivery problem in OBS networks. To minimize the impact of the out-of-sequence delivery on buffer space and resequencing latency, we propose a novel virtual burst assembly scheme to eliminate the problem. In addition to simulation results obtained from the OBS-ns2 simulator, we implemented the proposed virtual burst assembly scheme in Altera Stratix II FPGA hardware using Verilog HDL, and tested experimentally using real video. Both simulation and experimental results confirm the effectiveness of the proposed scheme.
11915654
Hybrid Neural Network Architecture for On-Line Learning
Approaches to machine intelligence based on brain models use neural networks for generalization but they do so as signal processing black boxes. In reality, the brain consists of many modules that operate in parallel at different levels. In this paper we propose a more realistic biologically inspired hybrid neural network architecture that uses two kinds of neural networks simultaneously to consider short-term and long-term characteristics of the signal. The first of these networks quickly adapts to new modes of operation whereas the second one provides more accurate learning within a specific mode. We call these networks the surfacing and deep learning agents and show that this hybrid architecture performs complementary functions that improve the overall learning. The performance of the hybrid architecture has been compared with that of back-propagation perceptrons and the CC and FC networks for chaotic time-series prediction, the CATS benchmark test, and smooth function approximation. It is shown that the proposed architecture provides a superior performance based on the RMS error criterion.
2862393
Online Constrained Pattern Detection over Streams
Online pattern detection poses a challenge in many data-intensive applications, including network traffic management, trend analysis, intrusion detection, and various intelligent sensor networks. These applications have to be time and space efficient while providing high quality answers. Meanwhile, far less attention has been paid for detecting constrained patterns, that cannot be simply matched because there is no available pattern for prediction. This paper presents our research effort in efficient pattern detection with constraint. We propose a new method named Online Pattern Detection with Constraint (OPDC) to detect constrained patterns over evolving data stream, taking into account various user-defined constraints. To ensure that the constrained patterns are representative, we extend regular expression in a simple but powerful way. Our experimental results on real data sets demonstrate the feasibility and effectiveness of the proposed scheme.
30833865
Noise-Aware Wavelength Assignment for Wavelength Switched Optical Networks
In transparent WSON (wavelength switched optical networks), signals are switched optically and propagate thousands of kilometers without electrical regeneration. Over such distances, physical impairments, such as crosstalk, ASE noise and so on, can accumulate along the path and lead to signal quality degradation. If the admission of a lightpath will either cause its BER to be too high, or sufficiently degrade the performance of the already established lightpaths, it must be blocked. Most of recent research only consider the first case, but ignore the second case, which will lead to service interruption. In this paper, a new noise-aware wavelength assignment scheme called NAWA has been proposed, which use IIES (Impairments impact Evaluation Scheme) to solve both problems mentioned above in a distributed way. Simulations have been conducted and numerical results show that: Compared with normal impairment-aware solutions, NAWA can eliminate the occurrence of service interruption, and achieve better performance in total blocking.
5365763
An extended approach to improving the semantic interoperation among reuse epositories
Software reuse is widely believed as a feasible way to improve both the productivity and quality of software development. The developers must be capable to acquire enough desired components before developing with reuse. Many Internet-enabled reuse repositories exist to provide access to reusable resources. It is necessary to eliminate the semantic gaps of the repositories to enable users to access resources from multiple repositories via a single representation view. In some sense, the only usable information to mine the semantics of the terms representing the resources is the mutual components stored in the repositories. In this paper, the extended improved relevancy matching and ranking (EIRMR) method is proposed to enhance the semantic interoperability of reuse repositories, based on our previous work (IRMR) and the mutual components in the third-party repositories. Experimental results on the data sets from the real repositories demonstrated an improvement in terms of searching effectiveness.
18513431
Modeling and Properties of Nonlinear Stochastic Dynamical System of Continuous Culture
The stochastic counterpart to the deterministic description of continuous fermentation with ordinary differential equation is investigated in the process of glycerol bio-dissimilation to 1,3-propanediol by Klebsiella pneumoniae. We briefly discuss the continuous fermentation process driven by three-dimensional Brownian motion and Lipschitz coefficients, which is suitable for the factual fermentation. Subsequently, we study the existence and uniqueness of solutions for the stochastic system as well as the boundedness of the Two-order Moment and the Markov property of the solution. Finally stochastic simulation is carried out under the Stochastic Euler-Maruyama method.
5908339
Intelligent Hierarchical Intrusion Detection System for Secure Wireless Ad Hoc Network
The nature of mobile ad hoc network (MANETs) makes them vulnerable to security attacks. Intrusion detection is a vital secure scheme for wireless mobile ad hoc networks (MANETs). However, the generalizing ability of current IDS is poor when given less priori knowledge, and a centralized intrusion detection network security solution does not work well in MANETs. In this paper we discuss the characters of security issues in ad hoc networks and propose a Support Vector Machine (SVM) based distributed hierarchical intrusion detection system that adapt to the characters of current ad hoc networks. Performance evaluations based on simulation experiment manifested our proposed approach is efficient and effective.