In UMTS (universal mobile telecommunications system) networks upgraded with HSPA (high speed packet access) technology, the high access bandwidth and advanced mobile devices make it applicable to share large files among mobile users by peer-to-peer applications. To receive files quickly is essential for mobile users in file sharing applications, mainly because they are subject to unstable signal strength and battery failures. While many researches present peer-to-peer file sharing architectures in mobile environments, few works focus on decreasing the time spent in disseminating files among users. In this paper, we present an efficient peer-to-peer file sharing design for HSPA networks called AFAM -- Adaptive efficient File shAring for uMts networks. AFAM can decrease the dissemination time by efficiently utilizing the upload-bandwidth of mobile nodes. It uses an adaptive rearrangement of a node's concurrent uploads, which causes the count of the node's concurrent uploads to lower while ensuring that the node's upload-bandwidth can be efficiently utilized. AFAM also uses URF -- Upload Rarest First policy for the block selection and receiver selection, which achieves real rarest-first for the spread of blocks and effectively avoids the "last-block" problem in file sharing applications. Our simulations show that, AFAM achieves much less dissemination time than other protocols including BulletPrime and a direct implementation of BitTorrent for mobile environments.

In digital speech communication over noisy high packet loss rate wireless channels, improving the overall performance of the realtime speech coding and transmission system is of great importance. A novel joint speech coding and transmission algorithm is proposed by fully exploiting the correlation between speech coding, channel coding and the transmission process. The proposed algorithm requires no algorithm delay and less bandwidth expansion while greatly enhancing the error correcting performance and the reconstructed speech quality compared with conventional algorithms. Simulations show that the residual error rate is reduced by 84.36% and the MOS (Mean Opinion Score) is improved over 38.86%.

Task preemption is a critical mechanism for building an effective multi-tasking environment on dynamically reconfigurable processors. When a task is preempted, its necessary state information must be correctly preserved in order for the task to be resumed later. Not only do coarse-grained Dynamically Reconfigurable Processing Array (DRPAs) devices have different architectures using a variety of development tools, but the great amount of state data of hardware tasks executing on such devices are usually distributed on many different storage elements. To address these difficulties, this paper aims at studying a general method for capturing the state data of hardware tasks targeting coarse-grained DRPAs. Based on resource usage, algorithms for identifying preemption points and inserting preemption states subject to user-specified preemption latency are proposed. Moreover, a modification to automatically incorporate proposed steps into the system design flow is also discussed. The performance degradation caused by additional preemption states is minimized by allowing preemption only at predefined points where demanded resources are small. The evaluation result using a model based on NEC Electronics' DRP-1 shows that the proposed method can produce preemption points satisfying a given preemption latency with reasonable hardware overhead (from 6% to 15%).

Optical Burst Switched (OBS) networks are considered as promising candidates for the next generation network architecture which does not need high-speed switch technologies. In OBS networks, contention resolution is one of the significant problems. Generally, setup reservations are operated per burst in OBS networks. To transmit multiple successive bursts successfully, the effective wavelength reservation must be implemented and enhanced network performance must be realized. In the proposed method, when an optical burst is generated and its destination is the same as that of the preceding burst or the path until the destination includes the entire path of the preceding burst, the subsequent burst is assigned to the same wavelength as the preceding burst and transmitted sequentially. The main aim in the proposed method is the efficient use of wavelength resources and the reduction of burst loss probability. We simulate and evaluate the effectiveness of the proposed method. As a result, it is verified that the proposed method can reduce the burst loss probably.

In this paper, we analyze existing vulnerabilities in handover for mobile WiMAX networks. To overcome these vulnerabilities, we propose a secure handover protocol that guarantees mutual authentication and forward/backward secrecy in handover. We present a formal analysis of our protocol using a logic-based formal method.

With an enhanced client computer performance and network bandwidth, content distribution services are receiving much attention. However client/server model and peer-to-peer model require vast cost for content distributions. These costs pose an impediment to broaden commercialization of content distribution services via the Internet. Content distribution cost consists of investment for server and network infrastructure which client/server model and peer-to-peer model require respectively. Thus, We focus on network infrastructure, especially in peer-to-peer content distribution networks which drastically increase traffic volume. The main feature of our proposal is utilization of inexpensive inter-ISP connections. This paper presents methods to constitute peer-to-peer content distribution networks that realizes lower cost content distribution and a reduction in the amount of inter-ISP traffic and its costs by considering the priority in usage of ISP interconnections in its distribution. Our proposal extends BitTorrent, which has been widely deployed by several content providers to reduce the load in congested servers and the distribution costs. Our performance evaluations show that our proposal achieves a reduction in network infrastructure costs and improved performance such as distribution time.

This work proposes new features to improve the pathological voice quality classification performance. They are the means, the variances, and the perturbations of the higher-order statistics (HOS) such as the skewness and the kurtosis. The HOS-based features show meaningful differences among normal, grade 1, grade 2, and grade 3 voices classified in the GRBAS scale. The jitter, the shimmer, the harmonic-to-noise ratio (HNR), and the variance of the short-time energy are utilized as the conventional features. The performances are measured by the classification and regression tree (CART) method. Specifically, the CART-based method by utilizing both the conventional features and the HOS-based ones shows its effectiveness in the pathological voice quality measurement, with the classification accuracy of 87.8%.

This paper presents the design of a CMOS RF Power Detector (PD) using 0.18 µm standard CMOS technology. The PD is an improved unbalanced source coupled pair incorporating an output differential amplifier and sink current steering. It realizes an input detectable power range of -30 to -20 dBm over 0.1-1 GHz. Also it shows a maximum data rate of 30 Mbps with 2 pF output loading under OOK modulation. The overall current consumption is 1.9 mA under a 1.5 V supply.

With the popularity of BitTorrent-like P2P applications, improving its performance has been an active research area. Super-seeding, a special upload policy for the initial seeder, improves the efficiency in producing multiple seeds and reduces the uploading bytes of content initiators, thus being highly expected as a promising solution for improving downloading performance while decreasing uploading cost. However, the overall impacts of super seeding upon BitTorrent performance remain a question and have not been analyzed so far in literature. In this paper, we present an analytical and experimental study over the performance of super-seeding scheme. We attempt to answer the following questions: whether and how much super-seeding saves uploading cost, whether the overall downloading time is decreased by super-seeding, and in which circumstances super-seeding performs worse. Based on the seeding process, our analytical study gives formulas on the new piece distribution time, average downloading time and minimum distribution time for heterogeneous P2P file distribution system with super-seeding. Robust evidence supporting the use (or not) of super-seeding is given based on our worldwide Internet experiments over wide distribution of 250 PlanetLab nodes. With a well-designed experimental scenario, we study the overall download time and upload cost of super seeding scheme under varying seed bandwidth and peer behavior. Results show that super-seeding can save an upload ratio of 20% and does help speeding up swarms in certain modes. Tentative conclusions about the effectiveness of super-seeding and its optimal working circumstances are given with inside mechanism analyzed and negative factor identified. Our work not only provides reference for the potential adoption of super-seeding in BitTorrent and other P2P applications, but also much insights for the tussle of enhancing of Quality of Experience (QoE) and saving cost for a large-scale BitTorrent-like P2P commercial application.

In a hidden Markov model (HMM), state duration probabilities decrease exponentially with time, which fails to adequately represent the temporal structure of speech. One of the solutions to this problem is integrating state duration probability distributions explicitly into the HMM. This form is known as a hidden semi-Markov model (HSMM). However, though a number of attempts to use HSMMs in speech recognition systems have been proposed, they are not consistent because various approximations were used in both training and decoding. By avoiding these approximations using a generalized forward-backward algorithm, a context-dependent duration modeling technique and weighted finite-state transducers (WFSTs), we construct a fully consistent HSMM-based speech recognition system. In a speaker-dependent continuous speech recognition experiment, our system achieved about 9.1% relative error reduction over the corresponding HMM-based system.

In P2P content distribution systems, there are many cases in which the content can be classified into hierarchically organized categories. In this paper, we propose a hybrid overlay network design suitable for such content called Pastry/NSHCC (Pastry for Non-Strictly Hierarchically Categorized Content). The semantic information of classification hierarchies of the content can be utilized regardless of whether they are in a strict tree structure or not. By doing so, the search scope can be restrained to any granularity, and the number of query messages also decreases while maintaining keyword searching availability. Through simulation, we showed that the proposed method provides better performance and lower overhead than unstructured overlays exploiting the same semantic information.

In this paper, an efficient node-level target classification scheme in wireless sensor networks (WSNs) is proposed. It uses acoustic and seismic information, and its performance is verified by the classification accuracy of vehicles in a WSN. Because of the hard limitation in resources, parametric classifiers should be more preferable than non-parametric ones in WSN systems. As a parametric classifier, the Gaussian mixture model (GMM) algorithm not only shows good performances to classify targets in WSNs, but it also requires very few resources suitable to a sensor node. In addition, our sensor fusion method uses a decision tree, generated by the classification and regression tree (CART) algorithm, to improve the accuracy, so that the algorithm drives a considerable increase of the classification rate using less resources. Experimental results using a real dataset of WSN show that the proposed scheme shows a 94.10% classification rate and outperforms the k-nearest neighbors and the support vector machine.

We consider a time-division multiple access (TDMA) transmission scheme in MIMO broadcast channels. To cope with the fairness issue in heterogeneous networks with slow fading, an opportunistic scheduling algorithm based on the channel eigen-direction is investigated. In the system with sparse users, the mismatch between a random beamforming vector and the principle eigenvector of the channel incurs a throughput penalty. To reduce such a throughput loss, a multiple random beams selection (MRBS) scheme exploiting chordal distances is proposed. Two feedback schemes (unquantized or quantized chordal distances) are considered. The closed-form throughput expressions of the proposed schemes are derived.

In this paper, a new methodology to estimate the number of competing stations in an IEEE 802.11 network, is proposed. Due to the nonlinear nature of the measurement model, an iterative nonlinear filtering algorithm, called the Scaled Unscented Filter (SUF), is employed. The SUF can provide a superior alternative to nonlinear filtering than the conventional Extended Kalman Filter (EKF), since it avoids errors associated with linearization. This approach demonstrates both high accuracy in addition to prompt reactivity to changes in the network occupancy status. In particular, the proposed algorithm shows superior performance in non saturated conditions when compared to the EKF. Numerical results demonstrate that the proposed algorithm provides a more viable method for estimation of the number of competing stations in an IEEE 802.11 network, than estimators based on the EKF.

The application of Cumulative Decision Feedback (DF) technique for energy/complexity constrained Wireless Sensor Networks (WSN) is considered. Theoretical bit error probability and average rate of a BPSK modulated DF are derived together with PHY-MAC layers' energy efficiency model for DF and Forward Error Correction (FEC) techniques. Moreover, an empirical optimization, which in turn relies upon a low complexity SNR estimation method also derived in this letter, is applied to the DF technique in order to obtain maximum energy efficiency.

Transmit beamforming can exploit the spatial diversity afforded by multiple-input multiple-output (MIMO) systems with low complexity. To apply this technique in more practical systems with the constraint of limited feedback, codebook based beamforming and vector quantization technique have been considered in various papers. On the other hand, multi-user scheduling is able to achieve another form of diversity arising from the independence of fading for different users, however, has not been fully taken into account in existing codebook based beamforming schemes. In this letter, a multi-codebook based beamforming and scheduling scheme is proposed, which exploits both spatial diversity and multi-user diversity by switching the codebook for different resource blocks. Meanwhile, the multi-codebook design issue is addressed, the corresponding theoretical analysis is provided, and the performance gain of proposed scheme is simulated. Furthermore, the impacts of related parameters on the performance gain are also investigated.

In March, 2007, IEEE802.15.4a was standardized as a low-rate and low-power UWB system for sensor networks. In general, detection of the IEEE802.15.4a signal is considered to be difficult because of its low transmitting power density and low duty cycle. However, if detecting of the IEEE802.15.4a signal is available, it is possible to avoid interference issues both among the IEEE802.15.4a systems and between the 15.4a and other UWB systems. This letter proposes a simple detection method using non-coherent detectors. The possibility of detecting of the IEEE802.15.4a signal by proposal detection method was examined. By conducting experiments with an emulated 15.4a RF signal, the signal detection probability was examined, and 15.4a signal from the range of about 11 meters in the radius could be detected. From this observation, the CSMA/CA method with detecting the signal in 15.4a system may be applied for alternative access method for 15.4a systems.

This article presents an indoor positioning and communication platform, using fluorescent lights. We set up a practical implementation of a VLC (Visible Light Communication) system in a University building. To finalize this work, it is important that we analyze the properties of the reception signal, especially the length of the data string that can be received at different walking speed. In this paper, we present a model and a series of formulae for analyzing the relationship between positioning signal availability and other important parameters, such as sensor angle, walking speed, data transmission rate, etc. We report a series of real-life experiments using VLC system and compare the results with those generated by the formula. The outcome is an improved design for determination of the reception area with more than 97% accurate signals, and an optimal transmission data length, and transmission rate.

Since an FFT-based speech encryption system retains a considerable residual intelligibility, such as talk spurts and the original intonation in the encrypted speech, this makes it easy for eavesdroppers to deduce the information contents from the encrypted speech. In this letter, we propose a new technique based on the combination of an orthogonal frequency division multiplexing (OFDM) scheme and an appropriate QAM mapping method to remove the residual intelligibility from the encrypted speech by permuting several frequency components. In addition, the proposed OFDM-based speech encryption system needs only two FFT operations instead of the four required by the FFT-based speech encryption system. Simulation results are presented to show the effectiveness of this proposed technique.

In this paper, we proposed a novel entropy-based image watermarking method in wavelet domain. Unlike traditional entropy, we use the normalized energy instead of the probability which is called energy-based entropy (EBE). Based on EBE, the watermark can be embedded robustly and imperceptibly. In our proposed method, the wavelet-trees are grouped into super-trees. Then each super-tree is also divided into five sub-blocks. According to the watermark bit state, the EBE of each sub-block will be modified respectively. In an experiment, three images (Lenna, Goldhill and Peppers) are chosen for evaluating the performance. The PSNR of these watermarked images are 44.039, 43.51 and 43.67. Compared with Wang et al.[18], it greatly increases the PSNR, by about 5.8, 4.8 and 3.9 dB respectively. For the consideration of the capacity for embedding, the maximum number of watermark bits is also increased. The experimental results show that the proposed entropy-based watermarking method performs well in JPEG compression, filtering (Gaussian filter, median filter and sharpen) and geometrical attacks (pixel shift and rotation). In addition, it is also very robust to against the multiple watermark attack.