Due to the recent network service market trends, network infrastructure providers must make their network infrastructures tolerant of network service complexity and swift at providing new network services. To achieve this, we first make a design decision for the single domain network infrastructure in which we use network virtualization and separate the network service control and management from the network infrastructure and leave the resource connectivity control and management in the network infrastructure so that the infrastructure can maintain simplicity and the network service can become complex and be quickly provided. Along with the decision, we construct an architecture of the network infrastructure and a network management model. The management model defines a slice as being determined by abstracted resource requirements and restructures the roles and planes from the viewpoint of network infrastructure usability so that network service requesters can manage network resources freely and swiftly in an abstract manner within the authorities the network infrastructure operator provides. We give the details of our design and implementation for a network virtualization management system along with the model. We deployed and evaluated our designed and implemented management system on the Japan national R&E testbed (JGN-X) to confirm the feasibility of our management system design and discuss room for improvement in terms of response time and scalability towards practical use. We also investigated certain cases of sophisticated network functions to confirm that the infrastructure can accept these functions without having to be modified.

This paper studies mapping techniques of multiple applications on embedded many-core SoCs. The mapping techniques proposed in this paper are static which means the mapping is decided at design time. The mapping techniques take into account both inter-application and intra-application parallelism in order to fully utilize the potential parallelism of the many-core architecture. Additionally, the proposed static mapping supports dynamic application switching, which means the applications mapped onto the same cores are switched to each other at runtime. Two approaches are proposed for static mapping: one approach is based on integer linear programming and the other is based on a greedy algorithm. Experimental results show the effectiveness of the proposed techniques.

This study presents a proposal for space-saving design of built-in antennas for handset terminals based on the concept of requisite design antenna volume. By investigating the relation between antenna input characteristic and electric near-field around the antenna element and surrounding components inside the terminal, and then evaluating the requisite design antenna volume, we propose the most effective deployment for both the antenna and surrounding components. The results show that our simple proposal can help reduced, by about 17% and 31.75%, the space that the antenna element actually requires at least for stable operation inside the terminal, in the single-band designs for the cellular 2GHz band (1920-2170MHz) and 800MHz band (830-880MHz), respectively. In the dual-band design, we verify that it can reduce, the antenna space by about 35.18%, and completely cover the two above cellular bands with good antenna performance.

With the increase of the number of wireless sensing or metering devices, the collection of sensing data using wireless communication becomes an important part of a smart grid system. Cognitive radio technology can be used to facilitate the deployment of smart grid systems. In this paper, we propose a data collection and dissemination framework for cognitive radio smart grid systems to fully utilize wireless resources while maintaining a reliably connected and efficient topology for each channel. In the proposed framework, each sensor node selects a channel considering the primary user (PU) channel utilization and network connectivity. In this way, the data collection and dissemination can be performed with a high reliability and short delay while avoiding a harmful effect on primary users. We use computer simulations to evaluate the proposed framework.

Much attention has recently been paid to direction of arrival (DOA) estimation using compressed sensing (CS) techniques, which are sparse signal reconstruction methods. In our previous study, we developed a method for estimating the DOAs of multi-band signals that uses CS processing and that is based on the assumption that incident signals have the same complex amplitudes in all the bands. That method has a higher probability of correct estimation than a single-band DOA estimation method using CS. In this paper, we propose novel DOA estimation methods for multi-band signals with frequency characteristics using the Khatri-Rao product. First, we formulate a method that can estimate DOAs of multi-band signals whose phases alone have frequency dependence. Second, we extend the scheme in such a way that we can estimate DOAs of multi-band signals whose amplitudes and phases both depend on frequency. Finally, we evaluate the performance of the proposed methods through computer simulations and reveal the improvement in estimation performance.

In dense femtocell networks (DFNs), one of the main issues is interference management since interference between femtocell access points (FAPs) reduces the system performance significantly. Further, FAPs serve different numbers of femtocell user equipments (FUEs), i.e., some FAPs have more than one FUE while others have one or no FUEs. Therefore, for DFNs, an intelligent channel assignment scheme is necessary considering both the number of FUEs connected to the same FAPs and interference mitigation to improve system performance. This paper proposes a two-stage dynamic channel assignment (TS-DCA) scheme for downlink DFNs based on orthogonal frequency division multiple access/frequency division duplex (OFDMA/FDD). In stage 1, using graph coloring algorithm, a femtocell gateway (FGW) first groups FUEs based on an interference graph that considers different numbers of FUEs per FAP. Then, in stage 2, the FGW dynamically assigns subchannels to FUE clusters according to the order of maximum capacity of FAP clusters. In addition, FAPs adaptively assign remaining subchannels in FUE clusters to their FUEs in other FUE clusters. Through simulations, we first find optimum parameters of the FUE clustering to maximize the system capacity and then evaluate system performance in terms of the mean FUE capacity, unsatisfied FUE probability, and mean FAP transmission energy consumption according to the different numbers of FUEs and FAPs with a given FUE traffic load.

To enhance the throughput of wireless local area networks (WLANs) by efficiently utilizing the radio resource, a distributed coordination function-based (DCF-based) orthogonal frequency division multiple access (OFDMA) WLAN system has been proposed. In the system, since each OFDMA sub-channel is assigned to the associated station with the highest channel gain, the transmission rate of DATA frames can be enhanced thanks to multi-user diversity. However, the optimum allocation of OFDMA sub-channels requires the estimation of channel state information (CSI) of all associated stations, and this incurs excessive signaling overhead. As the number of associated stations increases, the signaling overhead severely degrades the throughput of DCF-based OFDMA WLAN. To reduce the signaling overhead while obtaining a sufficient diversity gain, this paper proposes a channel access scheme that performs multiple DCF-based channel access. The key idea of the proposed scheme is to introduce additional DCF-based prioritized access along with the traditional DCF-based random access. In the additional DCF-based prioritized access, by dynamically adjusting contention window size according to the CSI of each station, only the stations with better channel state inform their CSI to the access point (AP), and the signaling overhead can be reduced while maintaining high multi-user diversity gain. Numerical results confirm that the proposed channel access scheme enhances the throughput of OFDMA WLAN.

This paper proposes low-power voltage-mode/current-mode hybrid circuits to realize an arbitrary two-variable logic function and a full-adder function. The voltage and current mode can be selected for low-power operations at low and high frequency, respectively, according to speed requirement. An nMOS pass transistor network is shared to realize voltage switching and current steering for the voltage- and current-mode operations, respectively, which leads to high utilization of the hardware resources. As a result, when the operating frequency is more than 1.15,GHz, the current mode of the hybrid logic circuit is more power-efficient than the voltage mode. Otherwise, the voltage mode is more power-efficient. The power consumption of the hybrid two-variable logic circuit is lower than that of the conventional two-input look-up table (LUT) using CMOS transmission gates, when the operating frequency is more than 800,MHz. The delay and area of the hybrid two-variable logic circuit are increased by only 7% and 13%, respectively

This paper analyzes the transmission performances of visible light communication (VLC) based on unipolar orthogonal frequency division multiplexing (OFDM), which is compatible with intensity modulation and direct detection (IM/DD). Three existing unipolar OFDM schemes, namely DC biased optical OFDM (DCO-OFDM), asymmetrically clipped optical OFDM (ACO-OFDM), and flip-OFDM are investigated and compared. While these three schemes have been analyzed for indoor optical wireless communication (OWC) subject to the limitation on the transmit optical power, they have not been carefully investigated and compared for VLC when a large transmit power is available due to the illumination requirement, and the signal dynamic range (DR) becomes the main limitation. For the analysis, DR expressions of DCO-OFDM, ACO-OFDM, and flip-OFDM signals are first derived. Then, the bit error rate (BER) expression of each unipolar OFDM scheme is derived in terms of the DR. For data rates in the range of 1-10Mbps, under the system parameters based on typical indoor environments, DCO-OFDM is observed to outperform the other two schemes. This superiority of DCO-OFDM is in contrast with previously reported results that indicate the attractiveness of ACO-OFDM and flip-OFDM over DCO-OFDM when the transmit optical power is the main limitation. Finally, light dimming is considered to identify the illumination level below which DCO-OFDM loses this superiority.

According to the match-degree between lightpaths, an HC-sharing approach is proposed to assign wavelength for an arriving transmission request for dynamic traffic in LOBS-based datacenter networks. The simulation results demonstrate that the proposed approach can provide lower block probability than other approaches for both unicast and multicast transmissions.

Internet traffic classification is an essential step for stable service provision. The payload signature classifier is considered a reliable method for Internet traffic classification but is prohibitively computationally expensive for real-time handling of large amounts of traffic on high-speed networks. In this paper, we describe several design techniques to minimize the search space of traffic classification and improve the processing speed of the payload signature classifier. Our suggestions are (1) selective matching algorithms based on signature type, (2) signature reorganization using hierarchical structure and traffic locality, and (3) early packet sampling in flow. Each can be applied individually, or in any combination in sequence. The feasibility of our selections is proved via experimental evaluation on traffic traces of our campus and a commercial ISP. We observe 2 to 5 times improvement in processing speed against the untuned classification system and Snort Engine, while maintaining the same level of accuracy.

The data rate of VLSI interconnections has been increasing according to the demand for high-speed operation of semiconductors such as CPUs. To realize high performance VLSI systems, high-speed data communication has become an important factor. However, at high-speed data rates, it is difficult to achieve accurate communication without bit errors because of inter-symbol interference (ISI). This paper presents high-speed data communication techniques for VLSI systems using Tomlinson-Harashima Precoding (THP). Since THP can eliminate the ISI with limiting average and peak power of transmitter signaling, THP is suitable for implementing advanced low-voltage VLSI systems. In this paper, 4-PAM (Pulse amplitude modulation) with THP has been employed to achieve high-speed data communication in VLSI systems. Simulation results show that THP can remove the ISI without increasing peak and average power of a transmitter. Moreover, simulation results clarify that multiple-valued data communication is very effective to reduce implementation costs for realizing high-speed serial links.

We propose a new algorithm to suppress both stationary background noise and nonstationary directional interference noise in a speech enhancement system that employs the generalized sidelobe canceller. Our approach builds on advances in generalized sidelobe canceller design involving the transfer function ratio. Our system is composed of three stages. The first stage estimates the transfer function ratio on the acoustic path, from the nonstationary directional interference noise source to the microphones, and the powers of the stationary background noise components. Secondly, the estimated powers of the stationary background noise components are used to execute spectral subtraction with respect to input signals. Finally, the estimated transfer function ratio is used for speech enhancement on the primary channel, and an adaptive filter reduces the residual correlated noise components of the signal. These algorithmic improvements give consistently better performance than the transfer function generalized sidelobe canceller when input signal-to-noise ratio is 10 dB or lower.

In this paper, a new analog signal transmission technique called analog single-carrier transmission with frequency-domain equalization (analog SC-FDE) is proposed. Analog SC-FDE applies discrete Fourier transform (DFT), frequency-domain spectrum shaping and mapping, inverse DFT (IDFT), and cyclic prefix (CP) insertion before transmission. At the receiver, one-tap FDE is applied to take advantage of frequency diversity. This paper considers, as an example, analog voice transmission. A theoretical analysis of the normalized mean square error (NMSE) performance is carried out to evaluate the transmission property of the proposed analog SC-FDE and is confirmed by computer simulation. We show that analog SC-FDE achieves better NMSE performance than conventional analog signal transmission scheme.

A novel Two-dimensional Fuzzy Discriminant Locality Preserving Projections (2D-FDLPP) algorithm is proposed for learning effective subspace of two-dimensional images. The 2D-FDLPP algorithm is derived from the Two-dimensional Locality Preserving Projections (2D-LPP) by exploiting both fuzzy and discriminant properties. 2D-FDLPP algorithm preserves the relationship degree of each sample belonging to given classes with fuzzy k-nearest neighbor classifier. Also, it introduces between-class scatter constrain and label information into 2D-LPP algorithm. 2D-FDLPP algorithm finds the subspace which can best discriminate different pattern classes and weakens the environment factors according to soft assignment method. Therefore, 2D-FDLPP algorithm has more discriminant power than 2D-LPP, and is more suitable for recognition tasks. Experiments are conducted on the MNIST database for handwritten image classification, the JAFFE database and Cohn-Kanade database for facial expression recognition and the ORL database for face recognition. Experimental results reported the effectiveness of our proposed algorithm.

The aim of this study is to present electrooculogram signals that can be used for human computer interface efficiently. Establishing an efficient alternative channel for communication without overt speech and hand movements is important to increase the quality of life for patients suffering from Amyotrophic Lateral Sclerosis or other illnesses that prevent correct limb and facial muscular responses. In this paper, we introduce the gaze estimation system of electrooculogram signals. Using this system, the electrooculogram signals can be recorded when the patients focused on each direct. All these recorded signals could be analyzed using math-method and the mathematical model will be set up. Gaze estimation can be recognized using electrooculogram signals follow these models.

In this paper, we propose a novel method for road sign detection and recognition in complex scene real world images. Our algorithm consists of four basic steps. First, we employ a regional contrast based bottom-up visual saliency method to highlight the traffic sign regions, which usually have dominant color contrast against the background. Second, each type of traffic sign has special color distribution, which can be explored by top-down visual saliency to enhance the detection precision and to classify traffic signs into different categories. A bag-of-words (BoW) model and a color name descriptor are employed to compute the special-class distribution. Third, the candidate road sign blobs are extracted from the final saliency map, which are generated by combining the bottom-up and the top-down saliency maps. Last, the color and shape cues are fused in the BoW model to express blobs, and a support vector machine is employed to recognize road signs. Experiments on real world images show a high success rate and a low false hit rate and demonstrate that the proposed framework is applicable to prohibition, warning and obligation signs. Additionally, our method can be applied to achromatic signs without extra processing.

A directional array radiator is presented, the aim of which is to enhance the sound of the television in a particular direction and hence provide a volume boost to improve speech intelligibility for the hard of hearing. The sound radiated by the array in other directions is kept low, so as not to increase the reverberant level of sound in the listening room. The array uses 32 loudspeakers, each of which are in phase-shift enclosures to generate hypercardioid directivity, which reduces the radiation from the back of the array. The loudspeakers are arranged in 8 sets of 4 loudspeakers, each set being driven by the same signal and stacked vertically, to improve the directivity in this plane. This creates a 3D beamformer that only needs 8 digital filters to be made superdirective. The performance is assessed by means of simulations and measurements in anechoic and reverberant environments. The results show how the array obtains a high directivity in a reverberant environment.

We propose a method for finding an appropriate setting of a pay-per-performance payment system to prevent participation of insincere workers in crowdsourcing. Crowdsourcing enables fast and low-cost accomplishment of tasks; however, insincere workers prevent the task requester from obtaining high-quality results. Instead of a fixed payment system, the pay-per-performance payment system is promising for excluding insincere workers. However, it is difficult to learn what settings are better, and a naive payment setting may cause unsatisfactory outcomes. To overcome these drawbacks, we propose a method for calculating the expected payments for sincere and insincere workers, and then clarifying the conditions in the payment setting in which sincere workers are willing to choose a task, while insincere workers are not willing to choose the task. We evaluated the proposed method by conducting several experiments on tweet labeling tasks in Amazon Mechanical Turk. The results suggest that the pay-per-performance system is useful for preventing participation of insincere workers.

We discuss a new high performance computing service (HPCS) platform that has been developed to provide domain-neutral computing service under the governmental support from “EDucation-research Integration through Simulation On the Net” (EDISON) project. With a first focus on technical features, we not only present in-depth explanations of the implementation details, but also describe the strengths of the EDISON platform against the successful nanoHUB.org gateway. To validate the performance and utility of the platform, we provide benchmarking results for the resource virtualization framework, and prove the stability and promptness of the EDISON platform in processing simulation requests by analyzing several statistical datasets obtained from a three-month trial service in the initiative area of computational nanoelectronics. We firmly believe that this work provides a good opportunity for understanding the science gateway project ongoing for the first time in Republic of Korea, and that the technical details presented here can be served as an useful guideline for any potential designs of HPCS platforms.