In this paper, a self optimization beamforming null control (SOBNC) scheme is proposed. There is a need of maintaining signal to interference plus noise ratio (SINR) threshold to control modulation and coding schemes (MCS) in recent technologies like Wi-Fi, Long Term Evolution (LTE) and Long Term Evolution Advanced (LTE-A). Selection of MCS depends on the SINR threshold that allows maintaining key performance index (KPI) like block error rate (BLER), bit error rate (BER) and throughput at certain level. The SOBNC is used to control the antenna pattern for SINR estimation and improve the SINR performance of the wireless communication systems. The nulling comes with a price; if wider nulls are introduced, i.e. more number of nulls are used, the 3dB beam-width and peak side lobe level (SLL) in antenna pattern changes critically. This paper proposes a method which automatically controls the number of nulls in the antenna pattern as per the changing environment based on adaptive-network based fuzzy interference system (ANFIS) to maintain output SINR level higher or equal to the required threshold. Finally, simulation results show a performance superiority of the proposed SOBNC compared with minimum mean square error (MMSE) based adaptive nulling control algorithm and conventional fixed null scheme.

Ever-evolving malware makes it difficult to prevent it from infecting hosts. Botnets in particular are one of the most serious threats to cyber security, since they consist of a lot of malware-infected hosts. Many countermeasures against malware infection, such as generating network-based signatures or templates, have been investigated. Such templates are designed to introduce regular expressions to detect polymorphic attacks conducted by attackers. A potential problem with such templates, however, is that they sometimes falsely regard benign communications as malicious, resulting in false positives, due to an inherent aspect of regular expressions. Since the cost of responding to malware infection is quite high, the number of false positives should be kept to a minimum. Therefore, we propose a system to generate templates that cause fewer false positives than a conventional system in order to achieve more accurate detection of malware-infected hosts. We focused on the key idea that malicious infrastructures, such as malware samples or command and control, tend to be reused instead of created from scratch. Our research verifies this idea and proposes here a new system to profile the variability of substrings in HTTP requests, which makes it possible to identify invariable keywords based on the same malicious infrastructures and to generate more accurate templates. The results of implementing our system and validating it using real traffic data indicate that it reduced false positives by up to two-thirds compared to the conventional system and even increased the detection rate of infected hosts.

Because accurate position information plays an important role in wireless sensor networks (WSNs), target localization has attracted considerable attention in recent years. In this paper, based on target spatial domain discretion, the target localization problem is formulated as a sparsity-seeking problem that can be solved by the compressed sensing (CS) technique. To satisfy the robust recovery condition called restricted isometry property (RIP) for CS theory requirement, an orthogonalization preprocessing method named LU (lower triangular matrix, unitary matrix) decomposition is utilized to ensure the observation matrix obeys the RIP. In addition, from the viewpoint of the positioning systems, taking advantage of the joint posterior distribution of model parameters that approximate the sparse prior knowledge of target, the sparse Bayesian learning (SBL) approach is utilized to improve the positioning performance. Simulation results illustrate that the proposed algorithm has higher positioning accuracy in multi-target scenarios than existing algorithms.

The random deployment of small cell base stations (BSs) causes the coverage areas of neighboring cells to overlap, which increases intercell interference and degrades the system capacity. This paper proposes a new intercell interference management (IIM) scheme to improve the system capacity in multiple-input multiple-output (MIMO) small cell networks. The proposed IIM scheme consists of both an interference cancellation (IC) technique on the receiver side, and a neural network (NN) based power control algorithm for intercell interference coordination (ICIC) on the transmitter side. In order to improve the system capacity, the NN power control optimizes downlink transmit power while IC eliminates interfering signals from received signals. Computer simulations compare the system capacity of the MIMO network with several ICIC algorithms: the NN, the greedy search, the belief propagation (BP), the distributed pricing (DP), and the maximum power, all of which can be combined with IC reception. Furthermore, this paper investigates the application of a multi-layered NN structure called deep learning and its pre-training scheme, into the mobile communication field. It is shown that the performance of NN is better than that of BP and very close to that of greedy search. The low complexity of the NN algorithm makes it suitable for IIM. It is also demonstrated that combining IC and sectorization of BSs acquires high capacity gain owing to reduced interference.

In this paper, we present a faster (wall-clock time) sorting method for numerical data subjected to fully homomorphic encryption (FHE). Owing to circuit-based construction and the FHE security property, most existing sorting methods cannot be applied to encrypted data without significantly compromising efficiency. The proposed algorithm utilizes the cryptographic single-instruction multiple-data (SIMD) operation, which is supported by most existing FHE algorithms, to reduce the computational overhead. We conducted a careful analysis of the number of required recryption operations, which are the computationally dominant operations in FHE. Accordingly, we verified that the proposed SIMD-based sorting algorithm completes the given task more quickly than existing sorting methods if the number of data items and (or) the maximum bit length of each data item exceed specific thresholds.

There is a strong demand to enjoy broadband and stable Internet connectivity not only in office and the home but also in high-speed train. Several systems are providing high-speed train with Internet connectivity using various technologies such as leaky coaxial cable (LCX), Wi-Fi, and WiMAX. However, their actual throughputs are less than 2Mbps. We developed a free-space optical (FSO) communication transceiver called LaserTrainComm2014 that achieves the throughput of 1 Gbps between the ground and a train. LaserTrainComm2014 employs a high-speed image sensor for coarse tracking and a quadrant photo-diode (QPD) for accurate tracking. Since the image captured by the high-speed image sensor has several types of noise, image processing is necessary to detect the beacon light of the other LaserTrainComm2014. As a result of field experiments in a vehicle test course, LaserTrainComm2014 achieves handover time of 21 milliseconds (ms) in the link layer at the speed of 60km/h. Even if the network layer signaling takes time of 10 milliseconds, the total communication disruption time due to handover is short enough to provide passengers with Internet connectivity for live streaming Internet applications such as YouTube, Internet Radio, and Skype.

GitHub is a developers' social networking service that hosts a great number of open source software (OSS) projects. Although some of the hosted projects are growing and have many developers, most projects are organized by a few developers and face difficulties in terms of sustainability. OSS projects depend mainly on volunteer developers, and attracting and retaining these volunteers are major concerns of the project stakeholders. To investigate the population structures of OSS development communities in detail and conduct software analytics to obtain actionable information, we apply a demographic approach. Demography is the scientific study of population and seeks to identify the levels and trends in the size and components of a population. This paper presents a case study, investigating the characteristics of the population structures of OSS projects on GitHub, and shows population projections generated with the well-known cohort component method. We found that there are four types of population structures in OSS development communities in terms of experiences and contributions. In addition, we projected the future population accurately using a cohort component population projection method. This method predicts a population of the next period using a survival rate calculated from past population. To the best of our knowledge, this is the first study that applied demography to the field of OSS research. Our approach addressing OSS-related problems based on demography will bring new insights, since studying population is novel in OSS research. Understanding current and future structures of OSS projects can help practitioners to monitor a project, gain awareness of what is happening, manage risks, and evaluate past decisions.

The likelihood-ratio based score level fusion (LR-based fusion) scheme has attracted much attention, since it maximizes accuracy if a log-likelihood ratio (LLR) is accurately estimated. In reality, it can happen that a user cannot input some query samples due to temporary physical conditions such as injuries and illness. It can also happen that some modalities tend to cause false rejection (i.e. the user is a “goat” for these modalities). The LR-based fusion scheme can handle these situations by setting LLRs corresponding to missing query samples to 0. In this paper, we refer to such a mode as a “modality selection mode”, and address an issue of accuracy in this mode. Specifically, we provide the following contributions: (1) We firstly propose a “modality selection attack”, in which an impostor inputs only query samples whose LLRs are more than 0 (i.e. takes an optimal strategy) to impersonate others. We also show that the impostor can perform this attack against the SPRT (Sequential Probability Ratio Test)-based fusion scheme, which is an extension of the LR-based fusion scheme to a sequential fusion scenario. (2) We secondly consider the case when both genuine users and impostors take this optimal strategy, and show that the overall accuracy in this case is “worse” than the case when they input all query samples. More specifically, we prove that the KL (Kullback-Leibler) divergence between a genuine distribution of integrated scores and an impostor's one, which can be compared with password entropy, is smaller in the former case. We also show to what extent the KL divergence losses for each modality. (3) We finally evaluate to what extent the overall accuracy becomes worse using the NIST BSSR1 Set 2 and Set 3 datasets, and discuss directions of multibiometric applications based on the experimental results.

In this paper, we study the impact of imperfect channel information on an amplify-and-forward (AF)-based two-way relaying network (TWRN) with adaptive modulation which consists of two end-terminals and multiple relays. Specifically, we consider a single-relay selection scheme of the TWRN in the presence of outdated channel state information (CSI) and channel estimation errors. First, we choose the best relay based on outdated CSI, and perform adaptive modulation on both relaying paths with channel estimation errors. Then, we discuss the impact of the outdated CSI on the statistics of the signal-to-noise ratio (SNR) per hop. In addition, we formulate the end-to-end SNRs with channel estimation errors and offer statistic analyses in the presence of both the outdated CSI and channel estimation errors. Finally, we provide the performance analyses of the proposed TWRN with adaptive modulation in terms of average spectral efficiency, average bit error rate, and outage probability. Numerical examples are given to verify our obtained analytical results for various system conditions.

Coordinate interleaved orthogonal design (CIOD) using four transmit antennas provides full diversity, full rate (FDFR) properties with low decoding complexity. However, the constellation expansion due to the coordinate interleaving of the rotated constellation results in peak to average power ratio (PAPR) increase. In this paper, we propose two signal constellation design methods which have low PAPR. In the first method we propose a signal constellation by properly selecting the signal points among the expanded square QAM constellation points, based on the co-prime interleaving of the first coordinate signal. We design a regular interleaving pattern so that the coordinate distance product (CPD) after the interleaving becomes large to get the additional coding gain. In the other method we propose a novel constellation with low PAPR based on the clipping of the rotated square QAM constellation. Our proposed signal constellations show much lower PAPR than the ordinary rotated QAM constellations for CIOD.

We propose a multi-label feature selection method that considers feature dependencies. The proposed method circumvents the prohibitive computations by using a low-rank approximation method. The empirical results acquired by applying the proposed method to several multi-label datasets demonstrate that its performance is comparable to those of recent multi-label feature selection methods and that it reduces the computation time.

The Virtual Machine Consolidation (VMC) algorithm is the core strategy of virtualization resource management software. In general, VMC efficiency dictates cloud datacenter efficiency to a great extent. However, all the current Virtual Machine (VM) consolidation strategies, including the Iterative Correlation Match Algorithm (ICMA), are not suitable for the dynamic VM consolidation of the level of physical servers in actual datacenter environments. In this paper, we propose two VM consolidation and placement strategies which are called standard Segmentation Iteration Correlation Combination (standard SICC) and Multi-level Segmentation Iteration Correlation Combination (multi-level SICC). The standard SICC is suitable for the single-size VM consolidation environment and is the cornerstone of multi-level SICC which is suitable for the multi-size VM consolidation environment. Numerical simulation results indicate that the numbers of remaining Consolidated VM (CVM), which are generated by standard SICC, are 20% less than the corresponding parameters of ICMA in the single-level VM environment with the given initial condition. The numbers of remaining CVMs of multi-level SICC are 14% less than the corresponding parameters of ICMA in the multi-level VM environment. Furthermore, the used physical servers of multi-level SICC are also 5% less than the used servers of ICMA under the given initial condition.

Given the rapid development of current wireless communication systems has led to two major challenges: energy conservation and interference avoidance. Addressing these challenges is critical for sustaining modern green communications. This paper proposes two energy-efficient schemes for a heterogeneous network environment. The schemes include a cell switching strategy and a power control technique. The proposed schemes can save energy while maintaining the service quality for users. Simulation results showed that compared with conventional schemes, the proposed schemes reduced energy consumption by up to 18% more and further enhanced the system energy efficiency by up to 22% without using any switch-off procedure.

In this paper, we propose a channel-unaware algorithm to suppress the narrowband interference (NBI) for the time synchronization, where multiple antennas are equipped at the receiver. Based on the fact that the characteristics of synchronization signal are different from those of NBI in both the time and spatial domain, the proposed algorithm suppresses the NBI by utilizing the multiple receive antennas in the eigen domain of NBI, where the eigen domain is obtained from the time domain statistical information of NBI. Because time synchronization involves incoherent detection, the proposed algorithm does not use the desired channel information, which is different from the eigen domain interference rejection combining (E-IRC). Simulation results show, compared with the traditional frequency domain NBI suppression technique, the proposed algorithm has about a 2 dB gain under the same probability of detection.

Quantum key distribution (QKD), a cryptography technology providing information theoretic security based on physical laws, has moved from the research stage to the engineering stage. Although the communication distance is subject to a limitation attributable to the QKD fundamentals, recent research and development of “key relaying” over a “QKD network” is overcoming this limitation. However, there are still barriers to widespread use of QKD integrated with conventional information systems: applicability and development cost. In order to break down these barriers, this paper proposes a new solution for developing secure network infrastructure based on QKD technology to accommodate multiple applications. The proposed solution introduces 3 functions: (1) a directory mechanism to manage multiple applications hosted on the QKD network, (2) a key management method to share and to allocate the keys for multiple applications, and (3) a cryptography communication library enabling existing cryptographic communication software to be ported to the QKD network easily. The proposed solution allows the QKD network to accommodate multiple applications of various types, and moreover, realizes applicability to conventional information systems easily. It also contributes to a reduction in the development cost per information system, since the development cost of the QKD network can be shared between the multiple applications. The proposed solution was implemented with a network emulating QKD technology and evaluated. The evaluation results show that the proposed solution enables the infrastructure of a single QKD network to host multiple applications concurrently, fairly, and effectively through a conventional application programming interface, OpenSSL API. In addition, the overhead of secure session establishment by the proposed solution was quantitatively evaluated and compared.

As dual-polarized multiple-input multiple-output (MIMO) technique has little inter-antenna interference, it provides high data rate and reliability to a user equipment (UE) with the low system complexity. In the joint transmission (JT) technique of the coordinated multi-point (CoMP) transmission system, multiple transmission points (TPs) transmit the same data to the UE so that the UE can get the diversity gain and the high reliability, especially at the cell-edge. However, the system performance of the dual-polarized MIMO in the JT technique of CoMP system is very sensitive on the dual-polarized channel state when the channel is asymmetric. In this letter, an improved dual-polarized MIMO scheme for JT of the downlink CoMP transmission system is proposed. This scheme adaptively applies the transmission power to each dual-polarized MIMO antenna and the modulation order of the transmission data according to the channel state information (CSI). System-level simulation results show that the proposed scheme provides better bit-error-rate (BER) performance in the asymmetric dual-polarized channel state than the conventional scheme.

This paper presents the design of a multiple-standard 1080 high definition (HD) video decoder on a mixed-grained reconfigurable computing platform integrating coarse-grained reconfigurable processing units (RPUs) and FPGAs. The proposed RPU, including 16×16 multi-functional processing elements (PEs), is used to accelerate compute-intensive tasks in the video decoding. A soft-core-based microprocessor array is implemented on the FPGA and adopted to speed-up the dynamic reconfiguration of the RPU. Furthermore, a mail-box-based communication scheme is utilized to improve the communication efficiency between RPUs and FPGAs. By exploiting dynamic reconfiguration of the RPUs and static reconfiguration of the FPGAs, the proposed platform achieves scalable performances and cost trade-offs to support a variety of video coding standards, including MPEG-2, AVS, H.264, and HEVC. The measured results show that the proposed platform can support H.264 1080 HD video streams at up to 57 frames per second (fps) and HEVC 1080 HD video streams at up to 52fps under 250MHz, at the same time, it achieves a 3.6× performance gain over an industrial coarse-grained reconfigurable processor for H.264 decoding, and a 6.43× performance boosts over a general purpose processor based implementation for HEVC decoding.

In order to minimize packet error rate in extremely dynamic vehicular networks, a novel vehicle to vehicle (V2V) mobile content transmission scheme that jointly employs random network coding and shuffling/scattering techniques is proposed in this paper. The proposed scheme consists of 3 steps: Step 1-The original mobile content data consisting of several packets is encoded to generate encoded blocks using random network coding for efficient error recovery. Step 2-The encoded blocks are shuffled for averaging the error rate among the encoded blocks. Step 3-The shuffled blocks are scattered at different vehicle locations to overcome the estimation error of optimum transmission location. Applying the proposed scheme in vehicular networks can yield error free transmission with high efficiency. Our simulation results corroborate that the proposed scheme significantly improves the packet error rate performance in high mobility environments. Thanks to the flexibility of network coding, the proposed scheme can be designed as a separate module in the physical layer of various wireless access technologies.

Named Data Networking (NDN) is a proposed future Internet architecture that shifts the fundamental abstraction of the network from host-to-host communication to request-response for named, signed data-an information dissemination focused approach. This paper describes a general design for receiver-driven, real-time streaming data (RTSD) applications over the current NDN implementation that aims to take advantage of the architecture's unique affordances. It is based on experimental development and testing of running code for real-time video conferencing, a positional tracking system for interactive multimedia, and a distributed control system for live performance. The design includes initial approaches to minimizing latency, managing buffer size and Interest retransmission, and adapting retrieval to maximize bandwidth and control congestion. Initial implementations of these approaches are evaluated for functionality and performance results, and the potential for future research in this area, and improved performance as new features of the architecture become available, is discussed.

We have investigated PtHf silicide formation utilizing a developed PtHf-alloy target to realize low contact resistivity for the first time. A 20 nm-thick PtHf-alloy thin film was deposited on the n-Si(100) by RF magnetron sputtering at room temperature. Then, silicidation was carried out by rapid thermal annealing (RTA) system at 450-600°C/5 min in N2/4.9%H2 ambient. The PtHf-alloy silcide, PtHfSi, layers were successfully formed, and the Schottky barrier height (SBH) for electron of 0.45 eV was obtained by 450°C silicidation. Furthermore, low contact resistivity was achieved for fabricated PtHSi such as 8.4x10-8 Ωcm2 evaluated by cross-bridge Kelvin resistor (CBKR) method.