Due to the increasing demand for 3D video transmission over wireless networks, managing the quality of experience (QoE) of wireless 3D video clients is becoming increasingly important. However, the variability of compressed 3D video bit streams and the wireless channel condition as well as the complexity of 3D video viewing experience assessment make it difficult to properly allocate wireless transmission resources. In this paper, we discuss the characteristics of H.264 3D videos and QoE assessment of 3D video clients, and further propose a transmission scheme for 3D video transmission over a wireless communication system. The purpose of our scheme is to minimize the average ratio of stalls among all video streaming clients. By taking into account the playout lead and its change, we periodically evaluate the degree of urgency of each client as regards bitstream receipt based on fuzzy logic, and then allocate the transmission resource blocks to clients jointly considering their degrees of urgency and channel conditions. The adaptive modulation and coding scheme (MCS) is applied to ensure a low transmission error rate. Our proposed scheme is suitable for practical implementation since it has low complexity, and can be easily applied in 2D video transmission and in non-OFDM systems. Simulation results, based on three left-and-right-views 3D videos and the Long Term Evolution (LTE) system, demonstrate the validity of our proposed scheme.

We address the problem of entity identification on a microblog with special attention to indirect reference cases in which entities are not referred to by their names. Most studies on identifying entities referred to them by their full/partial name or abbreviation, while there are many indirectly mentioned entities in microblogs, which are difficult to identify in short text such as microblogs. We therefore tackled indirect reference cases by developing features that are particularly important for certain types of indirect references and modeling dependency among referred entities by a Conditional Random Field (CRF) model. In addition, we model non-sequential order dependency while keeping the inference tractable by dynamically building dependency among entities. The experimental results suggest that our features were effective for indirect references, and our CRF model with adaptive dependency was robust even when there were multiple mentions in a microblog and achieved the same high performance as that with the fully connected CRF model.

Recently, Doppler radars have been used in various applications from the detection and the classification of indoor human activities to the detection of airplanes. To improve both the degrees of freedom (DOF) and the estimation accuracy of the direction-of-arrival (DOA) of targets, multiple-input multiple-output (MIMO) radar has received much attention in recent years. The temporal spatial virtual array based on Doppler shift of a moving target has been one of methods to improve DOA estimation accuracy. However, the DOA estimation accuracy based on the method depends on the velocity and the direction of the target on which we focus. Also, the temporal spatial virtual array should be generated based on the information of the single target. Thus, it is difficult to implement the method if there are multiple targets. In this paper, we propose a new method that provides high accuracy of DOA estimation by using the temporal spatial virtual array without dependence on the velocity, the direction and the number of existing targets. We demonstrate the DOA estimation accuracy and the effectiveness of the proposed method via simulations.

We propose a system named ETIS (Energy-based Tree Illustration System) for automatically generating tree illustrations characteristic of two-dimensional ones with features such as exaggerated branch curves, leaves, and flowers. The growth behavior of the trees can be controlled by adjusting the energy. The canopy shape and the region to fill with leaves and flowers are also controlled by hand-drawn guide lines.

The unconditionally stable (US) Laguerre-FDTD method has recently attracted significant attention for its high efficiency and accuracy in modeling fine structures. One of the most attractive characteristics of this method is its marching-on-in-order solution scheme. This paper presents Hermite-Rodriguez functions as another type of orthogonal basis to implement a new 2-D US solution scheme.

With the appearance of large OLED panels, the OLED TV industry has experienced significant growth. However, this technology is still in the early stages of commercialization, and some technical challenges remain to be overcome. During the development phase of a product, power consumption is one of the most important considerations. To reduce power consumption in OLED displays, we propose a method based on just-noticeable difference (JND). JND refers to the minimum visibility threshold when visual content is altered and results from physiological and psychophysical phenomena in the human visual system (HVS). A JND model suitable for OLED displays is derived from numerous experiments with OLED displays. With the use of JND, it is possible to reduce power consumption while minimizing perceptual image quality degradation.

We investigate a phased array-fed dual reflector antenna applying one-dimensional beam-scanning of the center-fed type, using an elliptical aperture to provide wide area observation. The distinguishing feature of this antenna is its elliptical aperture shape, in which the aperture diameter differs between the forward satellite direction and the cross-section orthogonal to it. The shape in the plane of the forward satellite direction, which does not have a beam-scanning function, is a ring-focus Cassegrain antenna, and the shape in the plane orthogonal to that, which does have a beam-scanning function, is an imaging reflector antenna. This paper describes issues which arose during design of the elliptical aperture shape and how they were solved, and presents design results using elliptical aperture dimensions of 1600 mm × 600 mm, in which the beam width differs by more than two times in the orthogonal cross-section. The effectiveness of the antenna was verified by fabricating a prototype antenna based on the design results. Measurement results confirmed that an aperture efficiency of 50% or more could be achieved, and that a different beam width was obtained in the orthogonal plane in accordance with design values.

DDoS remains a major threat to Software Defined Networks. To keep SDN secure, effective detection techniques for DDoS are indispensable. Most of the newly proposed schemes for detecting such attacks on SDN make the SDN controller act as the IDS or the central server of a collaborative IDS. The controller consequently becomes a target of the attacks and a heavy loaded point of collecting traffic. A collaborative intrusion detection system is proposed in this paper without the need for the controller to play a central role. It is deployed as a modified artificial neural network distributed over the entire substrate of SDN. It disperses its computation power over the network that requires every participating switch to perform like a neuron. The system is robust without individual targets and has a global view on a large-scale distributed attack without aggregating traffic over the network. Emulation results demonstrate its effectiveness.

A map-reduce framework is popular for big data analysis. In the typical map-reduce framework, both master node and worker nodes can use hard-disk drives (HDDs) as local disks for the map-reduce computation. However, because of the inherit mechanical problems of HDDs, the I/O performance is a bottleneck for the map-reduce framework when I/O-intensive applications (e.g., sorting) are performed. Replacing HDDs with solid-state drives (SSDs) is not economical, although SSDs have better performance than HDDs. In this paper, we propose a virtualization-based hybrid storage system for the map-reduce framework. The objective of the paper is to combine the advantages of the fast access property of SSDs and the low cost of HDDs by realizing an economical design and improving I/O performance of a map-reduce framework in a virtualization environment. We propose three storage combinations: SSD-based, HDD-based, and a hybrid of SSD-based and HDD-based storage systems which balances speed, capacity, and lifetime. According to experiments, the hybrid of SSD-based and HDD-based storage systems offers superior performance and economy.

In this research, we investigated the reliability of a 1-out-of-2 system with two-stage repair comprising hardware restoration and data reconstruction modes. Hardware restoration is normally independently executed by two modules. In contrast, we assumed that one of the modules could omit data reconstruction by replicating the data from the module during normal operation. In this 1-out-of-2 system, the two modules mutually cooperated in the recovery mode. As a first step, an evaluation model using Markov chains was constructed to derive a reliability measure: “unavailability in steady state.” Numerical examples confirmed that the reliability of the system was improved by the use of two cooperating modules. As the data reconstruction time increased, the gains in terms of system reliability also increased.

In this paper, we address the problem of non-parametric template matching which does not assume any specific deformation models. In real-world matching scenarios, deformation between a template and a matching result usually appears to be non-rigid and non-linear. We propose a novel approach called local rigidity constraints (LRC). LRC is built based on an assumption that the local rigidity, which is referred to as structural persistence between image patches, can help the algorithm to achieve better performance. A spatial relation test is proposed to weight the rigidity between two image patches. When estimating visual similarity under an unconstrained environment, high-level similarity (e.g. with complex geometry transformations) can then be estimated by investigating the number of LRC. In the searching step, exhaustive matching is possible because of the simplicity of the algorithm. Global maximum is given out as the final matching result. To evaluate our method, we carry out a comprehensive comparison on a publicly available benchmark and show that our method can outperform the state-of-the-art method.

Deterioration of sewer pipes is one of very important problems in Japan. Sewer inspections have been carried out mainly by visual check or wired remote robots with a camera. However, such inspection schemes involve high labor and/or monetary cost. Sewer inspection with boat-type video cameras or unwired robots takes a long time to check the result of the inspection because video data are obtained after the equipment is retrieved from the pipe. To realize low cost, safe and quick inspection of sewer pipes, we have proposed a sewer inspection system using drifting wireless sensor nodes. Water, soil, and the narrow space in the pipe make the long-range and high throughput wireless radio communication difficult. Therefore, we have to identify suitable radio frequency and antenna configuration based on wireless communication characteristics in sewer pipes. If the frequency is higher, the Fresnel zone, the needed space for the line of sight is small, but the path loss in free space is large. On the other hand, if the frequency is lower, the size of the Fresnel zone is large, but the path loss in free space is small. We conducted wireless communication experiments using 920MHz, 2.4GHz, and 5GHz band off-the-shelf devices in an experimental underground pipe. The measurement results show that the wireless communication range of 5GHz (IEEE 802.11a) is over 8m in a 200mm-diameter pipe and is longer than 920MHz (ARIB STD-T108), 2.4GHz (IEEE 802.11g, IEEE 802.15.4) band at their maximum transmission power. In addition, we confirmed that devices that use IEEE 802.11a and 54Mbps bit rate can transmit about 43MB data while they are in the communication range of an AP and drift at 1m/s in a 200mm-diameter pipe, and it is bigger than one of devices that use other bit rate.

In this paper, we first analyze the discriminative power in the Best Match (BM) 25 formula and provide its calculation method from the Bayesian point of view. The resulting, derived discriminative power is quite similar to the exponential inverse document frequency (EIDF) that we have previously proposed [1] but retains more preferable theoretical advantages. In our previous paper [1], we proposed the EIDF in the framework of the probabilistic information retrieval (IR) method BM25 to address the instance search task, which is a specific object search for videos using an image query. Although the effectiveness of our EIDF was experimentally demonstrated, we did not consider its theoretical justification and interpretation. We also did not describe the use of region-of-interest (ROI) information, which is supposed to be input to the instance search system together with the original image query showing the instance. Therefore, here, we justify the EIDF by calculating the discriminative power in the BM25 from the Bayesian viewpoint. We also investigate the effect of the ROI information for improving the instance search accuracy and propose two search methods incorporating the ROI effect into the BM25 video ranking function. We validated the proposed methods through a series of experiments using the TREC Video Retrieval Evaluation instance search task dataset.

In data sharing privacy has become one of the main concerns particularly when sharing datasets involving individuals contain private sensitive information. A model that is widely used to protect the privacy of individuals in publishing micro-data is k-anonymity. It reduces the linking confidence between private sensitive information and specific individual by generalizing the identifier attributes of each individual into at least k-1 others in dataset. K-anonymity can also be defined as clustering with constrain of minimum k tuples in each group. However, the accuracy of the data in k-anonymous dataset decreases due to huge information loss through generalization and suppression. Also most of the current approaches are designed for numerical continuous attributes and for categorical attributes they do not perform efficiently and depend on attributes hierarchical taxonomies, which often do not exist. In this paper we propose a new model for k-anonymization, which is called Similarity-Based Clustering (SBC). It is based on clustering and it measures similarity and calculates distances between tuples containing numerical and categorical attributes without hierarchical taxonomies. Based on this model a bottom up greedy algorithm is proposed. Our extensive study on two real datasets shows that the proposed algorithm in comparison with existing well-known algorithms offers much higher data utility and reduces the information loss significantly. Data utility is maintained above 80% in a wide range of k values.

With the flourish of applications based on the Internet of Things (IoT), privacy issues have been attracting a lot of attentions. Although the concept of privacy homomorphism was proposed along with the birth of the well-known RSA cryptosystems, cryptographers over the world have spent about three decades for finding the first implementation of the so-called fully homomorphic encryption (FHE). Despite of, currently known FHE schemes, including the original Gentry's scheme and many subsequent improvements as well as the other alternatives, are not appropriate for IoT-oriented applications because most of them suffer from the problems of inefficient key size and noisy restraining. In addition, for providing fully support to IoT-oriented applications, symmetric fully homomorphic encryptions are also highly desirable. This survey presents an analysis on the challenges of designing secure and practical FHE for IoT, from the perspectives of lightweight requirements as well as the security requirements. In particular, some issues about designing noise-free FHE schemes would be addressed.

A virtual network edge using live migration of virtualized network functions (VNFs) can be expected to reduce computation time and save resources instead of conventional network edge routers that have complex functions. Wavelength-division-multiplexing/time-division-multiplexing (WDM/TDM) photonic switching technology for metro ring networks is proposed to provide fast bandwidth resource allocation for rapidly changing service-flow demand. However, there are no reports on the coexistence of high-speed path switching for live migration with fast bandwidth resource allocation, as far as we know. We propose an architecture that achieves both high-speed path switching and fast dynamic bandwidth allocation control for service flows with in-service live migration. The feature of this architecture is that the VNF for the virtual edge corresponds to each 10-gigabit Ethernet-passive optical network (10G-EPON) and fast route change can be achieved with a simple point-to-point path between VNFs and optical line terminals (OLTs). The second feature is that the live migration of a VNF is limited to a part of it that contains a larger number of subscribers. Owing to the reduction in the number of total paths, fast resource allocation can be provided.

Information-Centric Networking (ICN) treats contents as first class citizens and adopts name-based routing for content distribution and retrieval. Content names rather than IP addresses are directly used for routing. However, due to the location-independent naming and the huge namespace, name-based routing faces scalability and efficiency issues including large routing tables and high path stretches. This paper proposes a universal Scalable Name-based Geometric Routing scheme (SNGR), which is a careful synthesis of geometric routing and name resolution. To provide scalable and efficient underlying routing, a universal geometric routing framework (GRF) is proposed. Any geometric routing scheme can be used directly for name resolution based on GRF. To implement an overlay name resolution system, SNGR utilizes a bi-level grouping design. With this design, a resolution node that is close to the consumer can always be found. Our theoretical analyses guarantee the performance of SNGR, and experiments show that SNGR outperforms similar routing schemes in terms of node state, path stretch, and reliability.

With the increase of data quantity, people have begun to attach importance to cloud storage. However, numerous security accidents occurred to cloud servers recently, thus triggering thought about the security of traditional single cloud. In other words, traditional single cloud can't ensure the privacy of users' data to a certain extent. To solve those security issues, multi-cloud systems which spread data over multiple cloud storage servers emerged. They employ a series of erasure codes and other keyless dispersal algorithms to achieve high-level security. But non-systematic codes like RS require relatively complex arithmetic, and systematic codes have relatively weaker security. In terms of keyless dispersal algorithms, they avoid key management issues but not suit to complete parallel optimization or deduplication which is important to limited cloud storage resources. So in this paper, we design a new kind of XOR-based non-systematic erasure codes - Privacy Protecting Codes (PPC) and a SIMD encoding algorithm for better performance. To achieve higher-level security, we put forward a novel deduplication-friendly dispersal algorithm called Hash Cyclic Encryption-PPC (HCE-PPC) which can achieve complete parallelization. With these new technologies, we present a multi-cloud storage system called CloudS. For better user experience and the tradeoffs between security and performance, CloudS provides multiple levels of security by various combinations of compression, encryption and coding schemes. We implement CloudS as a web application which doesn't require users to perform complicated operations on local.

Trellis coded modulation (TCM) concept is applied to the mode constellation points of orbital angular momentum (OAM) modulation. OAM modulation considers the multiple OAM modes as additional constellation points and maps a first part of a block of information bits to the transmitting OAM modes. Therefore, spatial multiplexing gains are retained and spectral efficiency is boosted. The second part of the block of information bits is mapped to a complex symbol using conventional digital modulation schemes. At any particular time instant, only one OAM mode is active. The receiver estimates the transmitted symbol and the active OAM mode, then uses the two estimates to retrieve the original block of data bits. Simulation reveals that with the TCM employed both for the OAM constellation points and the signal constellation points, a considerable bit error rate (BER) gain can be obtained under all turbulence conditions, compared with that of the no coding scheme.

Interference alignment (IA) is a method to improve the capacity of cell-edge users and thus attracts an intense research interest. We focus on the IA extended to the multiple-input multiple-output (MIMO) interference network. In this method, each coordinated transmitter generates beamforming vectors to align interference from different transmitters into confined subspace at each receiver. Then, using singular value decomposition (SVD) with the relative magnitude coefficients, transmitters calculate the beamforming vectors and the received vectors. However, in this method it is difficult to determine the value of the relative magnitude coefficients so that the system capacity is improved, because it is necessary to solve the non-linear function of multivariable. In this paper, we propose a design method of the relative magnitude coefficients of interference channels to improve system capacity using Brent's method on the K-User MIMO interference channel (MIMO-IFC). The proposed method can improve system capacity, though the system complexity increases due to Brent's method that requires multiple SVD calculation to calculate the null space. Thus, instead of using SVD, we introduce the complexity reduction method to calculate the null space of the matrix. Furthermore, we extend the proposed method to be applicable for more common systems where all base stations have the same number of transmit antennas. Through simulation, we show that the proposed method achieves a higher system capacity than the conventional one. We also show that the method that calculates the null space needs much lower complexity than SVD. In addition, we show that the proposed design method reduces the degradation of the system capacity caused by the interference not eliminated, and achieves the fairness of capacities among users for an increase of the number of design coefficients.