Video traffic occupies a major part of current mobile traffic. The characteristics of video traffic are dominated by the behavior of the video application users. This paper uses a state transition diagram to analyze the behavior of video application users on smart phones. Video application users are divided into two categories; keyword search users and initial screen users. They take different first action in video viewing. The result of our analysis shows that the patience of video application users depends on whether they have a specific purpose when they launch a video application or not. Mobile network operators can improve the QoE of video application users by utilizing the results of this study.

A two-dimensional (2D) wireless power transmission (WPT) system that handles a wide range of transmitted and received power is proposed and evaluated. A transmitter outputs the power to an arbitrary position on a 2D waveguide sheet by using a beam-forming technique. The 2D waveguide sheet does not require an absorber on its edge. The minimum propagation power on the sheet is increased 18 times by using the beam-forming technique. Power amplifier (PA) efficiency was improved from 19% to 46% when the output power was 10dB smaller than peak power due to the use of a PA supply-voltage and input power control method. Peak PA efficiency was 60%. A receiver inputs a wide range of power levels and drives various load impedances with a parallel rectifier. This rectifier enables a number of rectifying units to be tuned dynamically. The rectifier efficiency was improved 1.5 times while input power range was expanded by 6dB and the load-impedance range was expanded fourfold. The rectifier efficiency was 66-73% over an input power range of 18-36dBm at load impedances of 100 and 400Ω.

This article introduces a self-organizing model which builds the topology of a DHT mapping system for ICN. Due to its self-organizing operation and low average degree of maintenance, the management overhead of the system is reduced dramatically, which yields inherent scalability. The proposed model can improve latency by around 10% compared to an existing approach which has a near optimal average distance when the number of nodes and degree are given. In particular, its operation is simple which eases maintenance concerns. Moreover, we analyze the model theoretically to provide a deeper understanding of the proposal.

Maximally flat digital differentiators (MFDDs) are widely used in many applications. By using MFDDs, we obtain the derivative of an input signal with high accuracy around their center frequency of flat property. Moreover, to avoid the influence of noise, it is desirable to attenuate the magnitude property of MFDDs expect for the vicinity of the center frequency. In this paper, we introduce a design method of linear phase FIR band-pass MFDDs with an arbitrary center frequency. The proposed transfer function for both of TYPE III and TYPE IV can be achieved as a closed form function using Jacobi polynomial. Furthermore, we can easily derive the weighting coefficients of the proposed MFDDs using recursive formula. Through some design examples, we confirm that the proposed method can adjust the center frequency arbitrarily and the band width having flat property.

This paper shows a method to find a linear transformation that reduces the number of variables to represent a given incompletely specified index generation function. It first generates the difference matrix, and then finds a minimal set of variables using a covering table. Linear transformations are used to modify the covering table to produce a smaller solution. Reduction of the difference matrix is also considered.

For compressed sensing, to address problems which do not involve reconstruction, a correlation analysis between measurements and the transform coefficients is proposed. It is shown that there is a linear relationship between them, which indicates that we can abstract the inner property of images directly in the measurement domain.

As a promising future network architecture, Information-centric networking (ICN) has attracted much attention, its ubiquitous in-network caching is one of the key technologies to optimize the dissemination of information. However, considering the diversity of contents and the limitation of cache resources in the Internet, it is usually difficult to find a one-fit-all caching strategy. How to manage the ubiquitous in-network cache in ICN has become an important problem. In this paper, we explore ways to improve cache performance from the three perspectives of spatiality, temporality and availability, based on which we further propose an in-network cache management strategy to support differentiated service. We divide contents requested in the network into different levels and the selection of caching strategies depends on the content level. Furthermore, the corresponding models of utilizing cache resources in spatiality, temporality and availability are also derived for comparison and analysis. Simulation verifies that our differentiated service based cache management strategy can optimize the utilization of cache resources and get higher overall cache performance.

In this paper, we consider the lossy source coding problem with delayed side information at the decoder. We assume that delay is unknown but the maximum of delay is known to the encoder and the decoder, where we allow the maximum of delay to change with the block length. In this coding problem, we show an upper bound and a lower bound of the rate-distortion (RD) function, where the RD function is the infimum of rates of codes in which the distortion between the source sequence and the reproduction sequence satisfies a certain distortion level. We also clarify that the upper bound coincides with the lower bound when maximums of delay per block length converge to a constant. Then, we give a necessary and sufficient condition in which the RD function is equal to that for the case without delay. Furthermore, we give an example of a source which does not satisfy this necessary and sufficient condition.

The modeling of random telegraph noise (RTN) of MOS transistors is becoming increasingly important. In this paper, a novel method is proposed for realizing automated estimation of two important RTN-model parameters: the number of interface-states and corresponding threshold voltage shift. The proposed method utilizes a Gaussian mixture model (GMM) to represent the voltage distributions, and estimates their parameters using the expectation-maximization (EM) algorithm. Using information criteria, the optimal estimation is automatically obtained while avoiding overfitting. In addition, we use a shared variance for all the Gaussian components in the GMM to deal with the noise in RTN signals. The proposed method improved estimation accuracy when the large measurement noise is observed.

The outage capacity of the fading cognitive multicast channel (CMC) is investigated in this paper. Assume that the instantaneous channel state information (CSI) of the interference link between the cognitive base station (CBS) and the primary user (PU) is available at the CBS, we derive the outage capacity in Rayleigh fading environments under the interference power and the transmit power constraints. Under the condition that the interference power limit is sufficiently larger or smaller than the transmit power limit, the asymptotic outage capacity is obtained in closed-form. Assume that only the channel distribution information (CDI) of the interference link is available at the CBS, the outage capacity under the interference outage and the transmit power constraints is derived in closed-form. The theoretical results are confirmed by simulations. It is shown that the outage capacity is not degraded due to partial knowledge of the interference link when the interference power limit is sufficiently larger than the transmit power limit. It is also shown that the capacity gain due to increasing the number of the secondary users (SUs) is negligible if the number of the SUs is already large. Additionally, the case of CDI with estimation error is also investigated. Interestingly, we show that the estimation error of CDI may be a positive factor for improving the outage capacity of the CMC.

Keyword-based linked data information retrieval is an easy choice for general-purpose users, but the implementation of such an approach is a challenge because mere keywords do not hold semantic information. Some studies have incorporated templates in an effort to bridge this gap, but most such approaches have proven ineffective because of inefficient template management. Because linked data can be presented in a structured format, we can assume that the data's internal statistics can be used to effectively influence template management. In this work, we explore the use of this influence for template creation, ranking, and scaling. Then, we demonstrate how our proposal for automatic linked data information retrieval can be used alongside familiar keyword-based information retrieval methods, and can also be incorporated alongside other techniques, such as ontology inclusion and sophisticated matching, in order to achieve increased levels of performance.

In conventional wireless cellular networks, cell coverage is static and fixed, and each user equipment (UE) is connected to one or a few local base stations (BS). However, the users' distribution in the network area commonly fluctuates during a day. When there are congeries of users in some areas, conventional networks waste idle network resources in sparse areas. To address this issue, we propose a novel approach for cooperative cluster formation to dynamically transfer idle network resources from sparse cells to crowded cells or hotspots. In our proposed scheme, BS coverage is directed to hotspots by dynamically changing the antennas' beam angles, and forming large optimal cooperative clusters around hotspots. In this study, a cluster is a group of BSs that cooperatively perform joint transmission (JT) to several UEs. In this paper, a mathematical framework for calculation of the system rate of a cooperative cluster is developed. Next, the set of BSs for each cluster and the antennas' beam angles of each BS are optimized so that the system rate of the network is maximized. The trend of performance variation versus cluster size is studied and its limitations are determined. Numerical results using 3GPP specifications show that the proposed scheme attains several times higher capacity than conventional systems.

We consider an improved control method based on the Stability Transformation Method. Stability Transformation Method detects unknown and unstable periodic orbits of chaotic dynamical systems. Based on the approach to realize the Stability Transformation Method in real systems, we have proposed a control method which can stabilize unknown and unstable periodic orbits embedded in chaotic attractors. However, setting of the control parameters of the control system has remained as unsolved issue. When the dynamics of a target system are unknown, the control parameters have to be set by trial and error. In this paper, we improve the control method with the automatic adjustment function of the control parameters. We show an example of stabilizing unstable periodic orbits of the 3-dimensional hysteresis chaos generator by using the proposed control method. Some results are confirmed by laboratory measurements. The results imply that any unknown and unstable periodic orbits can be stabilized by using the proposed method, if the target chaos system is reduced to 1-dimensional return map.

IEEE 802.15.6 provides PHY and MAC layer profiles for wearable and implanted Wireless Body Area Networks (WBANs). The critical requirements of QoS guarantee and ultra-low-power are severe challenges when implementing IEEE 802.15.6. In this paper, the key problem in IEEE 802.15.6 standard that “How to allocate EAP (Exclusive Access Phase)?” is solved for the first time: An analysis of network performance indicates that too much EAP allocation can not promote traffic performance obviously and effectually. However, since EAP allocation plays an important role in guaranteeing quality of service, a customized and quantitative EAP allocation solution is proposed. Simulation results show that the solution can obtain the optimal network performance. Furthermore, the estimated models of delay and energy are developed, which help to design the WBAN according to application requirements and analyze the network performance according to the traffic characteristics. The models are simple, effective, and relatively accurate. Results show that the models have approximated mean and the correlation coefficient is greater than 0.95 compared with the simulations of IEEE 802.15.6 using NS2 platform. The work of this paper can solve crucial practical problems in using IEEE 802.15.6, and will propel WBANs applications widely.

This letter proposes an efficient lossless compression method for high dynamic range (HDR) images in OpenEXR format. The proposed method transforms an HDR image to an indexed image and packs the histogram of the indexed image. Finally the packed image is losslessly compressed by using any existing lossless compression algorithm such as JPEG 2000. Experimental results show that the proposed method reduces the bit rate of compressed OpenEXR images compared with equipped lossless compression methods of OpenEXR format.

In this paper, the spatial smoothing (SS) method is extended to the wideband multipath case. By reordering the array input signal and the weight vector, the corresponding covariance matrix of each subarray can be constructed conveniently. Then, a novel wideband beamforming algorithm, based on the SS method (SS-WB), can be achieved by linearly constrained minimum variance (LCMV). Further improvement of the output signal-to-interference-plus-noise ratio (SINR) for SS-WB can be obtained by removing the desired signal in the observed array data with the reconstruction of covariance matrix, which is denoted as wideband beamformer based on modified SS method (MSS-WB). Both proposed algorithms can reduce the desired signal cancellation due to the super decorrelation ability of SS method and MSS-WB can lead to a significantly improved output SINR. The simulations verify their effectiveness in the multipath environment.

NAND-based block devices such as memory cards and solid-state drives embed a flash translation layer (FTL) to emulate the standard block device interface and its features. The overall performance of these devices is determined mainly by the efficiency of the FTL scheme, so intensive research has been performed to improve the average performance of the FTL scheme. However, its worst-case performance has rarely been considered. The present study aims to improve the worst-case performance without affecting the average performance. The central concept is to distribute the garbage collection cost, which is the main source of performance fluctuations, over multiple requests. The proposed scheme comprises three modules: i) anticipated partial log block merging to distribute the garbage collection time; ii) reclaiming clean pages by moving valid pages to bound the worst-case garbage collection time, instead of performing repeated block merges; and iii) victim selection based on the valid page count in a victim log and the required clean page count to avoid subsequent garbage collections. A trace-driven simulation showed that the worst-case performance was improved up to 1,300% using the proposed garbage collection scheme. The average performance was also similar to that of the original scheme. This improvement was achieved without additional memory overheads.

Boneh et al. proposed the new idea of pairing-based cryptography by using the composite order group instead of prime order group. Recently, many cryptographic schemes using pairings of composite order group were proposed. Miller's algorithm is used to compute pairings, and the time of computing the pairings depends on the cost of calculating the Miller loop. As a method of speeding up calculations of the pairings of prime order, the number of iterations of the Miller loop can be reduced by choosing a prime order of low Hamming weight. However, it is difficult to choose a particular composite order that can speed up the pairings of composite order. Kobayashi et al. proposed an efficient algorithm for computing Miller's algorithm by using a window method, called Window Miller's algorithm. We can compute scalar multiplication of points on elliptic curves by using a window hybrid binary-ternary form (w-HBTF). In this paper, we propose a Miller's algorithm that uses w-HBTF to compute Tate pairing efficiently. This algorithm needs a precomputation both of the points on an elliptic curve and rational functions. The proposed algorithm was implemented in Java on a PC and compared with Window Miller's Algorithm in terms of the time and memory needed to make their precomputed tables. We used the supersingular elliptic curve y2=x3+x with embedding degree 2 and a composite order of size of 2048-bit. We denote w as window width. The proposed algorithm with w=6=2·3 was about 12.9% faster than Window Miller's Algorithm with w=2 although the memory size of these algorithms is the same. Moreover, the proposed algorithm with w=162=2·34 was about 12.2% faster than Window Miller's algorithm with w=7.

Aircraft Landing Scheduling (ALS) attempts to determine the landing time for each aircraft. The objective of ALS is to minimise the deviations of the landing time of each aircraft from its target landing time. In this paper, we propose a dynamic hyper-heuristic algorithm for the ALS problem. In our approach, the Scatter Search algorithm is chosen as the high level heuristic to build a chain of intensification and diversification priority rules, which are applied to generate the landing sequence by different priority rules, which are low level heuristics in the hyper-heuristic framework. The landing time for each aircraft can be calculated efficiently based on the landing sequence. Simulation studies demonstrate that the proposed algorithm can obtain high quality solutions for ALS.

Cloud computing, a novel distributed paradigm to provide powerful computing capabilities, is usually adopted by developers and researchers to execute complicated IoT applications such as complex workflows. In this scenario, it is fundamentally important to make an effective and efficient workflow application scheduling and execution by fully utilizing the advantages of the cloud (as virtualization and elastic services). However, in the current stage, there is relatively few research for workflow scheduling in cloud environment, where they usually just bring the traditional methods directly into cloud. Without considering the features of cloud, it may raise two kinds of problems: (1) The traditional methods mainly focus on static resource provision, which will cause the waste of resources; (2) They usually ignore the performance fluctuation of virtual machines on the physical machines, therefore it will lead to the estimation error of task execution time. To address these problems, a novel mechanism which can estimate the probability distribution of subtask execution time based on background VM load series over physical machines is proposed. An elastic performance fluctuations-aware stochastic scheduling algorithm is introduced in this paper. The experiments show that our proposed algorithm can outperform the existing algorithms in several metrics and can relieve the influence of performance fluctuations brought by the dynamic nature of cloud.