Anomaly detection is one approach in intrusion detection systems (IDSs) which aims at capturing any deviation from the profiles of normal network activities. However, it suffers from high false alarm rate since it has impediment to distinguish the boundaries between normal and attack profiles. In this paper, we propose an effective anomaly detection approach by hybridizing three techniques, i.e. particle swarm optimization (PSO), ant colony optimization (ACO), and genetic algorithm (GA) for feature selection and ensemble of four tree-based classifiers, i.e. random forest (RF), naive bayes tree (NBT), logistic model trees (LMT), and reduces error pruning tree (REPT) for classification. Proposed approach is implemented on NSL-KDD dataset and from the experimental result, it significantly outperforms the existing methods in terms of accuracy and false alarm rate.

The user authorization query (UAQ) problem determines whether there exists an optimum set of roles to be activated to provide a set of permissions requested by a user. It has been deemed as a key issue for efficiently handling user's access requests in role-based access control (RBAC). Unfortunately, the weight is a value attached to a permission/role representing its importance, should be introduced to UAQ, has been ignored. In this paper, we propose a comprehensive definition of the weighted UAQ (WUAQ) problem with the role-weighted-cardinality and permission-weighted-cardinality constraints. Moreover, we study the computational complexity of different subcases of WUAQ, and show that many instances in each subcase are intractable. In particular, inspired by the idea of the genetic algorithm, we propose an algorithm to approximate solve an intractable subcase of the WUAQ problem. An important observation is that this algorithm can be efficiently modified to handle the other subcases of the WUAQ problem. The experimental results show the advantage of the proposed algorithm, which is especially fit for the case that the computational overhead is even more important than the accuracy in a large-scale RBAC system.

We present the first demonstration of an electro-optic modulator based on a photolithographically fabricated photonic crystal (PhC) nanocavity with a p-i-n junction with SiO2 cladding. We show that the device exhibits an ultrahigh quality factor (Q∼105) and allow us to demonstrate electro-optic modulation through the integrated p-i-n diode structure. We demonstrate an electro-optic modulation based on the carrier injection.

This paper discusses key technologies specific for fifth generation (5G) cellular systems which are expected to connect internet of things (IoT) based vertical sectors. Because services for 5G will be expanded drastically, from information transfer services to mission critical and massive connection IoT connection services for vertical sectors, and requirement for cellular systems becomes quite different compared to that of fourth generation (4G) systems, after explanation for the service and technical trends for 5G, key wireless access technologies will be discussed, especially, from the view point of what is new and how import. In addition to the introduction of new technologies for wireless access, flexibility of networking is also discussed because it can cope with QoS support services, especially to cope with end-to-end latency constraint conditions. Therefore, this paper also discuss flexible network configuration using mobile edge computing (MEC) based on software defined network (SDN) and network slicing.

Hybrid vehicles (HVs) and electric vehicles (EVs) have become widespread. These vehicles incorporate a large number of electronic devices, which requires the use of a high-voltage (200 V) battery. Power electronics devices driven by the 200 V battery is expected to increase in the future. As such, we herein propose a power line communication (PLC) method that uses a high-voltage power line. In the present paper, we first clarify the transmission channel through modeling of an equivalent circuit and channel measurement. We then conduct noise measurements and determine the noise characteristics of the proposed PLC. Finally, we evaluate the bit error rate performance through computer simulations based on the measured transmission channel and noise.

This paper presents a high-throughput sliding block Viterbi decoder for IEEE 802.11ac systems. A 64-state bidirectional sliding block Viterbi method is proposed to meet the speed requirement of the system. The decoder throughput goes up to 640Mbps, which can be further increased by adding the block parallelism. Moreover, a modified add-compare-select (ACS) unit is designed to enhance the working frequency. The modified ACS unit obtains nearly 26% speed-up, compared to the conventional ACS unit. However, the area overhead and power dissipation are almost the same. The decoder is designed in a SMIC 0.13µm technology, and it occupies 1.96mm2 core area and 105mW power consumption with an energy efficiency of 0.1641nJ/bit with a 1.2V voltage supply.

Improved fractional variable tap-length adaptive algorithm that contains Sigmoid limited fluctuation function and adaptive variable step-size of tap-length based on fragment-full error is presented. The proposed algorithm can solve many deficiencies in previous algorithm, comprising small convergence rate and weak anti-interference ability. The parameters are able to modify reasonably on the basis of different situations. The Sigmoid constrained function can decrease the fluctuant amplitude of the instantaneous errors effectively and improves the ability of anti-noise interference. Simulations demonstrate that the proposed algorithm equips better performance.

In order to support user data rates of Gbps and above in the fifth generation (5G) communication systems, millimeter wave (mm-wave) communication is proposed as one of the most important enabling technologies. In this paper, we consider the spectrum bands shared by 5G cellular base stations (BS) and some existing networks, such as WiGig and proposed a method for spectrally efficient coexistence of multiple interfering BSs through adaptive self-organized beam scheduling. These BSs might use multiple radio access technologies belonging to multiple operators and are deployed in the unlicensed bands, such as 60GHz. Different from the recently emerging coexistence scenarios in the unlicensed 5GHz band, where the proposed methods are based on omni-directional transmission, beamforming needs to be employed in mm-wave bands to combat the high path loss problem. The proposed method is concerned with this new scenario of communication in the unlicensed bands where (a) beam-forming is mandatory to combat severe path loss, (b) without optimal scheduling of beams mutual interference could be severe due to the possibility of beam-collisions, (c) unlike LTE which users time-frequency resource blocks, a new resource, i.e., the beam direction, is used as mandatory feature. We propose in this paper a novel multi-RAT coexistence mechanism where neighbouring 5G BSs, each serving their own associated users, schedule their beam configurations in a self-organized manner such that their own utility function, e.g. spectral efficiency, is maximized. The problem is formulated as a combinatorial optimization problem and it is shown via simulations that our proposed distributed algorithms yield a comparable spectral efficiency for the entire networks as that using an exhaustive search, which requires global coordination among coexisting RATs and also has a much higher algorithmic complexity.

The use of flash memory based storage devices is rapidly increasing, and user demands for high performance are also constantly increasing. The performance of the flash storage device is greatly influenced by cleaning operations of Flash Translation Layer (FTL). Various studies have been conducted to lower the cost of cleaning operations. However, there are limits to achieve sufficient performance improvement of flash storages without help of a host system, with only limited information in storage devices. Recently, SCSI, eMMC, and UFS standards provide an interface for sending semantic information from a host system to a storage device. In this paper, we analyze effects of semantic information on performance and lifetime of flash storage devices. We evaluate performance and lifetime improvement through SA-FTL (Semantic Aware Flash Translation Layer), which can take advantage of semantic information in storage devices. Experiments show that SA-FTL improves performance and lifetime of flash based storages by up to 30 and 35%, respectively, compared to a simple page-level FTL.

This paper presents some results of an experimental trial for the 5th generation (5G) wireless communication systems using 28GHz band. In order to tackle rapidly increasing traffic for 2020 and beyond, new radio access networks for the 5G mobile communication systems will introduce the use of higher frequency bands such as spectra higher than 10GHz to achieve higher capacity and super high bit rate transmission of several tens of Gbps. The target of this experimental trial is to evaluate the feasibility of using the 28GHz band with super-wide bandwidth of 800MHz for 5G wireless communication systems. To compensate large path-loss in higher frequency, the beamforming (BF) based on Massive multiple-input multiple-output (MIMO) is one of promising techniques and can be combined with spatial multiplexing of multiple data streams to achieve much higher capacity. In addition, to support the mobility of mobile station (MS), beam tracking technique is important. In this trial, we first conduct a basic experiment of single-stream transmission by using prototype system with base station (BS) having 96-element antenna and MS having 8-element antenna to evaluate the effectiveness of joint transmitter/receiver BF in 28GHz band in terms of coverage, impact of path loss, shadowing loss and penetration loss under indoor, outdoor and outdoor-to-indoor (O-to-I) environments. We show that by using 28 GHz band with BF based on Massive MIMO, higher throughput near 1.2Gbps can be achieved at many points in the indoor environment. It is also shown that the throughput of over 1Gbps can be achieved at points around 200m distant from BS in outdoor line-of-site (LOS) environment. Secondly, to evaluate the effectiveness of spatial multiplexing and beam tracking under more realistic environment, we also conduct the outdoor experiment of BF combined with 2-stream spatial multiplexing in high mobility environment with MS speed of up to 60km/h by using smartphone-shape MS antenna. We also show that maximum throughput of 3.77Gbps can be achieved with MS speed of 60km/h by using BF with 2-stream multiplexing and beam tracking.

This work develops a third-order multibit switched-current (SI) delta-sigma modulator (DSM) with a four-bit switched-capacitor (SC) flash analog-to-digital converter (ADC) and an incremental data weighted averaging circuit (IDWA), which is fabricated using 0.18µm 1P6M CMOS technology. In the proposed DSM, a 4-bit SC flash ADC is used to improve its resolution, and an IDWA is used to reduce the nonlinearity of digital-to-analog converter (DAC) by moving the quantization noise out of the signal band by first-order noise shaping. Additionally, the proposed differential sample-and-hold circuit (SH) exhibits low input impedance with feedback and width-length adjustment in the SI feedback memory cell (FMC) to increase the conversion rate. A coupled differential replicate (CDR) common-mode feedforward circuit (CMFF) is used to compensate for the mirror error that is caused by the current mirror. Measurements indicate that the signal-to-noise ratio (SNR), dynamic range (DR), effective number of bits (ENOB), power consumption, and chip area are 64.1 dB, 64.4 dB, 10.36 bits, 18.82 mW, and 0.45 × 0.67 mm2 (without I/O pad), respectively, with a bandwidth of 20 kHz, an oversampling ratio (OSR) of 256, a sampling frequency of 10.24 MHz, and a supply voltage of 1.8 V.

This paper presents a method to realize index generation functions using multiple Index Generation Units (IGUs). The architecture implements index generation functions more efficiently than a single IGU when the number of registered vectors is very large. This paper proves that independent linear transformations are necessary in IGUs for efficient realization. Experimental results confirm this statement. Finally, it shows a fast update method to IGUs.

As the most compelling candidate for 5G, millimeter-wave communication has drawn considerable interest, despite the absence of systematic research on its performance. Therefore, this study investigates millimeter-wave cellular networks and their use of existing frequency reuse schemes and scheduling methods. To evaluate the performance of these networks, we configure a system-level simulator that reflects the eNodeB architecture and frame structure designed to overcome the millimeter-wave frequency characteristics of the Giga Korea Project. Simulations conducted using various combinations of frequency reuse schemes and scheduling methods are described. We found that the best performing radio resource management scheme changes according to the number of user equipment accessing the eNodeB. The results of this study will contribute to performance estimations of the capacity and fairness of cellular-based millimeter-wave communication systems before they are deployed.

Named Entity Translation Equivalents extraction plays a critical role in machine translation (MT) and cross language information retrieval (CLIR). Traditional methods are often based on large-scale parallel or comparable corpora. However, the applicability of these studies is constrained, mainly because of the scarcity of parallel corpora of the required scale, especially for language pairs of Chinese and Japanese. In this paper, we propose a method considering the characteristics of Chinese and Japanese to automatically extract the Chinese-Japanese Named Entity (NE) translation equivalents based on inductive learning (IL) from monolingual corpora. The method adopts the Chinese Hanzi and Japanese Kanji Mapping Table (HKMT) to calculate the similarity of the NE instances between Japanese and Chinese. Then, we use IL to obtain partial translation rules for NEs by extracting the different parts from high similarity NE instances in Chinese and Japanese. In the end, the feedback processing updates the Chinese and Japanese NE entity similarity and rule sets. Experimental results show that our simple, efficient method, which overcomes the insufficiency of the traditional methods, which are severely dependent on bilingual resource. Compared with other methods, our method combines the language features of Chinese and Japanese with IL for automatically extracting NE pairs. Our use of a weak correlation bilingual text sets and minimal additional knowledge to extract NE pairs effectively reduces the cost of building the corpus and the need for additional knowledge. Our method may help to build a large-scale Chinese-Japanese NE translation dictionary using monolingual corpora.

The cloud radio access network (C-RAN) is embracing unprecedented popularity in the evolution of current RAN towards 5G. One of the essential benefits of C-RAN is facilitating cooperative transmission to enhance capacity and energy performances. In this paper, we argue that the conventional symmetric coordination in which all antennas participate in transmission does not necessarily lead to an energy efficient C-RAN. Further, the current assessments of energy consumption should be modified to match this shifted paradigm in network architecture. Towards this end, this paper proposes an asymmetric coordination scheme to optimize the energy efficiency of C-RAN. Specifically, asymmetric coordination is approximated and formulated as a joint antenna selection and power allocation problem, which is then solved by a proposed sequential-iterative algorithm. A modular power consumption model is also developed to convert the computational complexity of coordination into baseband power consumption. Simulations verify the performance benefits of our proposed asymmetric coordination in effectively enhancing system energy efficiency.

Cost-effective cloud storage services are attracting users with their convenience, but there is a trade-off between service availability and usage cost. We develop two cloud provider selection models for cloud storage services to minimize the total cost of usage. The models select multiple cloud providers to meet the user requirements while considering unavailability. The first model, called a user-copy (UC) model, allows the selection of multiple cloud providers, where the user copies its data to multiple providers. In addition to the user copy function of the UC model, the second model, which is called a user and cloud-provider copy (UCC) model, allows cloud providers to make copies of the data to deliver them to other cloud providers. The cloud service is available if at least one cloud provider is available. We formulate both models as integer linear programming (ILP) problems. Our performance evaluation observes that both models reduce the total cost of usage, compared to the single cloud provider selection approach. As the cost of bandwidth usage between a user and a cloud provider increases, the UCC model becomes more beneficial than the UC model. We implement the prototype for cloud storage services, and demonstrate our models via Science Information Network 5.

The compressive sensing (CS) theory has been recognized as a promising technique to achieve the target localization in wireless sensor networks. However, most of the existing works require the prior knowledge of transmitting powers of targets, which is not conformed to the case that the information of targets is completely unknown. To address such a problem, in this paper, we propose a novel CS-based approach for multiple target localization and power estimation. It is achieved by formulating the locations and transmitting powers of targets as a sparse vector in the discrete spatial domain and the received signal strengths (RSSs) of targets are taken to recover the sparse vector. The key point of CS-based localization is the sensing matrix, which is constructed by collecting RSSs from RF emitters in our approach, avoiding the disadvantage of using the radio propagation model. Moreover, since the collection of RSSs to construct the sensing matrix is tedious and time-consuming, we propose a CS-based method for reconstructing the sensing matrix from only a small number of RSS measurements. It is achieved by exploiting the CS theory and designing an difference matrix to reveal the sparsity of the sensing matrix. Finally, simulation results demonstrate the effectiveness and robustness of our localization and power estimation approach.