The authors have proposed a new type of flexible and printable 12GHz-band phase shifter using polymer actuator for the first time. Polymer bending actuator was used as a termination device of a reflection-type 3-dB, 90° hybrid coupler as the phase-shift control unit which controls the electrical length of the waveguide for microwave signals by the applied bias voltage. The microstrip line circuit of the device has been fabricated using low-cost screen printing method. Polymer bending actuator having three-layer stacking structure, in which an ionic liquid electrolyte layer is sandwiched with two conductive network composite layers, was formed by wet processes. The authors have confirmed that the phase shift could be controlled in analog by low driving voltages of 2-7 V for the actuator with a insertion loss of 2.73 dB. This phase shifter can be integrated with flexible patch antenna and the current flexible polymer electronics devices such as transistors.

Large-scale virtualized data centers are increasingly becoming the norm in our data-intensive society. One pressing challenge is to reduce the energy consumption of servers while maintaining a high level of service agreement fulfillment. Due to the convenience of virtualization, virtual machine migration is an effective way to optimize the trade-off between energy and performance. However, there are obvious drawbacks in the current static threshold strategy for migration. This paper proposes a new decision strategy based on decision-theoretic rough sets. In the new strategy, the status of a server is determined by the Bayesian rough set model. The space is divided into positive, negative and boundary regions. According to this information, a migration decision with minimum risk will be made. This three-way decision framework in our strategy can reduce over-migration and delayed migration. The experiments in this paper show that this new strategy outperforms the benchmark examined. It is an efficient and flexible approach to the energy and performance trade-off in the cloud.

This paper investigates receive power control for multiuser inductive power transfer (IPT) systems with a single-frequency coil array. The primary task is to optimize the transmit coil currents to minimize the total input power, subject to the minimum receive powers required by individual users. Due to the complicated coupling mechanism among all transmit coils and user pickups, the optimization problem is a non-convex quadratically constrained quadratic program (QCQP), which is analytically intractable. This paper solves the problem by applying the semidefinite relaxation (SDR) technique and evaluates the performance by full-wave electromagnetic simulations. Our results show that a single-frequency coil array is capable of power control for various multiuser scenarios, assuming that the number of transmit coils is greater than or equal to the number of users and the transmission conditions for individual users are uncorrelated.

This paper presents a water leakage monitoring system that gathers acoustic data of water pipes using wireless communication technology and identifies the sound of water leakage using machine leaning technology. To collect acoustic data effectively, this system combines three types of data-collection methods: drive-by, walk-by, and static. To design this system, it is important to ascertain the wireless communication distance that can be achieved with sensors installed in a basement. This paper also reports on radio propagation from underground manholes made from reinforced concrete and resin concrete in residential and commercial areas using the 920 MHz band. We reveal that it is possible to design a practical system that uses radio communication from underground sensors.

This paper proposes a method for predicting individuality-preserving gait patterns. Physical rehabilitation can be performed using visual and/or physical instructions by physiotherapists or exoskeletal robots. However, a template-based rehabilitation may produce discomfort and pain in a patient because of deviations from the natural gait of each patient. Our work addresses this problem by predicting an individuality-preserving gait pattern for each patient. In this prediction, the transition of the gait patterns is modeled by associating the sequence of a 3D skeleton in gait with its continuous-value gait features (e.g., walking speed or step width). In the space of the prediction model, the arrangement of the gait patterns are optimized so that (1) similar gait patterns are close to each other and (2) the gait feature changes smoothly between neighboring gait patterns. This model allows to predict individuality-preserving gait patterns of each patient even if his/her various gait patterns are not available for prediction. The effectiveness of the proposed method is demonstrated quantitatively. with two datasets.

Software-defined networking (SDN) has rapidly emerged as a promising new technology for future networks and gained considerable attention from both academia and industry. However, due to the separation between the control plane and the data plane, the SDN controller can easily become the target of denial-of service (DoS) attacks. To mitigate DoS attacks in OpenFlow networks, our solution, MinDoS, contains two key techniques/modules: the simplified DoS detection module and the priority manager. The proposed architecture sends requests into multiple buffer queues with different priorities and then schedules the processing of these flow requests to ensure better controller protection. The results show that MinDoS is effective and adds only minor overhead to the entire SDN/OpenFlow infrastructure.

In order to obtain road information, we propose an information acquisition method using infrared laser radar by detecting 3D reflector code on roadside. The infrared laser radar on vehicle scans the 3D reflector code on guardrail. Through experiments, we show that the proposed method is able to obtain road information by detecting 3D reflector code on guardrail.

High-performance Network Over Coax, or HINOC for short, is a broadband access technology that can achieve bidirectional transmission for high-speed Internet service through a coaxial medium. In HINOC access networks, buffer management scheme can improve the fairness of buffer usage among different output ports and the overall loss performance. To provide different services to multiple priority classes while reducing the overall packet loss rate and ensuring fairness among the output ports, this study proposes a QoS optimization method for access networks. A backpressure-based queue threshold control scheme is used to minimize the weighted average packet loss rate among multiple priorities. A theoretical analysis is performed to examine the performance of the proposed scheme, and optimal system parameters are provided. Software simulation shows that the proposed method can improve the average packet loss rate by about 20% to 40% compared with existing buffer management schemes. Besides, FPGA evaluation reveals that the proposed method can be implemented in practical hardware and performs well in access networks.

With the evolution of autonomous distributed systems such as smart cities, autonomous vehicles, smart control and scheduling systems there is an increased need for approaches to manage the execution of services to deliver real-time performance. As Cloud-hosted services are increasingly used to provide intelligence and analytic functionality to Internet of Things (IoT) systems, Quality of Service (QoS) techniques must be used to guarantee the timely service delivery. This paper reviews state-of-the-art QoS and Cloud techniques for real-time service delivery and data analysis. A review of straggler mitigation and a classification of real-time QoS techniques is provided. Then a mathematical framework is presented capturing the relationship between the host execution environment and the executing service allowing the response-times to predicted throughout execution. The framework is shown experimentally to reduce the number of QoS violations by 21% and provides alerts during the first 14ms provide alerts for 94% of future violations.

During the execution of software, tremendous amounts of data can be recorded. By exploiting the execution data, one can discover behavioral models to describe the actual software execution. As a well-known open-source process mining toolkit, ProM integrates quantities of process mining techniques and enjoys a variety of applications in a broad range of areas. How to develop a better ProM software, both from user experience and software performance perspective, are of vital importance. To achieve this goal, we need to investigate the real execution behavior of ProM which can provide useful insights on its usage and how it responds to user operations. This paper aims to propose an effective approach to solve this problem. To this end, we first instrument existing ProM framework to capture execution logs without changing its architecture. Then a two-layered framework is introduced to support accurate ProM behavior discovery by characterizing both user interaction behavior and plug-in calling behavior separately. Next, detailed discovery techniques to obtain user interaction behavior model and plug-in calling behavior model are proposed. All proposed approaches have been implemented.

With the expansion of the Internet, the number of available Web services has increased. Web service clustering to identify functionally similar clusters has become a major approach to the efficient discovery of suitable Web services. In this study, we propose a Web service clustering approach that uses novel ontology learning and a similarity calculation method based on the specificity of an ontology in a domain with respect to information theory. Instead of using traditional methods, we generate the ontology using a novel method that considers the specificity and similarity of terms. The specificity of a term describes the amount of domain-specific information contained in that term. Although general terms contain little domain-specific information, specific terms may contain much more domain-related information. The generated ontology is used in the similarity calculations. New logic-based filters are introduced for the similarity-calculation procedure. If similarity calculations using the specified filters fail, then information-retrieval-based methods are applied to the similarity calculations. Finally, an agglomerative clustering algorithm, based on the calculated similarity values, is used for the clustering. We achieved highly efficient and accurate results with this clustering approach, as measured by improved average precision, recall, F-measure, purity and entropy values. According to the results, specificity of terms plays a major role when classifying domain information. Our novel ontology-based clustering approach outperforms comparable existing approaches that do not consider the specificity of terms.

Both placing responsibility of message sending on every IoT object and obfuscating the object's location from other objects are essential to realize a secure and privacy-preserved communication service. Two or more short-lived link identifiers (or pseudonyms) authorized by a trustable authority are often used in related studies, instead of a persistent or long-term use link identifier (i.e. vendor assigned MAC address). However, related studies have limitations in terms of frequently changing pseudonyms to enhance location privacy because the cryptographic algorithms used in them fixedly couple object's identifiers with its security keys. To overcome those limitations, we present a new pseudonym and key management scheme that enables dynamic coupling of pseudonym and key pairs without incurring any adverse impacts. Furthermore, we propose two lightweight pseudonym allocation protocols to effectively reduce the volume of message carrying the allocation parameters. Through qualitative analyses, we verify that the proposed scheme is more scalable than related approaches as it can efficiently allocate enough number of pseudonym/key pairs by reducing the control message overhead by more than 90%.

Multiuser MIMO (MU-MIMO) improves the system channel capacity by generating a large virtual MIMO channel between a base station and multiple user terminals (UTs) with effective utilization of wireless resources. Block beamforming algorithms such as Block Diagonalization (BD) and Block Maximum Signal-to-Noise ratio (BMSN) have been proposed in order to realize MU-MIMO broadcast transmission. The BD algorithm cancels inter-user interference (IUI) by creating the weights so that the channel matrices for the other users are set to be zero matrices. The BMSN algorithm has a function of maintaining a high gain response for each desired user in addition to IUI cancellation. Therefore, the BMSN algorithm generally outperforms the BD algorithm. However, when the number of transmit antennas is equal to the total number of receive antennas, the transmission rate by both BD and BMSN algorithms is decreased. This is because the eigenvalues of channel matrices are too small to support data transmission. To resolve the issue, this paper focuses on an antenna selection (AS) method at the UTs. The AS method reduces the number of pattern nulls for the other users except an intended user in the BD and BMSN algorithms. It is verified via bit error rate (BER) evaluation that the AS method is effective in the BD and BMSN algorithms, especially, when the number of user antennas with a low bit rate (i.e., low signal-to-noise power ratio) is increased. Moreover, this paper evaluates the achievable bit rate and throughput including an actual channel state information feedback based on IEEE802.11ac standard. Although the number of equivalent receive antenna is reduced to only one by the AS method when the number of antennas at the UT is two, it is shown that the throughputs by BD and BMSN with the AS method (BD-AS and BMSN-AS) are higher than those by the conventional BD and BMSN algorithms.

In this letter, we study a wireless powered communication network (WPCN) with non-orthogonal multiple access (NOMA), where the user clustering scheme that groups each two users in a cluster is adopted to guarantee the system performance. The two users in a cluster transmit data simultaneously via NOMA, while time division multiple access (TDMA) is used among clusters. We aim to maximize the system throughput by finding the optimal cluster permutation and the optimal time allocation, which can be obtained by solving the optimization problems corresponding to all cluster permutations. The closed-form solution of each optimization problem is obtained by exploiting its constraint structures. However, the complexity of this exhaustive method is quite high, we further propose a sub-optimal clustering scheme with low complexity. The simulation results demonstrate the superiority of the proposed scheme.

We discuss our recent progress in photonic crystal nanocavity quantum dot lasers. We show how enhanced light matter interactions in the nanocavity lead to diverse and fascinating lasing phenomena that are in general inaccessible by conventional bulky semiconductor lasers. First, we demonstrate thresholdless lasing, in which any clear kink in the output laser curve does not appear. This is a result of near unity coupling of spontaneous emission into the lasing cavity mode, enabled by the strong Purcell effect supported in the nanocavity. Then, we discuss self-frequency conversion nanolasers, in which both near infrared lasing oscillation and nonlinear optical frequency conversion to visible light are simultaneously supported in the individual nanocavity. Owing to the tight optical confinement both in time and space, a high normalized conversion efficiency over a few hundred %/W is demonstrated. We also show that the intracavity nonlinear frequency conversion can be utilized to measure the statistics of the intracavity photons. These novel phenomena will be useful for developing various nano-optoelectronic devices with advanced functionalities.

Frequency chirp of a semiconductor laser is controlled by using hybrid modulation, which simultaneously modulates intra-cavity loss and injection current to the laser. The positive adiabatic chirp of injection-current modulation is compensated with the negative adiabatic chirp created by intra-cavity-loss modulation, which enhances the chromatic-dispersion tolerance of the laser. A proof-of-concept transmission experiment confirmed that the hybrid modulation laser has a larger dispersion tolerance than conventional directly modulated lasers due to the negative frequency chirp originating from intra-cavity-loss modulation.

A lens-integrated surface-emitting DFB laser and its application to low-cost single-mode optical sub-assemblies (OSAs) are discussed. By using the LISEL, high-efficient optical coupling with reduced number of optical components and non-hermetic packaging are demonstrated. Designing the integrated lens of LISELs makes it possible to achieve passive alignment optical coupling to an SMF without the need for an additional lens. For SiP coupling, the light-emission angle from the LISEL can be controlled by the mirror angle and by displacing the lens. The capability for a low coupling loss of 3.9 dB between the LISEL and a grating coupler on the SiP platform was demonstrated. The LISEL with facet-free structure, integrating DBR mirror, PD, and window structure on its end facet, showed the same lasing performance as the conventional laser with AR facet coating. A storage test (200-hour saturated pressure-cooker test (PCT) at 138°C and 85% RH.) showed that the lasing characteristics did not degrade with high-humidity, demonstrating the potential for applying non-hermetic packaging. Our results indicate that the LISEL is one of the promising light sources for creating cost-effective OSAs.

Virtual Machine Placement (VMP) plays an important role in ensuring efficient resource provisioning of physical machines (PMs) and energy efficiency in Infrastructure as a Service (IaaS) data centers. Efficient server consolidation assisted by virtual machine (VM) migration can promote the utilization level of the servers and switch the idle PMs to sleep mode to save energy. The trade-off between energy and performance is difficult, because consolidation may cause performance degradation, even service level agreement (SLA) violations. A novel residual available capacity (RAC) resource model is proposed to resolve the VM selection and allocation problem from the cloud service provider (CSP) perspective. Furthermore, a novel heuristic VM selection policy for server consolidation, named Minimized Square Root available Resource (MISR) is proposed. Meanwhile, an efficient VM allocation policy, named Balanced Selection (BS) based on RAC is proposed. The effectiveness validation of the BS-MISR combination is conducted on CloudSim with real workloads from the CoMon project. Evaluation results of experiments show that the proposed combinationBS-MISR can significantly reduce the energy consumption, with an average of 36.35% compared to the Local Regression and Minimum Migration Time (LR-MMT) combination policy. Moreover, the BS-MISR ensures a reasonable level of SLAs compared to the benchmarks.

This paper proposes a hardware configuration for uplink multi-user multiple-input multiple-output (MU-MIMO) transmissions in a distributed antenna system (DAS). The demand for high-speed transmission in the uplink has increased recently, because of which standardizations in LTE-advanced and IEEE 802.11ax networks is currently underway. User terminal (UT) scheduling on the downlink MU-MIMO transmission is easy even in unlicensed band such as those in wireless local area network (WLAN) systems. However, the detailed management of the UTs is difficult on the uplink MU-MIMO transmissions because of the decentralized wireless access control. The proposed configuration allows an antenna to be selected from an external device on the access point (AP). All AP antennas are divided into groups, and the received signal in each group is input to the amplitude detector via a directional coupler. Subsequently, the selected antenna is fed by a multiple-to-one switch instead of a matrix switch. To clarify the effectiveness of the proposed configuration, we conduct computer simulations based on the ray-tracing method for propagation channels in an indoor environment.

Geosocial networking allows users to interact with respect to their current locations, which enables a group of users to determine where to meet. This calls for techniques that support processing of Multiple-user Location-based Keyword (MULK) queries, which return a set of Point-of-Interests (POIs) that are 'close' to the locations of the users in a group and can provide them with potential options at the lowest expense (e.g., minimizing travel distance). In this paper, we formalize the MULK query and propose a dynamic programming-based algorithm to find the optimal result set. Further, we design two approximation algorithms to improve MULK query processing efficiency. The experimental evaluations show that our solutions are feasible and efficient under various parameter settings.