In this paper, we propose a Mobile Edge Internet of Things (MEIoT) architecture by leveraging the fiber-wireless access technology, the cloudlet concept, and the software defined networking framework. The MEIoT architecture brings computing and storage resources close to Internet of Things (IoT) devices in order to speed up IoT data sharing and analytics. Specifically, the IoT devices (belonging to the same user) are associated to a specific proxy Virtual Machine (VM) in the nearby cloudlet. The proxy VM stores and analyzes the IoT data (generated by its IoT devices) in real-time. Moreover, we introduce the semantic and social IoT technology in the context of MEIoT to solve the interoperability and inefficient access control problem in the IoT system. In addition, we propose two dynamic proxy VM migration methods to minimize the end-to-end delay between proxy VMs and their IoT devices and to minimize the total on-grid energy consumption of the cloudlets, respectively. Performance of the proposed methods is validated via extensive simulations.

This letter presents two outage-optimal relaying schemes to improve the performance of a wireless energy harvesting system in cognitive radio networks. The performance of both schemes is then evaluated and compared by carrying out numerical simulations, and we also derive the analytic expression for the outage probability of the secondary system.

Modern FPGAs have been integrated in computing systems as accelerators for long running applications. This integration puts more pressure on the fault tolerance of computing systems, and the requirement for dependability becomes essential. As in the case of CPU-based system, checkpoint/restart techniques are also expected to improve the dependability of FPGA-based computing. Three issues arise in this situation: how to checkpoint and restart FPGAs, how well this checkpoint/restart model works with the checkpoint/restart model of the whole computing system, and how to build the model by a software tool. In this paper, we first present a new checkpoint/restart architecture along with a checkpointing mechanism on FPGAs. We then propose a method to capture consistent snapshots of FPGA and the rest of the computing system. Third, we provide “fine-grained” management for checkpointing to reduce performance degradation. For the host CPU, we also provide a stack which includes API functions to manage checkpoint/restart procedures on FPGAs. Fourth, we present a Python-based tool to insert checkpointing infrastructure. Experimental results show that the checkpointing architecture causes less than 10% maximum clock frequency degradation, low checkpointing latencies, small memory footprints, and small increases in power consumption, while the LUT overhead varies from 17.98% (Dijkstra) to 160.67% (Matrix Multiplication).

To efficiently use network resources, internet service providers need to conduct traffic engineering that dynamically controls traffic routes to accommodate traffic change with limited network resources. The performance of traffic engineering (TE) depends on the accuracy of traffic prediction. However, the size of traffic change has been drastically increasing in recent years due to the growth in various types of network services, which has made traffic prediction difficult. Our approach to tackle this issue is to separate traffic into predictable and unpredictable parts and to apply different control policies. However, there are two challenges to achieving this: dynamically separating traffic according to predictability and dynamically controlling routes for each separated traffic part. In this paper, we propose a macroflow-based TE scheme that uses different routing policies in accordance with traffic predictability. We also propose a traffic-separation algorithm based on real-time traffic analysis and a framework for controlling separated traffic with software-defined networking technology, particularly OpenFlow. An evaluation of actual traffic measured in an Internet2 network shows that compared with current TE schemes the proposed scheme can reduce the maximum link load by 34% (at the most congested time) and the average link load by an average of 11%.

Considering that different people are different in their linguistic preference and in order to determine the consensus state when using Computing with Words (CWW) for supporting consensus decision making, this paper first proposes an interval composite scale based 2-tuple linguistic model, which realizes the process of translation from word to interval numerical and the process of retranslation from interval numerical to word. Second, this paper proposes an interval composite scale based personalized individual semantics model (ICS-PISM), which can provide different linguistic representation models for different decision-makers. Finally, this paper proposes a consensus decision making model with ICS-PISM, which includes a semantic translation and retranslation phase during decision process and determines the consensus state of the whole decision process. These models proposed take into full consideration that human language contains vague expressions and usually real-world preferences are uncertain, and provide efficient computation models to support consensus decision making.

Concurrent transmission (CT) is a revolutionary multi-hop protocol that significantly improves the MAC- and network-layer efficiency by allowing synchronized packet collisions. Although its superiority has been empirically verified, there is still a lack of studies on how the receiver survives such packet collisions, particularly in the presence of the carrier frequency offsets (CFO) between the transmitters. This work rectifies this omission by providing a comprehensive evaluation of the physical-layer receiver performance under CT, and a theoretical analysis on the fading duration of the beating effect resulting from the CFO. The main findings from our evaluations are the following points. (1) Beating significantly affects the receiver performance, and an error correcting mechanism is needed to combat the beating. (2) In IEEE 802.15.4 systems, the direct sequence spread spectrum (DSSS) plays such a role in combatting the beating. (3) However, due to the limited length of DSSS, the receiver still suffers from the beating if the fading duration is too long. (4) On the other hand, the basic M-ary FSK mode of IEEE 802.15.4g is vulnerable to CT due to the lack of error correcting mechanism. In view of the importance of the fading duration, we further theoretically derive the closed form of the average fading duration (AFD) of the beating under CT in terms of the transmitter number and the standard deviation of the CFO. Moreover, we prove that the receiver performance can be improved by having higher CFO deviations between the transmitters due to the shorter AFD. Finally, we estimate the AFD in the real system by actually measuring the CFO of a large number of sensor nodes.

A ripple-free dual-rate control system is designed for a single-input single-output dual-rate system, in which the sampling interval of a plant output is longer than the holding interval of a control input. The dual-rate system is converged to a multi-input single-output single-rate system using the lifting technique, and a control system is designed based on an error system using the steady-state variable. Because the proposed control law is designed so that the control input is constant in the steady state, the intersample output as well as the sampled output converges to the set-point without both steady-state error and intersample ripples when there is neither modeling nor disturbance. Furthermore, in the proposed method, a two-degree-of-freedom integral compensation is designed, and hence, the transient response is not deteriorated by the integral action because the integral action is canceled when there is neither modeling nor disturbance. Moreover, in the presence of the modeling error or disturbance, the integral compensation is revealed, and hence, the steady-state error is eliminated on both the intersample and sampled response.

This paper proposes a fast safe-region generation method for several kinds of vicinity queries including set k nearest neighbor (NN) queries, ordered kNN queries, reverse kNN queries, and distance range queries. When a user is driving a car on a road network, he/she wants to know about objects located in the vicinity of the car. However, the result changes according to the movement of the car, and therefore, the user needs to request up-to-date result to the server. On the other hand, frequent requests for up-to-date results cause heavy loadings on the server. To cope with this problem efficiently, the idea of the safe-region has been proposed, however, it takes long processing time in existing works. This paper proposes a fast generation method of the safe-region applicable to several types of vicinity queries. Through experimental evaluations, we demonstrate that the proposed method outperforms the existing algorithms in the processing time by one or two orders of magnitude.

In this letter, we study a scenario based on decoupled RF energy harvesting networks (DRF-EHNs) that separate energy sources from information sources to overcome the doubly near-far problem and improve harvesting efficiency. We propose an algorithm to maximize energy efficiency (EE) while satisfying constraints on the maximum transmit power of the hybrid access point (H-AP) and power beacon (PB), while further satisfying constraints on the minimum quality of service and minimum amount of harvested power in multi-user Rayleigh fading channel. Using nonlinear fractional programming and Lagrangian dual decomposition, we optimize EE with four optimization arguments: the transmit power from the H-AP and PB, time-splitting ratio, and power-splitting ratio. Numerical results show that the proposed algorithm is more energy-efficient compared to baseline schemes.

The Transmission Control Protocol (TCP) with Network Coding (TCP/NC) was proposed to introduce packet loss recovery ability at the sink without TCP retransmission, which is realized by proactively sending redundant combination packets encoded at the source. Although TCP/NC is expected to mitigate the goodput degradation of TCP over lossy networks, the original TCP/NC does not work well in burst loss and time-varying channels. No apparent scheme was provided to decide and change the network coding-related parameters (NC parameters) to suit the diverse and changeable loss conditions. In this paper, a solution to support TCP/NC in adapting to mentioned conditions is proposed, called TCP/NC with Loss Rate and Loss Burstiness Estimation (TCP/NCwLRLBE). Both the packet loss rate and burstiness are estimated by observing transmitted packets to adapt to burst loss channels. Appropriate NC parameters are calculated from the estimated probability of successful recoverable transmission based on a mathematical model of packet losses. Moreover, a new mechanism for coding window handling is developed to update NC parameters in the coding system promptly. The proposed scheme is implemented and validated in Network Simulator 3 with two different types of burst loss model. The results suggest the potential of TCP/NCwLRLBE to mitigate the TCP goodput degradation in both the random loss and burst loss channels with the time-varying conditions.

Wireless Sensor Networks (WSNs) are randomly deployed in a hostile environment and left unattended. These networks are composed of small auto mouse sensor devices which can monitor target information and send it to the Base Station (BS) for action. The sensor nodes can easily be compromised by an adversary and the compromised nodes can be used to inject false vote or false report attacks. To counter these two kinds of attacks, the Probabilistic Voting-based Filtering Scheme (PVFS) was proposed by Li and Wu, which consists of three phases; 1) Key Initialization and assignment, 2) Report generation, and 3) En-route filtering. This scheme can be a successful countermeasure against these attacks, however, when one or more nodes are compromised, the re-distribution of keys is not handled. Therefore, after a sensor node or Cluster Head (CH) is compromised, the detection power and effectiveness of PVFS is reduced. This also results in adverse effects on the sensor network's lifetime. In this paper, we propose a Fuzzy Rule-based Key Redistribution Method (FRKM) to address the limitations of the PVFS. The experimental results confirm the effectiveness of the proposed method by improving the detection power by up to 13.75% when the key-redistribution period is not fixed. Moreover, the proposed method achieves an energy improvement of up to 9.2% over PVFS.

Seed detection or sometimes known as nuclei detection is a prerequisite step of nuclei segmentation which plays a critical role in quantitative cell analysis. The detection result is considered as accurate if each detected seed lies only in one nucleus and is close to the nucleus center. In previous works, voting methods are employed to detect nucleus center by extracting the nucleus saliency features. However, these methods still encounter the risk of false seeding, especially for the heterogeneous intensity images. To overcome the drawbacks of previous works, a novel detection method is proposed, which is called secant normal voting. Secant normal voting achieves good performance with the proposed skipping range. Skipping range avoids over-segmentation by preventing false seeding on the occlusion regions. Nucleus centers are obtained by mean-shift clustering from clouds of voting points. In the experiments, we show that our proposed method outperforms the comparison methods by achieving high detection accuracy without sacrificing the computational efficiency.

Transient scattering by a metal cylinder covered with inhomogeneous lossy material is analyzed for application of radar systems to nondestructive testing of reinforced concrete structures. First, inhomogeneous lossy material that is a model of corrosion by rust is approximated by a cylindrical multilayered medium, and analytic solution of a scattered field in frequency domain is derived. Next, time domain scattering response is calculated from the frequency domain data by using the inverse Fourier transform. Numerical results of pulse responses indicate that corrosion rate of the concrete can be evaluated by checking the waveform distortion of the pulse responses.

To aim to achieve a high-performance computation for microwave simulations with low cost, small size machine and low energy consumption, a method of the FDTD dedicated computer has been investigated. It was shown by VHDL logical circuit simulations that the FDTD dedicated computer with a dataflow architecture has much higher performance than that of high-end PC and GPU. Then the remaining task of this work is large scale computations by the dedicated computer, since microwave simulations for only 18×18×Z grid space (Z is the number of girds for z direction) can be executed in a single FPGA at most. To treat much larger numerical model size for practical applications, this paper considers an implementation of a domain decomposition method operation of the FDTD dedicated computer in a single FPGA.

In recent years, software-defined networking (SDN), which performs centralized network management with software, has attracted much attention. Although packets are transmitted based on flow entries in SDN switches, the number of flow entries that the SDN switches can handle is limited. To overcome this difficulty, this paper proposes a flow-based routing method that performs flexible routing control with a small number of flow entries. The proposed method provides mixed integer programming. It assigns common paths to flows that can be aggregated at intermediate switches, while considering the utilization of network links. Because it is difficult for mixed integer programming to compute large-scale problems, the proposed method also provides a heuristic algorithm for them. Through numerical experiments, this paper shows that the proposed method efficiently reduces both the number of flow entries and the loads of congested links.

The study of universal detector for fingerprinting code is strongly dependent on the design of scoring function. The optimal detector is known as MAP detector that calculates an optimal correlation score for a given single user's codeword. However, the knowledge about the number of colluders and their collusion strategy are inevitable. In this paper, we propose a new scoring function that equalizes the bias between symbols of codeword, which is called bias equalizer. We further investigate an efficient scoring function based on the bias equalizer under the relaxed marking assumption such that white Gaussian noise is added to a pirated codeword. The performance is compared with the MAP detector as well as some state-of-the-art scoring functions.

This paper reports the development of a landmine visualization system based on complex-valued self-organizing map (CSOM) by employing one-dimensional (1-D) array of taper-walled tapered slot antennas (TSAs). Previously we constructed a high-density two-dimensional array system to observe and classify complex-amplitude texture of scattered wave. The system has superiority in its adaptive distinction ability between landmines and other clutters. However, it used so many (144) antenna elements with many mechanical radio-frequency (RF) switches and cables that it has difficulty in its maintenance and also requires long measurement time. The 1-D array system proposed here uses only 12 antennas and adopts electronic RF switches, resulting in easy maintenance and 1/4 measurement time. Though we observe stripe noise specific to this 1-D system, we succeed in visualization with effective solutions.

Multilinear maps have lots of cryptographic applications including multipartite key exchange and indistinguishability obfuscations. Since the concept of multilinear map was suggested, three kinds of candidate multilinear maps are constructed. However, the security of multilinear maps suffers from various attacks. In this paper, we overview suggested multilinear maps and cryptanalysis of them in diverse cases.

In this paper, we theoretically analyse the influence of intersymbol interference (ISI) and continuous wave interference (CWI) on the bit error rate (BER) performance of the spread spectrum (SS) system using a real-valued Huffman sequence under the additive white Gaussian noise (AWGN) environment. The aperiodic correlation function of the Huffman sequence has zero sidelobes except the shift-end values at the left and right ends of shift. The system can give the unified communication and ranging system because the output of a matched filter (MF) is the ideal impulse by generating transmitted signal of the bit duration T=NTc, N=2n, n=1,2,… from the sequence of length M=2kN+1, k=0,1,…, where Tc is the chip duration and N is the spreading factor. As a result, the BER performance of the system is improved with decrease in the absolute value of the shift-end value, and is not influenced by ISI if the shift-end value is almost zero-value. In addition, the BER performance of the system of the bit duration T=NTc with CWI is improved with increase in the sequence length M=2kN+1, and the system can decrease the influence of CWI.

This paper describes a parametric representation of ultra-wideband radar signatures and its physical interpretation. Under the scattering theory of electromagnetic waves, a transfer function of radar scattering is factorized into three elementary parts and a radar signature with three parameters is derived. To use these parameters for radar target classification and identification, the relation between them and the response waveform is analytically revealed and numerically checked. The result indicates that distortion of the response waveform is sensitive to these parameters, and thus they can be expected to be used as features for radar target classification and identification.