This work presents a novel counter-based randomization method for use in a flying-adder frequency synthesizer with a cost-effective structure that can replace the fractional accumulator. The proposed technique involves a counter, a comparator and a modified linear feedback shift register. The power consumption and speed bottleneck of the conventional flying-adder are significantly reduced. The modified linear shift feedback register is used as a pseudo random data generator, suppressing the spurious tones arise from the periodic carry sequences that is generated by the fractional accumulator. Furthermore, the proposed counter-based randomization method greatly reduces the large memory size that is required by the conventional approach to carry randomization. A test chip for the proposed counter-based randomization method is fabricated in the TSMC 0.18,$mu $m 1P6M CMOS process, with the core area of 0.093,mm$^{mathrm{2}}$. The output frequency had a range of 43.4,MHz, extasciitilde 225.8,MHz at 1.8,V with peak-to-peak jitter (Pk-Pk) jitter 139.2,ps at 225.8,MHz. Power consumption is 2.8,mW @ 225.8,MHz with 1.8 supply voltage.

Optimizing embedded software is a problem having scientific and practical signification. Optimizing embedded software can be done in different phases of the software life cycle under different optimal conditions. Most studies of embedded software optimization are done in forward engineering and these studies have not given an overall model for the optimization problem of embedded software in both forward engineering and reverse engineering. Therefore, in this paper, we propose a new approach to embedded software optimization based on reverse engineering. First, we construct an overall model for the embedded software optimization in both forward engineering and reverse engineering and present a process of embedded software optimization in reverse engineering. The main idea of this approach is that decompiling executable code to source code, converting the source code to models and optimizing embedded software under different levels such as source code and model. Then, the optimal source code is recompiled. To develop this approach, we present two optimization techniques such as optimizing power consumption of assembly programs based on instruction schedule and optimizing performance based on alternating equivalent expressions.

The number of states is a very important matter for model checking approach in Petri net's analysis. We first gave a formal definition of state number calculation problem: For a Petri net with an initial state (marking), how many states does it have? Next we showed the problem cannot be solved in polynomial time for a popular subclass of Petri nets, known as free choice workflow nets, if P≠NP. Then we proposed a polynomial time algorithm to solve the problem by utilizing a representational bias called as process tree. We also showed effectiveness of the algorithm through an application example.

Packet classification is a fundamental task in the control of network traffic, protection from cyber threats. Most layer 3 and higher network devices have a packet classification capability that determines whether to permit or discard incoming packets by comparing their headers with a set of rules. Although linear search is an intuitive implementation of packet classification, it is very inefficient. Srinivasan et al. proposed a novel lookup scheme using a hierarchical trie instead of linear search, which realizes faster packet classification with time complexity proportional to rule length rather than the number of rules. However, the hierarchical trie and its various improved algorithms allow only single prefix rules to be processed. Since it is necessary for layer 4 and higher packet classifications to deal with arbitrary bitmask rules in the hierarchical trie, we propose a run-based trie based on the hierarchical trie, but extended to deal with arbitrary bitmask rules. Our proposed algorithm achieves O((dW)2) query time and O(NdW) space complexity with N rules of length dW. The query time of our novel alrorithm doesn't depend on the number of rules. It solves the latency problem caused by increase of the rules in firewalls.

This paper proposes a novel greedy algorithm, called Creditability-Estimation based Matching Pursuit (CEMP), for the compressed sensing signal recovery. As proved in the algorithm of Stagewise Orthogonal Matching Pursuit (StOMP), two Gaussian distributions are followed by the matched filter coefficients corresponding to and without corresponding to the actual support set of the original sparse signal, respectively. Therefore, the selection for each support point is interpreted as a process of hypothesis testing, and the preliminarily selected support set is supposed to consist of rejected atoms. A hard threshold, which is controlled by an input parameter, is used to implement the rejection. Because the Type I error may happen during the hypothesis testing, not all the rejected atoms are creditable to be the true support points. The creditability of each preliminarily selected support point is evaluated by a well-designed built-in mechanism, and the several most creditable ones are adaptively selected into the final support set without being controlled by any extra external parameters. Moreover, the proposed CEMP does not necessitate the sparsity level to be a priori control parameter in operation. In order to verify the performance of the proposed algorithm, Gaussian and Pulse Amplitude Modulation sparse signals are measured in the noiseless and noisy cases, and the experiments of the compressed sensing signal recoveries by several greedy algorithms including CEMP are implemented. The simulation results show the proposed CEMP can achieve the best performances of the recovery accuracy and robustness as a whole. Besides, the experiment of the compressed sensing image recovery shows that CEMP can recover the image with the highest Peak Signal to Noise Ratio (PSNR) and the best visual quality.

In recent years, the time variation of Internet traffic has increased due to the growth of streaming and cloud services. Backbone networks must accommodate such traffic without congestion. Traffic engineering with traffic prediction is one approach to stably accommodating time-varying traffic. In this approach, routes are calculated from predicted traffic to avoid congestion, but predictions may include errors that cause congestion. We propose prediction-based traffic engineering that is robust against prediction errors. To achieve robust control, our method uses model predictive control, a process control method based on prediction of system dynamics. Routes are calculated so that future congestion is avoided without sudden route changes. We apply calculated routes for the next time slot, and observe traffic. Using the newly observed traffic, we again predict traffic and re-calculate the routes. Repeating these steps mitigates the impact of prediction errors, because traffic predictions are corrected in each time slot. Through simulations using backbone network traffic traces, we demonstrate that our method can avoid the congestion that the other methods cannot.

A feedback vertex set F of an undirected graph G is a vertex subset of G whose removal results in a forest. Such a set F is said to be independent if F forms an independent set of G. In this paper, we study the problem of finding an independent feedback vertex set of a given graph with the minimum number of vertices, from the viewpoint of graph classes. This problem is NP-hard even for planar bipartite graphs of maximum degree four. However, we show that the problem is solvable in linear time for graphs having tree-like structures, more specifically, for bounded treewidth graphs, chordal graphs and cographs. We then give a fixed-parameter algorithm for planar graphs when parameterized by the solution size. Such a fixed-parameter algorithm is already known for general graphs, but our algorithm is exponentially faster than the known one.

In this paper, we propose an analysis of broadcasting in the IEEE 802.11p MAC protocol. We consider multi-channel operation which is specifically designed for VANET (Vehicular Ad hoc Networks) applications. This protocol supports channel switching; the device alternates between the CCH (Control Channel) and the SCH (Service Channel) during the fixed synchronization interval. It helps vehicles with a single transceiver to access the CCH periodically during which time they acquire or broadcast safety-related messages. Confining the broadcasting opportunity to the deterministic CCH interval entails a non-typical approach to the analysis. Our analysis is carried out considering 1) the time dependency of the system behavior caused by the channel switching, 2) the mutual influence among the vehicles using a multi-dimensional stochastic process, and 3) the generation of messages distributed over the CCH interval. The proposed analysis enables the prediction of the successful delivery ratio and the delay of the broadcast messages. Furthermore, we propose a refinement of the analysis to take account of the effects of hidden nodes on the system performance. The simulation results show that the proposed analysis is quite accurate in describing both the delivery ratio and delay, as well as in reflecting the hidden node effects. The benefits derived from the distributed generation of traffic are also evidenced by the results of experiments.

Developing a practical and accurate statistical parser for low-resourced languages is a hard problem, because it requires large-scale treebanks, which are expensive and labor-intensive to build from scratch. Unsupervised grammar induction theoretically offers a way to overcome this hurdle by learning hidden syntactic structures from raw text automatically. The accuracy of grammar induction is still impractically low because frequent collocations of non-linguistically associable units are commonly found, resulting in dependency attachment errors. We introduce a novel approach to building a statistical parser for low-resourced languages by using language parameters as a guide for grammar induction. The intuition of this paper is: most dependency attachment errors are frequently used word orders which can be captured by a small prescribed set of linguistic constraints, while the rest of the language can be learned statistically by grammar induction. We then show that covering the most frequent grammar rules via our language parameters has a strong impact on the parsing accuracy in 12 languages.

Syndrome key equation solution is one of the important processes in the decoding of Reed-Solomon codes. This paper proposes a low power key equation solver (KES) architecture where the power consumption is reduced by decreasing the required number of multiplications without degrading the decoding throughput and latency. The proposed method employs smaller number of multipliers than a conventional low power KES architecture. The critical path in the proposed KES circuit is minimized so that the operation at a high clock frequency is possible. A low power folded KES architecture is also proposed to further reduce the hardware complexity by executing folded operations in a pipelined manner with a slight increase in decoding latency.

This paper presents a novel peer-to-peer protocol to efficiently distribute virtual machine images in a datacenter. A primary idea of it is to improve the performance of peer-to-peer content delivery by employing deduplication to take advantage of similarity both among and within VM images in cloud datacenters. The efficacy of the proposed scheme is validated through an evaluation that demonstrates substantial performance gains.

In this paper, we report our analysis of path loss variation characteristics in the low millimeter wave band based on measurement results obtained by using 26.365GHz. We analyze the fading scale of the measurement results by applying a wavelet analysis method. It is clarified that a fading of unique scale between the scale of fast fading and shadowing can be seen in the low millimeter band. Finally, it is shown that the variation characteristics can be evaluated by taking reflection paths at building walls into account, in addition to the ground waves and LOS paths.

An on-channel repeater (OCR) performing simultaneous reception and transmission at the same frequency is beneficial to improve spectral efficiency and coverage. In an OCR, it is important to cancel the feedback interference caused by imperfect isolation between the transmit and receive antennas, and least mean square (LMS) based adaptive filters are commonly used for this purpose. In this paper, we analyze the performance of the LMS based adaptive feedback canceller in terms of its transient behavior and the steady-state mean square error (MSE). Through a theoretical analysis, we derive iterative equations to compute transient MSEs and provide a procedure to simply evaluate steady-state MSEs for the adaptive feedback canceller. Simulation results performed to verify the theoretical MSEs show good agreement between the proposed theoretical analysis and the empirical results.

Satellite clusters have been satisfactorily implemented in a number of applications, such as positioning and sensor networks, with the purpose of improving communication system capabilities. However, because the use of clusters requires good management of the resources, those solutions imply new challenges for communication systems. This paper focuses on improving the data management between network elements by considering a network formed by satellite clusters. Satellite clusters work in cooperation to provide real-time and non-real-time services in different footprint areas. This study proposes the adjustable energy consumption access scheme (AECS) as one possible solution response to particular necessities of communication and at the same time, as a way of decreasing the system energy consumption. Energy consumption is a key issue that concerns green network operations and it is directly linked to the cooperation and coordination between network elements. On the other hand, we support the implementation of Optical Inter-Satellite Links (OISL) for communication between cluster elements. The analysis involves the study of energy consumption, transmission delay, specific link margins, bit error rate (BER) and QoS.

This manuscript presents a simple scheme to improve the performance of a feedback control system that uses power line channels for its feedback loop. The noise and attenuation of power lines, and thus the signal to noise ratio, are known to be cyclostationary. Such cyclic features in the channel allow us to predict virtually error free transmission instants as well as instants of high probability of errors. This paper introduces and evaluates the effectiveness of a packet transmission scheduling that collaborates with a predictive control scheme adapted to this cyclostationary environment. In other words, we explore the cooperation between the physical and application layers of the system in order to achieve an overall optimization. To rate the control quality of the system we evaluate its stability as well as its ability to follow control commands accurately. We compare a scheme of increased packet rate against our proposed scheme which emulates a high packet rate with the use of predictive control. Through this comparison, we verify the effectiveness of the proposed scheme to improve the control quality of the system, even under low signal to noise ratio conditions in the cyclostationary channel.

A rotating shaft with attached sensors is wrapped in a two-dimensional waveguide sheet through which the data and power are wirelessly transmitted. A retrodirective transponder array affixed to the sheet beamforms power to the moving sensor to eliminate the need for a battery. A universal on-sheet reference scheme is proposed for calibrating the transponder circuit delay variation and eliminating a crystal oscillator from the sensor. A base signal transmitted from the on-sheet reference device is used for generating the pilot signal transmitted from the sensor and the power signal transmitted from the transponder. A 0.18-µm CMOS transponder chip and the sheet with couplers were fabricated. The coupler has three resonant frequencies used for the proposed system. The measured propagation gain of the electric field changes to less than ±1.5dB within a 2.0-mm distance between the coupler and the sheet. The measured power transmission efficiency with beamforming is 23 times higher than that without it. Each transponder outputs 1W or less for providing 3mW to the sensor.

Implicit feedback is an approach that utilizes uplink channel state information (CSI) for downlink transmit beamforming on multiple-input multiple-output (MIMO) systems, relying on over-the-air channel reciprocity. The implicit feedback improves throughput efficiency because overhead of CSI feedback for change of over-the-air channel responses is omitted. However, it is necessary for the implicit feedback to calibrate circuitry responses that uplink CSI includes, because actual downlink and uplink channel responses do not match due to different transmit and receive circuitry chains. This paper presents our proposed calibration scheme, weighted-combining calibration (WCC); it offers improved calibration accuracy. In WCC, an access point (AP) calculates multiple calibration coefficients from ratios of downlink and uplink CSI, and then combines coefficients with minimum mean square error (MMSE) weights. The weights are derived using a linear approximation in the high signal to noise power ratio (SNR) regime. Analytical mean square error (MSE) of calibration coefficients with WCC and calibration schemes for comparison is expressed based on the linear approximation. Computer simulations show that the analytical MSE matches simulated one if the linear approximation holds, and that WCC improves the MSE and signal to interference plus noise power ratio (SINR). Indoor experiments are performed on a multiuser MIMO system with implicit feedback based on orthogonal frequency division multiplexing (OFDM), built using measurement hardware. Experimental results verify that the channel reciprocity can be exploited on the developed multiuser MIMO-OFDM system and that WCC is also effective in indoor environments.

Large-scale content transfer, especially video transfer, is now a dominant traffic component in the Internet. Originally, content transfer had a content-oriented feature, i.e., “Users do not care where content is retrieved. Users only take care of what content they obtain.” Conventional traffic engineering (TE) aims to obtain optimal routes for traffic between ingress and egress router pairs, i.e., TE has focused on a location-oriented approach that takes care of where to connect. With increased demand for content-oriented features for content traffic, TE needs to focus on content-oriented routing design. In this study, we therefore propose a novel approach to content-oriented TE, called content aware routing (CAR). In CAR, routes are designed for content and egress router pairs, i.e., content traffic toward a receiver-side router. Content demand can be flexibly distributed to multiple servers (i.e., repositories) providing the same content, meaning that content can be obtained from anywhere. CAR solves the optimization problem of minimizing maximum link utilization. If there are multiple optimal solutions, CAR selects a solution in which resource usage is minimized. Using numerical examples formulated by the linear programming problem, we evaluated CAR by comparing it with combinations of conventional content delivery networks and TE, i.e., location-oriented designs. Our numerical results showed that CAR improved maximum link utilization by up to 15%, with only a 5% increase of network resource usage.

Radio Frequency based Device-Free Localization (RFDFL) is an emerging localization technique without requirements of attaching any electronic device to a target. The target can be localized by means of measuring the shadowing of received signal strength caused by the target. However, the accuracy of RFDFL deteriorates seriously in environment with WiFi interference. State-of-the-art methods do not efficiently solve this problem. In this paper, we propose a dual-band method to improve the accuracy of RFDFL in environment without/with severe WiFi interference. We introduce an algorithm of fusing dual-band images in order to obtain an enhanced image inferring more precise location and propose a timestamp-based synchronization method to associate the dual-band images to ensure their one-one correspondence. With real-world experiments, we show that our method outperforms traditional single-band localization methods and improves the localization accuracy by up to 40.4% in real indoor environment with high WiFi interference.

In retinal blood vessel extraction through background removal, the vessels in a fundus image which appear in a higher illumination variance area are often missing after the background is removed. This is because the intensity values of the vessel and the background are nearly the same. Thus, the estimated background should be robust to changes of the illumination intensity. This paper proposes retinal blood vessel extraction using background estimation. The estimated background is calculated by using a weight surface fitting method with a high degree polynomial. Bright pixels are defined as unwanted data and are set as zero in a weight matrix. To fit a retinal surface with a higher degree polynomial, fundus images are reduced in size by different scaling parameters in order to reduce the processing time and complexity in calculation. The estimated background is then removed from the original image. The candidate vessel pixels are extracted from the image by using the local threshold values. To identify the true vessel region, the candidate vessel pixels are dilated from the candidate. After that, the active contour without edge method is applied. The experimental results show that the efficiency of the proposed method is higher than the conventional low-pass filter and the conventional surface fitting method. Moreover, rescaling an image down using the scaling parameter at 0.25 before background estimation provides as good a result as a non-rescaled image does. The correlation value between the non-rescaled image and the rescaled image is 0.99. The results of the proposed method in the sensitivity, the specificity, the accuracy, the area under the receiver operating characteristic (ROC) curve (AUC) and the processing time per image are 0.7994, 0.9717, 0.9543, 0.9676 and 1.8320 seconds for the DRIVE database respectively.