A novel watermarked MDC system based on the SFQ algorithm and the sub-sampling method is proposed in this paper. Sub-sampling algorithm is applied onto the transformed image to introduce some redundancy between different channels. Secret information is embedded into the preprocessed sub-images. Good performance of the new system to defense the noise and the compression attacks is shown in the experimental results.

In this correspondence, we devise a new method for constructing a ternary column sequence set of length 3m+1-1 form ternary sequences of period 3m-1 with ideal autocorrelation, and the ternary LCZ sequence set of period 3n-1 is constructed by using the column sequence set when (m+1)|n. In addition, the method is popularized to the p-ary LCZ sequence. The resultant LCZ sequence sets in this paper are optimal with respect to the Tang-Fan-Matsufuji bound.

Considerable effort has been devoted to minimizing XPath queries under the assumption that the minimal query is faster than the original query. However, little attention has been paid to the validity of the assumption. In this paper, we provide a detailed analysis on the effectiveness of XPath query minimization and present an extensive experimental evaluation on the effectiveness using six publicly available XQuery engines. To the best of our knowledge, this is the first work done towards this objective. Experiments on real and synthetic data sets show that although the assumption is valid for some cases, the performance of the minimal query is often lower than or almost equal to that of the original query.

The wireless sensor network (WSN) is a technology that senses environmental information and provides appropriate services to users. There are diverse application areas for WSNs such as disaster prevention, military, and facility management. Despite the many prospective applications, WSN s are vulnerable to various malicious attacks. In false report attacks, a malicious attacker steals a few sensor nodes and obtains security materials such as authentication keys from the nodes. The attacker then injects false event reports to the network through the captured nodes. The injected false reports confuse users or deplete the limited energy of the nodes in the network. Many filtering schemes have been proposed to detect and remove false reports. In the statistical en route filtering (SEF) scheme, each node shares authentication keys selected from a global key pool. Due to the limited memory, each node is able to store only a small portion of the global key pool. Therefore, the routing paths of the event reports significantly affect the filtering (i.e., detecting) probability of false reports. In this paper, we propose a method to determine the routing paths of event reports both hop by hop and on demand at each node. In this method, each node chooses the next node on the path from the event source to the sink node based on the key indexes of its neighbor nodes. Experiments show that the proposed method is far more energy efficient than the SEF when the false traffic ratio (FTR) is ≥ 50% in the network.

In this letter, a quantization error-aware Tomlinson-Harashinma Precoding (THP) is proposed based on the equivalent zero-forcing (ZF) criterion in Multiuser Multiple-Input Single-Output (MU-MISO) systems with limited feedback, where the transmitter has only quantized channel direction information (CDI). This precoding scheme is robust to the channel uncertainties arising from the quantization error and the lack of channel magnitude information (CMI). Our simulation results show that the new THP scheme outperforms the conventional precoding scheme in limited feedback systems with respect to Bit Error Ratio (BER).

Hovering unmanned aerial vehicles (UAVs) with mutual sense and communication capability form a new-fashioned airborne ad hoc network. Traditional routing protocols assume that there has already existed an end-to-end path before the message forwarding starts which, however, is not always available in the airborne network featuring randomly violent topological changes. Local heuristic information without complex computational cost should be considered to help route in this specific delay tolerant network (DTN). In this letter, we take Crowd Density (CD) and Relative Velocity Direction (RVD) as the fuzzy inputs, and use approximate reasoning to calculate priority of alternative candidates. Finally, the proposed mechanism is compared with some existing protocols.

In this letter a general admission control strategy is proposed and mathematically analyzed. Fractional buffering finely adjusts different QoS metrics allowing them to simultaneously achieve their maximum acceptable values, maximizing system capacity. Fractional buffering also allows the adequate and fair performance comparison among different resource management strategies and/or evaluation scenarios.

This letter proposes a simple heuristic to identify the discrete-time switched autoregressive exogenous (SARX) systems. The goal of the identification is to identify the switching sequence and the system parameters of all submodels simultaneously. In this letter the SARX system identification problem is formulated as the l0 norm minimization problem, and an iterative algorithm is proposed by applying the reweighted least squares technique. Although the proposed algorithm is heuristic, the numerical examples show its efficiency and robustness for noise.

This letter proposes a reuse method of unit test cases, which characterize internal behaviors of a called function, for enhancing capability of automatic generation of test cases. Existing test case generation tools have limits in finding solutions to the deep call structure of the source code. In our approach, the complex call structure is simplified by reusing unit test cases of called functions. As unit test cases represent the characteristics of the called function, the internal behaviors of called functions are replaced by the test cases. This approach can be applicable to existing test tools for simplifying the process of generation and enhancing their capabilities.

We present attacks on the generalized Feistel schemes, where each round function consists of a subkey XOR, S-boxes, and then a linear transformation (i.e. a Substitution-Permutation (SP) round function). Our techniques are based on rebound attacks. We assume that the S-boxes have a good differential property and the linear transformation has an optimal branch number. Under this assumption, we firstly describe known-key distinguishers on the type-1, -2, and -3 generalized Feistel schemes up to 21, 13 and 8 rounds, respectively. Then, we use the distinguishers to make several attacks on hash functions where Merkle-Damgård domain extender is used and the compression function is constructed with Matyas-Meyer-Oseas or Miyaguchi-Preneel hash modes from generalized Feistel schemes. Collision attacks are made for 11 rounds of type-1 Feistel scheme. Near collision attacks are made for 13 rounds of type-1 Feistel scheme and 9 rounds of type-2 Feistel scheme. Half collision attacks are made for 15 rounds of type-1 Feistel scheme, 9 rounds of type-2 Feistel scheme, and 5 rounds of type-3 Feistel scheme.

Non-negative matrix factorization (NMF) is widely used for music transcription because of its efficiency. However, the conventional NMF-based music transcription algorithm often causes harmonic confusion errors or time split-up errors, because the NMF decomposes the time-frequency data according to the activated frequency in its time. To solve these problems, we proposed an NMF with temporal continuity and harmonicity constraints. The temporal continuity constraint prevented the time split-up of the continuous time components, and the harmonicity constraint helped to bind the fundamental with harmonic frequencies by reducing the additional octave errors. The transcription performance of the proposed algorithm was compared with that of the conventional algorithms, which showed that the proposed method helped to reduce additional false errors and increased the overall transcription performance.

Large-signal-based nonlinear models are developed to analyze a variety of dynamic performances in a resonant tunneling diode (RTD) with peripheral circuits such as an integrated broad band bow-tie antenna, a bias circuit and a bias stabilizer circuit. Dynamic modes of the RTD are classified by the time-domain analysis with the model. On the basis of our model, we suggest a possibility to discuss a terahertz order oscillation mode control, and the ASK modulation in several tens Gbit/sec in the RTD with the broad band antenna. Validity of the model and analysis is shown by explaining measured results of modulated oscillation signals in fabricated triple-barrier RTDs.

This paper proposes a novel dynamic Scratch-pad Memory allocation strategy to optimize the energy consumption of the memory sub-system. Firstly, the whole program execution process is sliced into several time slots according to the temporal dimension; thereafter, a Time-Slotted Cache Conflict Graph (TSCCG) is introduced to model the behavior of Data Cache (D-Cache) conflicts within each time slot. Then, Integer Nonlinear Programming (INP) is implemented, which can avoid time-consuming linearization process, to select the most profitable data pages. Virtual Memory System (VMS) is adopted to remap those data pages, which will cause severe Cache conflicts within a time slot, to SPM. In order to minimize the swapping overhead of dynamic SPM allocation, a novel SPM controller with a tightly coupled DMA is introduced to issue the swapping operations without CPU's intervention. Last but not the least, this paper discusses the fluctuation of system energy profit based on different MMU page size as well as the Time Slot duration quantitatively. According to our design space exploration, the proposed method can optimize all of the data segments, including global data, heap and stack data in general, and reduce the total energy consumption by 27.28% on average, up to 55.22% with a marginal performance promotion. And comparing to the conventional static CCG (Cache Conflicts Graph), our approach can obtain 24.7% energy profit on average, up to 30.5% with a sight boost in performance.

Recently, server virtualization technology, which is one of the key technologies to support cloud computing, has been making progress and gaining in maturity, resulting in an increase in the provision of cloud-based services and the integration of servers in enterprise networks. However, the progress in network virtualization technology, which is needed for the efficient and effective construction and operation of clouds, is lagging behind. It is only recently that all the required technical areas have started to be covered. This paper identifies network-related issues in cloud environments, describes the needs for network virtualization, and presents the recent trends in, and application fields of, network virtualization technology.

A conical area evolutionary algorithm (CAEA) is presented to further improve computational efficiencies of evolutionary algorithms for bi-objective optimization. CAEA partitions the objective space into a number of conical subregions and then solves a scalar subproblem in each subregion that uses a conical area indicator as its scalar objective. The local Pareto optimality of the solution with the minimal conical area in each subregion is proved. Experimental results on bi-objective problems have shown that CAEA offers a significantly higher computational efficiency than the multi-objective evolutionary algorithm based on decomposition (MOEA/D) while CAEA competes well with MOEA/D in terms of solution quality.

Dynamic resource management has become an active area of research in the Cloud Computing paradigm. Cost of resources varies significantly depending on configuration for using them. Hence efficient management of resources is of prime interest to both Cloud Providers and Cloud Users. In this work we suggest a probabilistic resource provisioning approach that can be exploited as the input of a dynamic resource management scheme. Using a Video on Demand use case to justify our claims, we propose an analytical model inspired from standard models developed for epidemiology spreading, to represent sudden and intense workload variations. We show that the resulting model verifies a Large Deviation Principle that statistically characterizes extreme rare events, such as the ones produced by “buzz/flash crowd effects” that may cause workload overflow in the VoD context. This analysis provides valuable insight on expectable abnormal behaviors of systems. We exploit the information obtained using the Large Deviation Principle for the proposed Video on Demand use-case for defining policies (Service Level Agreements). We believe these policies for elastic resource provisioning and usage may be of some interest to all stakeholders in the emerging context of cloud networking.

Clock gating is supported by commercial tools as a power optimization feature based on the guard signal described in HDL (structural method). However, the identification of control signals for gated registers is hard and designer-intensive work. Besides, since the clock gating cells also consume power, it is imperative to minimize the number of inserted clock gating cells and their switching activities for power optimization. In this paper, we propose an automatic multi-stage clock gating algorithm with ILP (Integer Linear Programming) formulation, including clock gating control candidate extraction, constraints construction and optimum control signal selection. By multi-stage clock gating, unnecessary clock pulses to clock gating cells can be avoided by other clock gating cells, so that the switching activity of clock gating cells can be reduced. We find that any multi-stage control signals are also single-stage control signals, and any combination of signals can be selected from single-stage candidates. The proposed method can be applied to 3 or more cascaded stages. The multi-stage clock gating optimization problem is formulated as constraints in LP format for the selection of cascaded clock-gating order of multi-stage candidate combinations, and a commercial ILP solver (IBM CPLEX) is applied to obtain the control signals for each register with minimum switching activity. Those signals are used to generate a gate level description with guarded registers from original design, and a commercial synthesis and layout tools are applied to obtain the circuit with multi-stage clock gating. For a set of benchmark circuits and a Low Density Parity Check (LDPC) Decoder (6.6k gates, 212 F.F.s), the proposed method is applied and actual power consumption is estimated using Synopsys NanoSim after layout. On average, 31% actual power reduction has been obtained compared with original designs with structural clock gating, and more than 10% improvement has been achieved for some circuits compared with single-stage optimization method. CPU time for optimum multi-stage control selection is several seconds for up to 25k variables in LP format. By applying the proposed clock gating, area can also be reduced since the multiplexors controlling register inputs are eliminated.

This letter proposes a new image colorization algorithm based on the sparse optimization. Introducing some assumptions, a problem of recovering a color image from a grayscale image with the small number of known color pixels is formulated as a mixed l0/l1 norm minimization, and an iterative reweighted least squares (IRLS) algorithm is proposed. Numerical examples show that the proposed algorithm colorizes the grayscale image efficiently.

This letter presents the architecture of multi-gigabit parallel demodulator suitable for demodulating high order QAM modulated signal and easy to implement on FPGA platform. The parallel architecture is based on frequency domain implementation of matched filter and timing phase correction. Parallel FIFO based delete-keep algorithm is proposed for timing synchronization, while a kind of reduced constellation phase-frequency detector based parallel decision feedback PLL is designed for carrier synchronization. A fully pipelined parallel adaptive blind equalization algorithm is also proposed. Their parallel implementation structures suitable for FPGA platform are investigated. Besides, in the demonstration of 2 Gbps demodulator for 16QAM modulation, the architecture is implemented and validated on a Xilinx V6 FPGA platform with performance loss less than 2 dB.

In resetting attacks against a proof system, a prover or a verifier is reset and enforced to use the same random tape on various inputs as many times as an adversary may want. Recent deployment of cloud computing gives these attacks a new importance. This paper shows that argument systems for any NP language that are both resettably-sound and resettable zero-knowledge are possible by a constant-round protocol in the BPK model. For that sake, we define and construct a resettably-extractable conditional commitment scheme.