In this letter, a new class of almost binary sequence pairs with a single zero element and three autocorrelation values is presented. The new almost binary sequence pairs are based on cyclic difference sets and difference set pairs. By applying the method to the binary sequence pairs, new binary sequence pairs with three-level autocorrelation are constructed. It is shown that new sequence pairs from our constructions are balanced or almost balanced and have optimal three-level autocorrelation when the characteristic sequences or sequence pairs of difference sets or difference set pairs are balanced or almost balanced and have optimal autocorrelations.

Location of a source is of considerable interest in wireless sensor networks, and it can be estimated from passive measurements of the arrival times. A novel algorithm for source location by utilizing the time of arrival (TOA) measurements of a signal received at spatially separated sensors is proposed. The algorithm is based on total least-squares (TLS) method, which is a generalized least-squares method to solve an overdetermined set of equations whose coefficients are noisy, and gives an explicit solution. Comparisons of performance with standard least-squares method are made, and Monte Carlo simulations are performed. Simulation results indicate that the proposed TLS algorithm gives better results than LS algorithm.

With energy shortages and global climate change leading our concerns these days, the energy consumption of datacenters has become a key issue. Obviously, a substantial reduction in energy consumption can be made by powering down servers when they are not in use. This paper aims at designing, implementing and evaluating a Green Scheduler for reducing energy consumption of datacenters in Cloud computing platforms. It is composed of four algorithms: prediction, ON/OFF, task scheduling, and evaluation algorithms. The prediction algorithm employs a neural predictor to predict future load demand based on historical demand. According to the prediction, the ON/OFF algorithm dynamically adjusts server allocations to minimize the number of servers running, thus minimizing the energy use at the points of consumption to benefit all other levels. The task scheduling algorithm is responsible for directing request traffic away from powered-down servers and toward active servers. The performance is monitored by the evaluation algorithm to balance the system's adaptability against stability. For evaluation, we perform simulations with two load traces. The results show that the prediction mode, with a combination of dynamic training and dynamic provisioning of 20% additional servers, can reduce energy consumption by 49.8% with a drop rate of 0.02% on one load trace, and a drop rate of 0.16% with an energy consumption reduction of 55.4% on the other. Our method is also proven to have a distinct advantage over its counterparts.

In this note, we go further on the “basis exchange” idea presented in [2] by using Mobious inversion. We show that the matrix S1(f)S0(f)-1 has a nice form when f is chosen to be the majority function, where S1(f) is the matrix with row vectors υk(α) for all α ∈ 1f and S0(f)=S1(f ⊕ 1). And an exact counting for Boolean functions with maximum algebraic immunity by exchanging one point in on-set with one point in off-set of the majority function is given. Furthermore, we present a necessary condition according to weight distribution for Boolean functions to achieve algebraic immunity not less than a given number.

This paper presents a high-speed SHA-1 implementation. Unlike the conventional unfolding transformation, the proposed unfolding transformation technique makes the combined hash operation blocks to have almost the same delay overhead regardless of the unfolding factor. It can achieve high throughput of SHA-1 implementation by avoiding the performance degradation caused by the first hash computation. We demonstrate the proposed SHA-1 architecture on a FPGA chip. From the experimental results, the SHA-1 architecture with unfolding factor 5 shows 1.17 Gbps. The proposed SHA-1 architecture can achieve about 31% performance improvements compared to its counterparts. Thus, the proposed SHA-1 can be applicable for the security of the high-speed but compact mobile appliances.

For a prime p with p≡3 (mod 4) and an odd number m, the Bentness of the p-ary binomial function fa,b(x)=Tr1n(axpm-1)+Tr12 is characterized, where n=2m, a ∈ F*pn, and b ∈ F*p2. The necessary and sufficient conditions of fa,b(x) being Bent are established respectively by an exponential sum and two sequences related to a and b. For the special case of p=3, we further characterize the Bentness of the ternary function fa,b(x) by the Hamming weight of a sequence.

Low drop-out regulators (LDOs) are widely used in the system-on-a-chip (SoC) design. Due to the multi-function and energy saving requirements for mobile applications nowadays, more strict specifications are expected on the developmental roadmap of the LDOs. An output-capacitorless LDO providing fast transient response under the low supply voltage and low quiescent current conditions is proposed in this paper. Provided by the low supply voltage, the proposed LDO adopts cascading technique using the Multipath Nested Miller Compensation (MNMC) to maintain a higher bandwidth for fast transient requirement. In addition, a Transient Quiescent Current Booster (TQCB) is supplemented to the operational amplifier to improve the slew rate for the fast load transient. The TQCB only raises the quiescent current during the load transient instant so that both power saving and the load response improvement could be well achieved. It deserves noting that the proposed TQCB contains only two transistors, which is simple to be implemented compared to the other transient current enhancement techniques. The designed LDO has only 1.6 pF capacitance for the totally added on-chip compensation, and 25.8 µA of current consumption in the main amplifier. The recovery time under the fast load change is less than 3 µs and the stability is guaranteed. Test results from the real implementation of a 0.35 µm CMOS process verify that the designed LDO performs as expected.

In this paper, a novel algorithm, Cross Low-dimension Pursuit, based on a new structured sparse matrix, Permuted Block Diagonal (PBD) matrix, is proposed in order to recover sparse signals from incomplete linear measurements. The main idea of the proposed method is using the PBD matrix to convert a high-dimension sparse recovery problem into two (or more) groups of highly low-dimension problems and crossly recover the entries of the original signal from them in an iterative way. By sampling a sufficiently sparse signal with a PBD matrix, the proposed algorithm can recover it efficiently. It has the following advantages over conventional algorithms: (1) low complexity, i.e., the algorithm has linear complexity, which is much lower than that of existing algorithms including greedy algorithms such as Orthogonal Matching Pursuit and (2) high recovery ability, i.e., the proposed algorithm can recover much less sparse signals than even 1-norm minimization algorithms. Moreover, we demonstrate both theoretically and empirically that the proposed algorithm can reliably recover a sparse signal from highly incomplete measurements.

In the received signal strength-based ranging algorithms, distance is estimated from a path loss model, in which the path loss exponent is considered a key parameter. The conventional RSS-based algorithms generally assume that the path loss exponent is known a priori. However, this assumption is not acceptable in the real world because the channel condition depends on the current wireless environment. In this paper, we propose an accurate estimation method of the path loss exponent that results in minimizing distance estimation errors in varying environments. Each anchor node estimates the path loss exponent for its transmission coverage by the sequential rearrangement of the received signal strengths of all sensor nodes within its coverage. Simulation results show that the proposed method can accurately estimate the actual path loss exponent without any prior knowledge and provides low distance estimation error.

Silver electrical contacts are separated to generate break arcs in a DC48 V/6-24 A resistive circuit. The transverse magnetic field formed by a permanent magnet is applied to the break arcs. A series of experiments are carried out for two different experimental conditions. One condition is a constant contact separating speed while the magnetic flux density is changed to investigate the shortening effect of the arc duration. Another condition is a constant magnetic flux density while the contact separating speed is changed to investigate the changes in the arc duration and the contact gap when the break arc is extinguished. As a result, with constant separating speed, it is confirmed that the duration of break arcs is shortened by the transverse magnetic field and the break arcs are extinguished when the arc length reaches a certain value L. Under the condition of constant transverse magnetic field, (i) the arc duration is shortened by increasing the separation speed; (ii) the contact gap when the break arc is extinguished is almost constant when the separating speed v is sufficiently faster than 5 mm/s.

A hybrid overlay/underlay spectrum sharing method for cognitive radio networks based on user classification and convex optimization is proposed. Interference radii are configured for the primary receiver and each cognitive receiver. Cognitive users are divided into four groups and allocated different spectrum sharing patterns according to their distance from the primary transmitter and receiver. An optimal power allocation scheme that achieves the maximum sum rate of cognitive radio system on the premise of satisfying the interference constraint of primary receiver is acquired through the convex optimization method. Performance analysis and simulation results show that, compared with existing methods, our method leads to improved performance of achievable sum rate of cognitive users while guarantees the transmission of primary users.

Many malicious programs we encounter these days are armed with their own custom encoding methods (i.e., they are packed) to deter static binary analysis. Thus, the initial step to deal with unknown (possibly malicious) binary samples obtained from malware collecting systems ordinarily involves the unpacking step. In this paper, we focus on empirical experimental evaluations on a generic unpacking method built on a dynamic binary instrumentation (DBI) framework to figure out the applicability of the DBI-based approach. First, we present yet another method of generic binary unpacking extending a conventional unpacking heuristic. Our architecture includes managing shadow states to measure code exposure according to a simple byte state model. Among available platforms, we built an unpacking implementation on PIN DBI framework. Second, we describe evaluation experiments, conducted on wild malware collections, to discuss workability as well as limitations of our tool. Without the prior knowledge of 6029 samples in the collections, we have identified at around 64% of those were analyzable with our DBI-based generic unpacking tool which is configured to operate in fully automatic batch processing. Purging corrupted and unworkable samples in native systems, it was 72%.

This paper presents novel structures of band-pass filters using two configurations of open loop ring resonators (OPLRR): a resonator with embedded quadruply-stepped impedance transmission lines (QSITL) in coupled lines, and a stepped impedance resonator (SIR). Both types of OPLRR have the capability of suppressing the second spurious response and shifting the third spurious response to a higher frequency as well. To demonstrate the performances of both proposed resonators, two sections of each structure with cascaded and crossed configurations at an operating frequency of 0.9 GHz are presented. Both methodologies are easy to design and implement. The methodology with a SIR has a better performance than the SITL. The measurement results of the proposed circuits are in full agreement with the simulated prediction results.

Providing quality-of service (QoS) guarantees in VoIP applications has become an urgent demand in wireless and mobile networks. One of the important issues is to find a simple quality metric fitted to low power mobile devices such as smart phones. This paper considers the gap ratio (the proportion of the accumulated gap periods over the whole call session) as a simple quality metric. Our study aims to find the optimum packet count threshold between two adjacent lost packets (referred to as Gmin in RTCP-XR), which is needed for the purpose of identifying whether the current packet at the receiver belongs to the gap state or the burst state, because quality prediction errors depend on the Gmin value when the gap ratio is used as a simple quality metric. Based on this metric, we propose an accounting model that can be a candidate accounting metric useful for a quality-based accounting mechanism.

We consider a queuing model with applications to electric vehicle (EV) charging systems in smart grids. We adopt a scheme where an Electric Service Company (ESCo) broadcasts a one bit signal to EVs, possibly indicating 'on-peak' periods during which electricity cost is high. EVs randomly suspend/resume charging based on the signal. To model the dynamics of EVs we propose an M/M/∞ queue with random interruptions, and analyze the dynamics using time-scale decomposition. There exists a trade-off: one may postpone charging activity to 'off-peak' periods during which electricity cost is cheaper, however this incurs extra delay in completion of charging. Using our model we characterize achievable trade-offs between the mean cost and delay perceived by users. Next we consider a scenario where EVs respond to the signal based on the individual loads. Simulation results show that peak electricity demand can be reduced if EVs carrying higher loads are less sensitive to the signal.

In this paper, we propose precoding and power allocation strategies for full-duplex multiple input multiple output (MIMO) relays. The precoding scheme for full-duplex MIMO relays is derived based on the block diagonalization (BD) method to suppress the self-interference in the full-duplex relaying so that each relay station (RS) can receive multiple data streams from the base station (BS), while forwarding the decoded data streams to mobile stations (MS's) simultaneously. We also develop the optimal power allocation scheme for full-duplex MIMO relays. Numerical results verify that the proposed scheme provides substantial performance improvement compared with the conventional half-duplex relay (HDR), if sufficient physical isolation between the transmit and receive antennas is ensured such that the proposed full-duplex MIMO relays operate in a tolerable self-interference range.

Wireless Sensor Networks (WSNs) are gradually moving toward the adoption of clustered heterogeneous designs, incorporating a mixture of variety kinds of sensor nodes with different radio coverage and battery capacity. Compared with homogeneous networks, heterogeneous networks are able to reduce the initial cost of the network or prolong the network lifetime. The architecture and routing protocol for this type of heterogeneous WSN should be energy aware in order to prolong the lifetime of the network. However, most of the existing clustering methods consider only initial energy of the sensor nodes and ignore the non-uniform energy drainage caused by many-to-one traffic near sink and/or cluster heads in heterogeneous network environment. In this paper, we propose a new clustering method for WSN with heterogeneous node types which selects cluster heads considering not only the transmission power and residual energy of each node but also those of its adjacent nodes. Simulation experiments show that the proposed method increases network lifetime by 80% and 60% more than that of the CC and HEED, respectively.

This paper proposes a new resource allocation algorithm for uplink OFDMA-based cooperative relay networks, assuming multiple user nodes, multiple relay nodes and a single destination. The aim is to maximise the total sum of the users' data rates, while guaranteeing fairness among them with different QoS requirements. Assuming perfect channel state information (CSI) at the resource allocation controller, the optimisation problem is formulated such that each user is assigned a weight factor based on its QoS requirements. The ones with higher weights are given higher priorities to select their resources (relay stations and subcarriers) first. Once the required QoS is achieved for all users, the weight factor for all users is reduced to a small uniform value. The remaining resources are then allocated to the users with higher instantaneous rates in order of magnitude. The results show that the proposed algorithm outperforms the greedy and static algorithms in terms of outage probability and fairness, and at the same time outperforms Jeong's algorithm by 58% in terms of total sum rate, with an average 74% reduction in system complexity.

In this letter, the reliabilty of the generalized normal-Laplace (GNL) distribution used for modeling the multiple access interference (MAI) plus noise in time-hopping (TH) binary phase-shift keying (BPSK) ultra-wideband (UWB) systems is evaluated in terms of the probability density function and the BER. The multiple access performance of TH-BPSK UWB systems based on GNL model is analyzed. The average BER performance obtained by using GNL approximation well matches with the exact BER results of TH-BPSK UWB systems. The parameter estimates of GNL distribution based on the moments estimation method is also presented.

This paper proposes a novel hallucination technique for color face image reconstruction in the RGB, YCbCr, HSV and CIELAB color systems. Our hallucination method depends on multilinear principal component analysis (MPCA) with a linear regression model. In the hallucination framework, many color face images are expressed in color spaces. These images can be naturally described as tensors or multilinear arrays. This novel hallucination technique can perform feature extraction by determining a multilinear projection that captures most of the original tensorial input variation. In our experiments, we used facial images from the FERET database to test our hallucination approach which is demonstrated by extensive experiments with high-quality hallucinated color face images. The experimental results show that a correlation between the color channel and the proposed hallucination method can reduce the complexity in the color face hallucination process.