Analyzing the schedulability of hierarchical real-time systems is difficult because of the systems' complex behavior. It gets more complicated when shared resources or dependencies among tasks are included. This paper introduces a framework based on UPPAAL that can analyze the schedulability of hierarchical real-time systems.

In the conventional cellular macrocell implementation strategy, the main base station transmits the radio signals in the omnidirectional manner in order to provide a wide range of cellular transmission to the users. In reality, however, the users move from one place to another depending on their activities, hence, sometimes this creates areas where no user exists inside the macrocell. Nevertheless, the base station continues to transmit the radio signals to all the coverage areas due to its involuntary manner, thus causing waste of energy. In our previous work, an energy efficient LTE macrocell base station scheme based on hourly user location distribution, which utilized opportunistic beamforming, was proposed in order to provide the cellular transmission only to the area where the user density is high. The drawback of this scheme was that there were many users who cannot receive the cellular transmission because of the limitation of the beamforming shape. In this paper, to overcome this difficulty, a new energy efficient macrocell strategy will be proposed. Here, additional low power consumption femtocell access points are deployed inside the macrocell to support the energy efficient opportunistic beamforming based on the hourly user location distribution. Concretely, the femtocell access points are woken up only when the active calling users exist inside its range. The proposed new strategy will be evaluated in terms of the hourly successful calling user ratio, the total power consumption and the hourly average downlink throughput compared with the previously proposed beamforming transmission strategy and the conventional omnidirectional transmission. The results will show the effectiveness of the proposed strategy in providing an energy efficient cellular macrocell system with high quality cellular services.

It is important to collect and spread accurate information quickly during disasters. Therefore, utilizing Twitter at the time of accidents has been gaining attention in recent year. In this paper, we propose a real-time information sharing system during disaster based on the utilization of Twitter. The proposed system consists of two sub-systems, a disaster information tweeting system that automatically attaches user's current geo-location information (address) and the hashtag of the form “#(municipality name) disaster,” and a disaster information mapping system that displays neighboring disaster-related tweets on a map.

Bistatic multi-input multi-output (MIMO) radar has the capability of measuring the transmit angle from the receiving array, which means the existence of information redundancy and benefits data association. In this paper, a data association decision for bistatic MIMO radar is proposed and the performance advantages of bistatic MIMO radar in data association is analyzed and evaluated. First, the parameters obtained by receiving array are sent to the association center via coordinate conversion. Second, referencing the nearest neighbor association (NN) algorithm, an improved association decision is proposed with the transmit angle and target range as association statistics. This method can evade the adverse effects of the angle system errors to data association. Finally, data association probability in the presence of array directional error is derived and the correctness of derivation result is testified via Monte Carlo simulation experiments. Besides that performance comparison with the conventional phased array radar verifies the excellent performance of bistatic MIMO Radar in data association.

It is qualitatively considered that emergency information processing by using UTM grids is effective in generating COP (Common Operational Pictures). Here, we conducted a numerical evaluation based on emergency information-processing training to examine the efficiency of the use of UTM grid maps by staff at the Tagajo City Government office. The results of the demonstration experiment were as follows: 1) The time required for information propagation and mapping with UTM coordinates was less than that with address text consisting of area name and block number. 2) There was no measurable difference in subjective estimates of the training performance of participants with or without the use of UTM grids. 3) Fear of real emergency responses decreased among training participants using UTM grids. 4) Many of the negative free answers on a questionnaire evaluation of participants involved requests regarding the reliability and operability of UTM tools.

SDN (Software-Defined Networking) enables software applications to program individual network devices dynamically and therefore control the behavior of the network as a whole. Incomplete programming and/or inconsistency with the network policy of SDN software applications may lead to verification issues. The objective of this paper is to describe the formal modeling that uses the process algebra called pACSR and then suggest a method to verify the firewall application running on top of the SDN controller. The firewall rules are translated into a pACSR process which acts as the specification, and packet's behaviors in SDN are also translated to a pACSR process which is a role as the implementation. Then we prove the correctness by checking whether the parallel composition of two pACSR processes is deadlock-free. Moreover, in the case of network topology changes, our verification can be directly applied to check whether any mismatches or inconsistencies will occur.

A 62ps timing resolution pulse generator (PG) is presented. The PG adopts the multi-phase ring oscillator and the pulse combiner circuit (PCC) to achieve the low timing error. The PCC can decide an arbitrary waveform via 16 phase outputs. PCC adopts the coarse-tuning stage (CTS) and the fine-tuning (FTS) to define the operational frequency range and the timing resolution, respectively. Hence, PCC uses edge combiner (EC) to combine the period window of CTS. The latency of PG is only 3 cycle times. The operational frequency range of PG is from 15MHz to 245MHz. The timing resolution and average accuracy of PG are 62.5ps and ±0.5 LSB, respectively. The RMS jitter and peak-to-peak jitter of PG are 6.55ps and 66.67ps, respectively, at 245MHz.

Named Data Networking (NDN) has emerged as an alternative to traditional IP-based networking for the achievement of Information-Centric Networking (ICN). Currently, most NDN is deployed over IP networks, but such an overlay deployment increases the transport network overhead due to the use of dual network control planes (NDN routing and IP routing). Software-Defined Networking (SDN) can be used to mitigate the network overhead by forwarding NDN packets without the use of IP routing. However, to deploy NDN over SDN, a variable NDN content name needs to be mapped to a fixed-size match field in an OpenFlow switch flow table. For efficient support of such a mapping task, we propose a new architecture that uses dual name for content: content name and Name Tag. The Name Tag is derived from the corresponding content name and is a legitimate IPv6 address. By using the proposed Name Tag, the SDN with an NDN control application can transport an IPv6 packet that encapsulates an NDN packet for an NDN name-based routing. We emulate the proposed architecture using Mininet and verify that it is feasible.

This paper presents a 60 GHz analog/digital beamforming receiver that effectively suppresses interference signals, targeting the IEEE 802.11ad/WiGig standard. Combining two-stream analog frontends with interference rejection digital signal processing, the analog beamforming steers the antenna beam to the desired direction while the digital beamforming provides gain suppression in the interference direction. A prototype has been built with 40 nm CMOS analog frontends as well as offline baseband digital signal processing. Measurements show a 3.1 dB EVM advantage over conventional two-stream diversity during a packet collision situation.

In this letter, a novel robust adaptive beamforming algorithm is addressed to improve the robustness against steering vector random errors (SVREs), which eliminates the signal of interest (SOI) component from the sample covariance matrix (SCM), based on interference-plus-noise covariance matrix (IPNCM) reconstruction over annulus uncertainty sets. Firstly, several annulus uncertainty sets are used to constrain the steering vectors (SVs) of both interferences and the SOI. Additionally the IPNCM is reconstructed according to its definition by estimating each interference SV over its own annulus uncertainty set via the subspace projection algorithm. Meanwhile, the SOI SV is estimated as the prime eigenvector of the SOI covariance matrix term calculated over its own annulus uncertainty set. Finally, a novel robust beamformer is formulated based on the new IPNCM and the SOI SV, and it outperforms other existing reconstruction-based beamformers when the SVREs exist, especially in low input signal-to-noise ratio (SNR) cases, which is proved through the simulation results.

The lifting wavelet transform (WT) has been widely applied to image coding. Recently, the total number of lifting steps has been minimized introducing a non-separable 2D structure so that delay from input to output can be reduced in parallel processing. However the minimum lifting WT has a problem that its upper bound of the rate-distortion curve is lower than that of the standard lifting WT. This is due to the rounding noise generated inside the transform in its integer implementation. This paper reduces the rounding noise introducing channel scaling. The channel scaling is designed so that the dynamic range of signal values is fully utilized at each channel inside the transform. As a result, the signal to noise ratio is increased and therefore the upper bound of the minimum lifting WT in lossy coding is improved.

Shrinkage widely linear recursive least squares (SWL-RLS) and its improved version called structured shrinkage widely linear recursive least squares (SSWL-RLS) algorithms are proposed in this paper. By using the relationship between the noise-free a posterior and a priori error signals, the optimal forgetting factor can be obtained at each snapshot. In the implementation of algorithms, due to the a priori error signal known, we still need the information about the noise-free a priori error which can be estimated with a known formula. Simulation results illustrate that the proposed algorithms have faster convergence and better tracking capability than augmented RLS (A-RLS), augmented least mean square (A-LMS) and SWL-LMS algorithms.

A novel computational method based on a combination of the method of moments in the complex frequency domain and the fast inverse Laplace transform is proposed for solving time-domain electromagnetic problems. Using our proposed method, it is easy to estimate and control the computational error, and the observation time can be selected independently. We investigate canonical scattering problems and verify these advantages.

In this paper, we investigate multi-service forwarding in selfish wireless networks (SeWN) with selfish relay nodes (RN). The RN's node-selfishness is characterized from the perspectives of its residual energy and the incentive paid by the source, by which the degree of intrinsic selfishness (DeIS) and the degree of extrinsic selfishness (DeES) are defined. Meanwhile, a framework of the node-selfishness management is conceived to extract the RNs' node-selfishness information (NSI). Based on the RN's NSI, the expected energy cost and expected service profit are determined for analyzing the effect of the RN's node-selfishness on the multi-service forwarding. Moreover, the optimal incentive paid by the source is obtained for minimizing its cost and, at the same time, effectively stimulating the multi-service delivery. Simulation validate our analysis.

Energy-efficient tracking of continuous objects such as fluids, gases, and wild fires is one of the important challenging issues in wireless sensor networks. Many studies have focused on electing fewer nodes to report the boundary information of continuous objects for energy saving. However, this approach of using few reporting packets is very sensitive to packet loss. Many applications based on continuous objects tracking require timely and precise boundary information due to the danger posed by the objects. When transmission of reporting packets fails, applications are unable to track the boundary reliably and a delay is imposed to recover. The transmission failure can fatally degrade application performance. Thus, it is necessary to consider just-in-time recovery for reliable continuous object tracking. Nevertheless, most schemes did not consider the reliable tracking to handle the situation that packet loss happen. Recently, a scheme called I-COD with retransmission was proposed to recover lost packets but it leads to increasing both the energy consumption and the tracking latency owing to the retransmission. Thus, we propose a reliable tracking scheme that uses fast recovery with the redundant boundary information to track continuous objects in real-time and energy-efficiently. In the proposed scheme, neighbor nodes of boundary nodes gather the boundary information in duplicate and report the redundant boundary information. Then the sink node can recover the lost packets fast by using the redundant boundary information. The proposed scheme provides the reliable tracking with low latency and no retransmissions. In addition, the proposed scheme saves the energy by electing fewer nodes to report the boundary information and performing the recovery without retransmissions. Our simulation results show that the proposed scheme provides the energy-efficient and reliable tracking in real-time for the continuous objects.

The finite-difference time-domain (FDTD) method has been widely used in recent years to analyze the propagation and scattering of electromagnetic waves. Because the FDTD method has second-order accuracy in space, its numerical dispersion error arises from truncated higher-order terms of the Taylor expansion. This error increases with the propagation distance in cases of large-scale analysis. The numerical dispersion error is expressed by a dispersion relation equation. It is difficult to solve this nonlinear equation which have many parameters. Consequently, a simple formula is necessary to substitute for the dispersion relation error. In this study, we have obtained a simple formula for the numerical dispersion error of 2-D and 3-D FDTD method in free space propagation.

Sentence similarity computation is an increasingly important task in applications of natural language processing such as information retrieval, machine translation, text summarization and so on. From the viewpoint of information theory, the essential attribute of natural language is that the carrier of information and the capacity of information can be measured by information content which is already successfully used for word similarity computation in simple ways. Existing sentence similarity methods don't emphasize the information contained by the sentence, and the complicated models they employ often need using empirical parameters or training parameters. This paper presents a fully unsupervised computational model of sentence semantic similarity. It is also a simply and straightforward model that neither needs any empirical parameter nor rely on other NLP tools. The method can obtain state-of-the-art experimental results which show that sentence similarity evaluated by the model is closer to human judgment than multiple competing baselines. The paper also tests the proposed model on the influence of external corpus, the performance of various sizes of the semantic net, and the relationship between efficiency and accuracy.

Because the perceptual compressive sensing framework can achieve a much better performance than the legacy compressive sensing framework, it is very promising for the compressive sensing based image compression system. In this paper, we propose an innovative adaptive perceptual block compressive sensing scheme. Firstly, a new block-based statistical metric which can more appropriately measure each block's sparsity and perceptual sensibility is devised. Then, the approximated theoretical minimum measurement number for each block is derived from the new block-based metric and used as weight for adaptive measurements allocation. The obtained experimental results show that our scheme can significantly enhance both objective and subjective performance of a perceptual compressive sensing framework.

In this paper, a convolution theorem which is analogous to the theorem for Fourier transform is shown among a certain type of polynomials. We establish a fast method of the multiplication in a special class of quotient rings of multivariate polynomials over q-element finite field GF(q). The polynomial which we treat is one of expressing forms of the multiple-valued logic function from the product of the semigroups in GF(q) to GF(q). Our results can be applied to the speedup of both software and hardware concerning multiple-valued Boolean logic.

In the paradigm of network coding, when the network topology information cannot be utilized completely, random linear network coding (RLNC) is proposed as a feasible coding scheme. But since RLNC neither considers the global network topology nor coordinates codings between different nodes, it may not achieve the best possible performance of network coding. Hence, the performance analysis of RLNC is very important for both theoretical research and practical applications. Motivated by a fact that different network topology information can be available for different network communication problems, we study and obtain several upper and lower bounds on the failure probability at sink nodes depending on different network topology information in this paper, which is also the kernel to discuss some other types of network failure probabilities. In addition, we show that the obtained upper bounds are tight, the obtained lower bound is asymptotically tight, and we give the worst cases for different scenarios.