Most peer-to-peer (P2P) systems build their own overlay networks for implementing peer selection strategies without taking into account the locality on the underlay network. As a result, a large quantity of traffic crossing internet service providers (ISPs) or autonomous systems (ASes) is generated on the Internet. Controlling the P2P traffic is therefore becoming a big challenge for the ISPs. To control the cost of the cross-ISP/AS traffic, ISPs often throttle and/or even block P2P applications in their networks. In this paper, we propose a router-aided approach for localizing the P2P traffic hierarchically; it features the insertion of additional delay into each P2P packet based on geographical location of its destination. Compared to the existing approaches that solve the problem on the application layer, our proposed method does not require dedicated servers, cooperation between ISPs and P2P users, or modification of existing P2P application software. Therefore, the proposal can be easily utilized by all types of P2P applications. Experiments on P2P streaming applications indicate that our hierarchical traffic localization method not only reduces significantly the inter-domain traffic but also maintains a good performance of P2P applications.

In this paper, we introduce a biologically-motivated model to detect image saliency. The model employs an isophote based operator to detect potential structure and global saliency information related to each pixel, which are then combined with integral image to build up final saliency maps. We show that the proposed model outperforms seven state-of-the-art saliency detectors in experimental studies.

We propose a parallel pth powering method over an arbitrary finite field GF(pm). Using the proposed method, we present the explicit formulae for the computation of cubing over a ternary field GF(3m) which is defined by irreducible trinomials. We show that the field cubing computation for irreducible trinomials, which plays an important role in calculating pairing, can be implemented very efficiently.

A macroscopic structure was analyzed for a system comprising multiple elements in which the dynamics is affected by their distribution. First, a nonlinear Boltzmann equation, which has an integration term with respect to the distribution of the elements, was derived. Next, the moment vector equation (MVE) for the Boltzmann equation was derived. The average probability density function (pdf) in a steady state was derived using eigen analysis of the coefficient matrix of the MVE. The macroscopic structure of the system and the mechanism that provides the average pdf and the transient response were then analyzed using eigen analysis. Evaluation of the average pdf and transient response showed that using eigen analysis is effective for analyzing not only the transient and stationary properties of the system but also the macroscopic structure and the mechanism providing the properties.

In this letter, constructions of sequences with perfect odd autocorrelation and sequence sets with zero odd correlation zone (ZOCZ) over the 8-QAM+ constellation are presented. Based on odd perfect ternary sequences, odd perfect sequences and ZOCZ sequence sets over the 8-QAM+ constellation are constructed by using shift vectors and mappings. These odd perfect sequences and ZOCZ sequence sets over 8-QAM+ constellation can be used in communication systems to achieve high transmission data rate (TDR) and low interference.

Soccer player tracking and labeling suffer from the similar appearance of the players in the same team, especially in long-shot scenes where the faces and the numbers of the players are too blurry to identify. In this paper, we propose an efficient multi-player tracking system. The tracking system takes the detection responses of a human detector as inputs. To realize real-time player detection, we generate a spatial proposal to minimize the scanning scope of the detector. The tracking system utilizes the discriminative appearance models trained using the online Boosting method to reduce data-association ambiguity caused by the appearance similarity of the players. We also propose to build an online learned player recognition model which can be embedded in the tracking system to approach online player recognition and labeling in tracking applications for long-shot scenes by two stages. At the first stage, to build the model, we utilize the fast k-means clustering method instead of classic k-means clustering to build and update a visual word vocabulary in an efficient online manner, using the informative descriptors extracted from the training samples drawn at each time step of multi-player tracking. The first stage finishes when the vocabulary is ready. At the second stage, given the obtained visual word vocabulary, an incremental vector quantization strategy is used to recognize and label each tracked player. We also perform importance recognition validation to avoid mistakenly recognizing an outlier, namely, people we do not need to recognize, as a player. Both quantitative and qualitative experimental results on the long-shot video clips of a real soccer game video demonstrate that, the proposed player recognition model performs much better than some state-of-the-art online learned models, and our tracking system also performs quite effectively even under very complicated situations.

Cooperative wireless communication is a communication mechanism to attain diversity through virtual antenna array that is formed by sharing resources among different users. Different strategies of resource utilization such as amplify-and-forward (AF) and decode-and-forward (DF) already exist in cooperative networks. Although the implementation of these strategies is simple, their utilization of the channel state information (CSI) is generally poor. As a result, the outage and bit error rate (BER) performances need much more improvement in order to satisfy the upcoming high data rate demands. For that to happen the spectral efficiency supported by a wireless system at a very low outage probability should be increased. In this paper a new approach, based on the previously existing ones, called CSI directed estimate and forward (CDEF) with a reduced estimation domain is proposed. A closed form solution for the optimal signal estimation at the relay using minimum mean square error (MMSE) as well as a possible set reduction of the estimation domain is given. It will be shown that this new strategy attains better symbol error rate (SER) and outage performance than AF or DF when the source relay link is comparatively better than the relay destination link. Simulation results also show that it has got better spectral efficiency at low outage probability for a given signal to noise ratio (SNR) as well as for a fixed outage probability in any operating SNR range.

This paper deals with carrier frequency offset (CFO) estimation based on the minimum variance distortionless response (MVDR) criterion without using specific training sequences for interleaved orthogonal frequency division multiple access (OFDMA) uplink systems. In the presence of large CFOs, the estimator is proposed to find a new CFO vector based on the first-order Taylor series expansion of the one initially given. The problem of finding the new CFO vector is formulated as the closed form of a generalized eigenvalue problem, which allows one to readily solve it. Since raising the accuracy of residual CFO estimation can provide more accurate residual CFO compensation, this paper also present a decision-directed MVDR approach to improve the CFO estimation performance. However, the proposed estimator can estimate CFOs with less computation load. Several computer simulation results are provided for illustrating the effectiveness of the proposed blind estimate approach.

To help student nurses learn to transfer patients from a bed to a wheelchair, this paper proposes a system for automatic skill evaluation in nurses' training for this task. Multiple Kinect sensors were employed, in conjunction with colored markers attached to the trainee's and patient's clothing and to the wheelchair, in order to measure both participants' postures as they interacted closely during the transfer and to assess the correctness of the trainee's movements and use of equipment. The measurement method involved identifying body joints, and features of the wheelchair, via the colors of the attached markers and calculating their 3D positions by combining color and depth data from two sensors. We first developed an automatic segmentation method to convert a continuous recording of the patient transfer process into discrete steps, by extracting from the raw sensor data the defining features of the movements of both participants during each stage of the transfer. Next, a checklist of 20 evaluation items was defined in order to evaluate the trainee nurses' skills in performing the patient transfer. The items were divided into two types, and two corresponding methods were proposed for classifying trainee performance as correct or incorrect. One method was based on whether the participants' relevant body parts were positioned in a predefined spatial range that was considered ‘correct’ in terms of safety and efficacy (e.g., feet placed appropriately for balance). The second method was based on quantitative indexes and thresholds for parameters describing the participants' postures and movements, as determined by a Bayesian minimum-error method. A prototype system was constructed and experiments were performed to assess the proposed approach. The evaluation of nurses' patient transfer skills was performed successfully and automatically. The automatic evaluation results were compared with evaluation by human teachers and achieved an accuracy exceeding 80%.

This paper presents a new phase unwrapping algorithm, based on an extended particle filter (EPF) for SAR interferometry. This technique is not limited by the nonlinearity of the model, and is able to accurately unwrap noisy interferograms by applying EPF to simultaneously perform noise suppression and phase unwrapping. Results obtained from synthetic and real data validate the effectiveness of the proposed method.

This paper considers coordinated linear precoding for rate optimization in downlink multicell, multiuser orthogonal frequency-division multiple access networks. We focus on two different design criteria. In the first, the weighted sum-rate is maximized under transmit power constraints per base station. In the second, we minimize the total transmit power satisfying the signal-to-interference-plus-noise-ratio constraints of the subcarriers per cell. Both problems are solved using standard conic optimization packages. A less complex, fast, and provably convergent algorithm that maximizes the weighted sum-rate with per-cell transmit power constraints is formulated. We approximate the non-convex weighted sum-rate maximization (WSRM) problem with a solvable convex form by means of a sequential parametric convex approximation approach. The second-order cone formulations of an objective function and the constraints of the optimization problem are derived through a proper change of variables, first-order linear approximation, and hyperbolic constraints transformation. This algorithm converges to the suboptimal solution while taking fewer iterations in comparison to other known iterative WSRM algorithms. Numerical results are presented to demonstrate the effectiveness and superiority of the proposed algorithm.

We propose a new, compact, center-fed reflector antenna that is capable of one-dimensional electronic beam scanning. The reflector profile in the vertical section (beam-scanning) is set to an imaging reflector configuration, while the profile in the orthogonal horizontal section (non-beam-scanning) is set to a Cassegrain antenna configuration. The primary radiator is a one-dimensional phased array antenna. We choose a center-fed configuration in order to reduce the antenna size as much as possible, despite the fact that the increased blocking area from the primary radiator causes degradation in efficiency compared to the typical offset-type configuration. In the proposed configuration, beam scanning is limited to one dimension, but utilize a compact, center-fed configuration that maintains the features of an imaging reflector antenna. We present the antenna configuration and design method and show that results obtained from the prototype antenna verify the predicted performance.

This paper describes low-power dynamic multiple-input and multiple-output (MIMO) detection for a 4×4 MIMO-orthogonal frequency-division multiplexing (MIMO-OFDM) receiver. MIMO-OFDM systems achieve high-speed and large capacity communications. However, they impose high computational cost in MIMO detection when separating spatially multiplexed signals and they consume vast amounts of power. We propose low-power dynamic MIMO detection that controls detection speed according to wireless environments. The power consumption is reduced by dynamic voltage and frequency scaling (DVFS) that controls the operating voltage and clock frequency in the MIMO detector. We implemented dynamic MIMO detection in a pipelined minimum mean square error (MMSE) MIMO detector that we developed in our previous work. A power saving of 92% was achieved under lowest clock frequency mode conditions.

Remote data possession checking for cloud storage is very important, since data owners can check the integrity of outsourced data without downloading a copy to their local computers. In a previous work, Chen proposed a remote data possession checking protocol using algebraic signature and showed that it can resist against various known attacks. In this paper, we find serious security flaws in Chen's protocol, and shows that it is vulnerable to replay attack by a malicious cloud server. Finally, we propose an improved version of the protocol to guarantee secure data storage for data owners.

To characterize an antenna, the acquisition of its three-dimensional radiation pattern is the fundamental requirement. Spherical antenna measurement is a practical approach to measuring antenna patterns in spherical geometry. However, due to the limitations of measurement range and measurement time, the measured samples may either be incomplete on scanning sphere, or be inadequate in terms of the sampling interval. Therefore there is a need to extrapolate and interpolate the measured samples. Spherical wave expansion, whose band-limited property is derived from the sampling theorem, provides a good tool for reconstructing antenna patterns. This research identifies the limitation of the conventional algorithm when reconstructing the pattern of an antenna which is not located at the coordinate origin of the measurement set-up. A novel algorithm is proposed to overcome the limitation by resampling between the unprimed and primed (where the antenna is centred) coordinate systems. The resampling of measured samples from the unprimed coordinate to the primed coordinate can be conducted by translational phase shift, and the resampling of reconstructed pattern from the primed coordinate back to the unprimed coordinate can be accomplished by rotation and translation of spherical waves. The proposed algorithm enables the analytical and continuous pattern reconstruction, even under the severe sampling condition for deviated AUT. Numerical investigations are conducted to validate the proposed algorithm.

We proposes a method for determining the frequency for monitoring the activities of a malware download site used for malware attacks on websites. In recent years, there has been an increase in attacks exploiting vulnerabilities in web applications for infecting websites with malware and maliciously using those websites as attack platforms. One scheme for countering such attacks is to blacklist malware download sites and filter out access to them from user websites. However, a malware download site is often constructed through the use of an ordinary website that has been maliciously manipulated by an attacker. Once the malware has been deleted from the malware download site, this scheme must be able to unblacklist that site to prevent normal user websites from being falsely detected as malware download sites. However, if a malware download site is frequently monitored for the presence of malware, the attacker may sense this monitoring and relocate that malware on a different site. This means that an attack will not be detected until the newly generated malware download site is discovered. In response to these problems, we clarify the change in attack-detection accuracy caused by attacker behavior. This is done by modeling attacker behavior, specifying a state-transition model with respect to the blacklisting of a malware download site, and analyzing these models with synthetically generated attack patterns and measured attack patterns in an operation network. From this analysis, we derive the optimal monitoring frequency that maximizes the true detection rate while minimizing the false detection rate.

Computation integrity is difficult to verify when mass data processing is outsourced. Current integrity protection mechanisms and policies verify results generated by participating nodes within a computing environment of service providers (SP), which cannot prevent the subjective cheating of SPs. This paper provides an analysis and modeling of computation integrity for mass data processing services. A third-party sampling-result verification method, named TS-TRV, is proposed to prevent lazy cheating by SPs. TS-TRV is a general solution of verification on the intermediate results of common MapReduce jobs, and it utilizes the powerful computing capability of SPs to support verification computing, thus lessening the computing and transmission burdens of the verifier. Theoretical analysis indicates that TS-TRV is effective on detecting the incorrect results with no false positivity and almost no false negativity, while ensuring the authenticity of sampling. Intensive experiments show that the cheating detection rate of TS-TRV achieves over 99% with only a few samples needed, the computation overhead is mainly on the SP, while the network transmission overhead of TS-TRV is only O(log N).

An effective interlaced-to-progressive scanning format conversion method is presented for the interpolation of interlaced images. On the basis of the weight assignment algorithm, the proposed method is composed of three stages: (1) straightforward interpolation with pre-determined six-tap filter, (2) fuzzy metric-based weight assignment, (3) updating the interpolation results. We first deinterlace the missing line with six-tap filter in the working window. Then we compute the local weight among the adjacent pixels with a fuzzy metric. Finally we deinterlace the missing pixels using the proposed interpolator. Comprehensive simulations conducted on different images and video sequences have proved the effectiveness of the proposed method, with significant improvement over conventional methods.

N-Shift Zero Correlation Zone (NS-ZCZ) sequence is defined with the N-shift zero correlation zone in the correlation function. Namely, the N-shift zero only appears within the correlation zone symmetrically distributed in the center of the correlation function. Moreover, the traditional ZCZ sequences can be considered as the N-shift ZCZ sequence with N=1. Similar to ZCZ sequence, NS-ZCZ sequences can be applied in sequence design for co-channel interference mitigation with more sequences in the sequence set compared with the traditional N-shift sequences. In this letter, the definition and construction algorithms are proposed. The corresponding theoretical bounds are analyzed.

We propose a novel approach to the target localization problem using Doppler frequency shift measurements. We first reformulate the maximum likelihood estimation (MLE) as a constrained weighted least squares (CWLS) estimation, and then perform the semidefinite relaxation to relax the CWLS problem as a convex semidefinite programming (SDP) problem, which can be efficiently solved using modern convex optimization methods. Finally, the SDP solution can be used to initialize the original MLE which can provide estimates achieve the Cramer-Rao lower bound accuracy. Simulations corroborate the good performance of the proposed method.