A high-speed low-complexity time-multiplexing Reed-Solomon-based forward error correction architecture based on the pipelined truncated inversionless Berlekamp-Massey algorithm is presented in this paper. The proposed architecture has very high speed and very low hardware complexity compared with conventional Reed-Solomon-based forward error correction architectures. Hardware complexity is improved by employing a truncated inverse Berlekamp-Massey algorithm. A high-speed and high-throughput data rate is facilitated by employing a three-parallel processing pipelining technique and modified syndrome computation block. The time-multiplexing method for pipelined truncated inversionless Berlekamp-Massey architecture is used in the parallel Reed-Solomon decoder to reduce hardware complexity. The proposed architecture has been designed and implemented with 90-nm CMOS technology. Synthesis results show that the proposed 16-channel Reed-Solomon-based forward error correction architecture requires 417,600 gates and can operate at 640 MHz to achieve a throughput of 240 Gb/s. The proposed architecture can be readily applied to Reed-Solomon-based forward error correction devices for next-generation short-reach optical communications.

In this paper, we propose a novel incremental method for discovering latent variables from multivariate data with high efficiency. It integrates non-Gaussianity and an adaptive incremental model in an unsupervised way to extract informative features. Our proposed method discovers a small number of compact features from a very large number of features and can still achieve good predictive performance in EEG signals. The promising EEG signal classification results from our experiments prove that this approach can successfully extract important features. Our proposed method also has low memory requirements and computational costs.

This paper focuses on power control in relay-enhanced multicell networks with universal frequency reuse for maximizing the overall system throughput, subject to interference and noise impairments, and individual power constraints at both BSs and RSs. With a high signal-to-interference-plus-noise ratio (SINR) approximation, an energy efficiency based power allocation algorithm is proposed to achieve the maximum sum throughput with the least power consumption. Moreover, an iterative quasi-distributed power allocation algorithm is also presented, which is suitable for any SINR regime. Numerical results indicate that the proposed algorithms approach the optimal power allocation and the system performance can be significantly improved in terms of network throughput and energy efficiency.

We propose three operation modes, namely, DCF uplink, Downlink, and CTS uplink modes to solve the unfairness problem between uplink and downlink as well as improve the performance of delay and throughput. The proposed scheme only requires modifying AP's functionalities without any changes of STAs, and is fully backward compatible to the legacy DCF. Its analytical result is validated against simulation and performance evaluation shows the proposed scheme is superior to the traditional IEEE 802.11 WLAN.

We present a privacy preserving method based on inserting dummy data into original data on the data structure called Zero-suppressed BDDs (ZDDs). Our task is distributed itemset mining, which is frequent itemset mining from horizontally partitioned databases stored in distributed places called sites. We focus on the fundamental case in which there are two sites and each site has a database managed by its owner. By dividing the process of distributed itemset mining into the set union and the set intersection, we show how to make the operations secure in the sense of undistinguishability of data, which is our criterion for privacy preserving based on the already proposed criterion, p-indistinguishability. Our method conceals the original data in each operation by inserting dummy data, where ZDDs, BDD-based directed acyclic graphs, are adopted to represent sets of itemsets compactly and to implement the set operations in constructing the distributed itemset mining process. As far as we know, this is the first technique which gives a concrete representation of sets of itemsets and an implementation of set operations for privacy preserving in distributed itemset mining. Our experiments show that the proposed method provides undistinguishability of dummy data. Furthermore, we compare our method with Secure Multiparty Computation (SMC), which is one of the well-known techniques of secure computation.

In this paper, we have addressed the problem of ordering transactions in network-on-chips (NoCs) for post-silicon validation. The main idea is to extract the order of the transactions from the local partial orders in each NoC tile based on a set of “happened-before” rules, assuming transactions do not have a timestamp. The assumption is based on the fact that implementation and usage of a global time as timestamp in such systems may not be practical or efficient. When a new transaction is received in a tile, we send special messages to the neighboring tiles to inform them regarding the new transaction. The process of sending those special messages continues recursively in all the tiles that receive them until another such special message is detected. This way, we relate local orders of different tiles with each other. We show that our method can reconstruct the correct transaction orders when communication delays are deterministic. We have shown the effectiveness of our method by correctly ordering the transaction in NoCs with mesh and torus topologies with different sizes from 5*5 to 9*9. Also, we have implemented the proposed method in hardware to show its feasibility.

Multicore processor architectures have become ubiquitous in today's computing platforms, especially in parallel computing installations, with their power and cost advantages. While the technology trend continues towards having hundreds of cores on a chip in the foreseeable future, an urgent question posed to system designers as well as application users is whether applications can receive sufficient support on today's operating systems for them to scale to many cores. To this end, people need to understand the strengths and weaknesses on their support on scalability and to identify major bottlenecks limiting the scalability, if any. As open-source operating systems are of particular interests in the research and industry communities, in this paper we choose three operating systems (Linux, Solaris and FreeBSD) to systematically evaluate and compare their scalability by using a set of highly-focused microbenchmarks for broad and detailed understanding their scalability on an AMD 32-core system. We use system profiling tools and analyze kernel source codes to find out the root cause of each observed scalability bottleneck. Our results reveal that there is no single operating system among the three standing out on all system aspects, though some system(s) can prevail on some of the system aspects. For example, Linux outperforms Solaris and FreeBSD significantly for file-descriptor- and process-intensive operations. For applications with intensive sockets creation and deletion operations, Solaris leads FreeBSD, which scales better than Linux. With the help of performance tools and source code instrumentation and analysis, we find that synchronization primitives protecting shared data structures in the kernels are the major bottleneck limiting system scalability.

MPEG spatial audio object coding (SAOC) is a new audio coding standard which efficiently represents various audio objects as a down-mix signal and spatial parameters. MPEG SAOC has a backward compatibility with existing playback systems for the down-mix signal. If a mastering signal is used for providing CD-like sound quality instead of the down-mix signal, an output signal decoded with the mastering signal may be easily degraded due to the difference between the down-mix and the mastering signals. To successfully use the mastering signal in MPEG SAOC, the difference between two signals should be eliminated. As a simple mastering signal processing, we propose a mastering signal processing using the mastering down-mix gain (MDG) which is similar to the arbitrary down-mix gain of MPEG Surround. Also, we propose an enhanced mastering signal processing using the MDG bias in order to reduce quantization errors of the MDG. Experimental results show that the proposed schemes can improve sound quality of the output signal decoded with the mastering signal. Especially, the enhanced method shows better performance than the simple method in the aspects of the quantization errors and the sound quality.

Bag of visual words is a promising approach to object categorization. However, in this framework, ambiguity exists in patch encoding by visual words, due to information loss caused by vector quantization. In this paper, we propose to incorporate patch-level contextual information into bag of visual words for reducing the ambiguity mentioned above. To achieve this goal, we construct a hierarchical codebook in which visual words in the upper hierarchy contain contextual information of visual words in the lower hierarchy. In the proposed method, from each sample point we extract patches of different scales, all of which are described by the SIFT descriptor. Then, we build the hierarchical codebook in which visual words created from coarse scale patches are put in the upper hierarchy, while visual words created from fine scale patches are put in the lower hierarchy. At the same time, by employing the corresponding relationship among these extracted patches, visual words in different hierarchies are associated with each other. After that, we design a method to assign patch pairs, whose patches are extracted from the same sample point, to the constructed codebook. Furthermore, to utilize image information effectively, we implement the proposed method based on two sets of features which are extracted through different sampling strategies and fuse them using a probabilistic approach. Finally, we evaluate the proposed method on dataset Caltech 101 and dataset Caltech 256. Experimental results demonstrate the effectiveness of the proposed method.

Lee and Kwon proposed an anonymous authentication scheme based on Zhu et al.'s scheme. However, Lee et al.'s scheme has two disadvantages. Firstly, their scheme is vulnerable to off-line dictionary attacks. An adversary can guess a user password from the user's login messages eavesdropped by the adversary. Secondly, an authentication server called a home agent requires a verification table, which violates the original advantage of Zhu et al.'s scheme. That is, it increases the key management costs of the home agent. In this letter, we show the weaknesses of Lee et al.'s scheme and another three existing schemes. Then, we propose a new secure scheme without the verification table, while providing security for off-line dictionary attacks and other attacks except for a certain type of combined attacks.

The expected write deficiency of the index-less indexed flash codes (ILIFC) is studied. ILIFC is a coding scheme for flash memory, and consists of two stages with different coding techniques. This study investigates the write deficiency of the first stage of ILIFC, and shows that omitting the second stage of ILIFC can be a practical option for realizing flash codes with good average performance. To discuss the expected write deficiency of ILIFC, a random walk model is introduced as a formalization of the behavior of ILIFC. Based on the random walk model, two different techniques are developed to estimate the expected write deficiency. One technique requires some computation, but gives very precise estimation of the write deficiency. The other technique gives a closed-form formula of the write deficiency under a certain asymptotic scenario.

A parameterization of perfect sequences over composition algebras over the real number field is presented. According to the proposed parameterization theorem, a perfect sequence can be represented as a sum of trigonometric functions and points on a unit sphere of the algebra. Because of the non-commutativity of the multiplication, there are two definitions of perfect sequences, but the equivalence of the definitions is easily shown using the theorem. A composition sequence of sequences is introduced. Despite the non-associativity, the proposed theorem reveals that the composition sequence from perfect sequences is perfect.

In this paper, we propose two new attacks against stream cipher RC4 which can recover the secret key in different length with practical computational amount. However, we have to point out that the proposed attacks are performed under relatively strong related key models. The same as the usual related key models, the adversary can specify the key differentials without knowing the target key information. However, in our attacks, only the relation between two keystream outputs or the two final internal states are required for the attacker. In addition, we discover a statistical bias of RC4 which is the key point to one of the attacks. Besides the inappropriate usage during the WEP environment, RC4 is still considered to be secure with the proper setting, and we believe the result of this paper will add to the understanding of RC4 and how to use it correctly and safely.

In this letter, we argue that user resources will be still useful in the information-centric network (ICN). From this point of view, we first examine how P2P utilizing user resources looks like in ICN. Then, we identify challenging research issues to utilize user resources in ICN.

This study presents an adaptive quantization index modulation scheme applicable on a small audio segment, which in turn allows the watermarking technique to withstand time-shifting and cropping attacks. The exploitation of auditory masking further ensures the robustness and imperceptibility of the embedded watermark. Experimental results confirmed the efficacy of this scheme against common signal processing attacks.

In this letter, for offloading traffic to Wireless Local Area Network (WLAN) with transport layer mobility where WLAN service is intermittently available, we propose a novel scheme to freeze and melt the timeout handling procedure of SCTP. Simulation results show that the proposed scheme significantly improves the performance in terms of file transfer completion time.

In this letter, we present a method for improving the front-to-back ratio (FBR) of a broadcast antenna. The digitalization of terrestrial TV demands more efficient channel usage due to the reduction in TV bands after the switch-over. Thus, we designed an antenna with an FBR improved over -45 dB as compared to the -20 to -25 dB FBR range of existing antennas. We show experimentally that this antenna satisfies the required performance.

This paper presents comprehensive comparisons based on the block error rate (BLER) of open-loop (OL) transmit diversity schemes considering a cubic metric (CM) for single-carrier (SC)-Frequency Division Multiple Access (FDMA) using discrete Fourier transform (DFT)-precoded OFDMA in uplink frequency-selective fading channels. The OL transmit diversity schemes assumed in the paper are space-time block code (STBC), space-frequency block code (SFBC), single-carrier (SC) - SFBC, cyclic delay diversity (CDD), and frequency switched transmit diversity (FSTD) for two antennas and a combination of STBC, SFBC, SC-SFBC and selection transmit diversity including time switched transmit diversity (TSTD) or FSTD for four antennas. We derive the most appropriate OL transmit diversity scheme for SC-FDMA using a frequency domain equalizer (FDE) with QPSK and 16QAM modulations and with various channel coding rates employing turbo coding. We investigate the best OL transmit diversity scheme under various propagation channel conditions including the fading maximum Doppler frequency and root mean square (r.m.s.) delay spread, and the fading correlation between transmitter/receiver antennas.

The interference rejection combining (IRC) receiver, which can suppress inter-cell interference, is effective in improving the cell-edge user throughput. The IRC receiver is typically based on the minimum mean square error (MMSE) criteria, and requires a covariance matrix including the interference signals, in addition to a channel matrix from the serving cell. Therefore, in order to clarify the gain from the IRC receiver, the actual estimation error of these matrices should be taken into account. In a system performance evaluation, the link performance modeling of the IRC receiver, i.e., the output signal-to-interference-plus-noise power ratio (SINR) after IRC reception including the estimation errors, is very important in evaluating the actual performance of the IRC receiver in system level simulations. This is because these errors affect the suppression of the interference signals for the IRC receiver. Therefore, this paper investigates and proposes IRC receiver modeling schemes for the covariance matrix and channel estimation errors. As the modeling scheme for the covariance matrix, we propose a scheme that averages the conventional approximation using the complex Wishart distribution in the frequency domain to address issues that arise in a frequency selective fading channel. Furthermore, we propose a modeling scheme for the channel estimation error according to the ideal channel response of all cells and a channel estimation filter to address channel fading fluctuations. The results of simulations assuming the LTE/LTE-Advanced downlink with two transmitter and receiver antenna branches show that the proposed modeling scheme for the covariance matrix estimation error accurately approximates the performance of a realistic IRC receiver, which estimates the covariance matrix and channel matrix of the serving cell based on the demodulation reference signal (DM-RS), even in a frequency selective fading channel. The results also show that the proposed modeling scheme for the channel estimation error is a robust scheme in terms of the r.m.s. delay spread of a channel model compared to the scheme using the mean square error (MSE) statistic of the estimated channel coefficients based on a channel estimation filter.

Characterization of peer-to-peer (P2P) traffic is an essential step to develop workload models towards capacity planning and cyber-threat countermeasure over P2P networks. In this paper, we present a classification scheme for characterizing P2P file-sharing hosts based on transport layer statistical features. The proposed scheme is accessed on a virtualized environment that simulates a P2P-friendly cloud system. The system shows high accuracy in differentiating P2P file-sharing hosts from ordinary hosts. Its tunability regarding monitoring cost, system response time, and prediction accuracy is demonstrated by a series of experiments. Further study on feature selection is pursued to identify the most essential discriminators that contribute most to the classification. Experimental results show that an equally accurate system could be obtained using only 3 out of the 18 defined discriminators, which further reduces the monitoring cost and enhances the adaptability of the system.