Testbeds play a key role in the advancement of network science and the exploration of new network architectures. Because the scale and scope of any individual testbed is necessarily limited, federation is a useful technique for constructing testbeds that serve a wide range of experimenter needs. In a federated testbed, individual facilities maintain local autonomy while cooperating to provide a unified set of abstractions and interfaces to users. Forming an international federation is particularly challenging, because issues of trust, user access policy, and local laws and regulations are of greater concern that they are for federations within a single country. In this paper, we describe an architecture, based on the US National Science Foundation's GENI project, that is capable of supporting the needs of an international federation.

In this note we suggest a new parallelizable mode of operation for message authentication codes (MACs). The new MAC algorithm iterates a pseudo-random function (PRF) FK:{0,1}m → {0,1}n, where K is a key and m,n are positive integers such that m ≥ 2n. The new construction is an improvement over a sequential MAC algorithm presented at FSE2008, solving positively an open problem posed in the paper – the new mode is capable of fully parallel execution while achieving rate-1 efficiency and “full n-bit” security. Interestingly enough, PMAC-like parallel structure, rather than CBC-like serial iteration, has beneficial side effects on security. That is, the new construction is provided with a more straightforward security proof and with an even better (“-free”) security bound than the FSE 2008 construction.

This letter describes the design methodology for reduced reconfigurable logic circuits based on double gate carbon nanotube field effect transistors (DG-CNTFETs) with ambipolar propoerty. Ambipolar Binary Decision Diagram (Am-BDD) which represents the cornerstone for automatic pass transistor logic (PTL) synthesis flows of ambipolar devices was utilized to build DG-CNTFET based n-input reconfigurable cells in the conventional approach. The proposed method can reduce the number of ambipolar devices for 2-inputs reconfigurable cells, incorporating the simple Boolean algebra in the Am-BDD compared with the conventional approach. As a result, the static 2-inputs reconfigurable circuit with 16 logic functions can be synthesized by using 8 DG-CNTFETs although the previous design method needed 12 DG-CNTFETs for the same purpose.

The Linking Open Data (LOD) cloud is a collection of linked Resource Description Framework (RDF) data with over 31 billion RDF triples. Accessing linked data is a challenging task because each data set in the LOD cloud has a specific ontology schema, and familiarity with the ontology schema used is required in order to query various linked data sets. However, manually checking each data set is time-consuming, especially when many data sets from various domains are used. This difficulty can be overcome without user interaction by using an automatic method that integrates different ontology schema. In this paper, we propose a Mid-Ontology learning approach that can automatically construct a simple ontology, linking related ontology predicates (class or property) in different data sets. Our Mid-Ontology learning approach consists of three main phases: data collection, predicate grouping, and Mid-Ontology construction. Experiments show that our Mid-Ontology learning approach successfully integrates diverse ontology schema with a high quality, and effectively retrieves related information with the constructed Mid-Ontology.

This paper identifies a ripple effect problem (REP) that spreads interference to neighbors and proposes a novel channel localization mechanism to decrease the REP in a Wi-Fi system. The proposed mechanism has less blocking probability when compared to a random channel allocation mechanism and also has increased channel reusability. The proposed mechanism in simulation yields less channels BEm as the number of users and Tused increase.

In this letter, we reduce the computational complexity of the conventional iterative MMSE-ML signal detection method for multiple input multiple output (MIMO) single carrier FDMA (SC-FDMA) systems, without compromising the error performance. Complexity analysis confirms the efficacy of the proposed modification.

A leakage-aware Coordinated Scheduling/Coordinated Beamforming (CS/CB) scheme for heterogeneous networks with layered limited feedback is proposed. In particular, all pico cells cooperatively select an optimal beamforming vector for the macro cell within a CoMP cluster so as to minimizing leakage power from the macro cell. Simulations show that the proposed scheme outperforms the conventional non-CoMP scheme with perfect channel state information at teansmitter (CSIT). Furthermore, the feedback amount and scheduler complexity is decreased greatly.

In this letter, we propose a innovative threshold receiver for MIMO-OFDM system. The proposed scheme calculates the channel condition number and then selects either combined V algorithm and CLLL or combined QRD-M and DFE detection scheme according to channel information. The complexity of the proposed scheme is about 33.3% of the QRD-M for 44 MIMO-OFDM system.

Entity is an important information carrier in Web pages. Users would like to directly get a list of relevant entities instead of a list of documents when they submit a query to the search engine. So the research of related entity finding (REF) is a meaningful work. In this paper we investigate the most important task of REF: Entity Ranking. The wrong-type entities which don't belong to the target-entity type will pollute the ranking result. We propose a novel method to filter wrong-type entities. We focus on the acquisition of seed entities and automatically extracting the common Wikipedia categories of target-entity type. Also we demonstrate how to filter wrong-type entities using the proposed model. The experimental results show our method can filter wrong-type entities effectively and improve the results of entity ranking.

Orthogonal frequency division multiplexing (OFDM) is very sensitive to the frequency errors caused by phase noise and Doppler shift. These errors will disturb the orthogonality among subcarriers and cause intercarrier interference (ICI). A simple method to combat ICI is proposed in this letter. The main idea is to map each data symbol onto a couple of subcarriers rather to a single subcarrier. Different from the conventional adjacent coupling and symmetric coupling methods, the frequency diversity can be utilized more efficiently by the proposed adaptive coupling method based on optimal subcarrier spacing. Numerical results show that our proposed method provides a robust signal-to-noise ratio (SNR) improvement over the conventional coupling methods.

A novel conjugate unitary ESPRIT (CU-ESPRIT) algorithm for the joint direction of departure (DOD), and direction of arrival (DOA), estimation in a bistatic MIMO radar is proposed. A new virtual array is formed by using the properties of noncircular signals, and the properties of the centro-Hermitian matrix are employed to convert the complex-valued data matrix into a real-valued data matrix. Then the real-valued rotational invariance properties of the new virtual array are determined to estimate DODs and DOAs, which are paired automatically. The proposed method provides better angle estimation performance and detects more targets owing to double number of MIMO virtual array elements. Simulation results are presented to verify the effectiveness of the proposed algorithm.

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.

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.

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.

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.

Real-time on-chip measurement of bit error rate (BER) for high-speed analog-to-digital converters (ADCs) does not only require expensive multi-port high-speed data acquisition equipment but also enormous post-processing. This paper proposes a low-cost built-in-self-test (BIST) circuit for high-speed ADC BER test. Conventionally, the calculation of BER requires a high-speed adder. The presented method takes the advantages of Gray coding and only needs simple logic circuits for BER evaluation. The prototype of the BIST circuit is fabricated along with a 5-bit high-speed flash ADC in a 90-nm CMOS process. The active area is only 90 µm 70 µm and the average power consumption is around 0.3 mW at 700 MS/s. The measurement of the BIST circuit shows consistent results with the measurement by external data acquisition equipment.

In this paper, we reformulate the issue related to wireless mesh networks (WMNs) from the Chief Executive Officer (CEO) problem viewpoint, and provide a practical solution to a simple case of the problem. It is well known that the CEO problem is a theoretical basis for sensor networks. The problem investigated in this paper is described as follows: an originator broadcasts its binary information sequence to several forwarding nodes (relays) over Binary Symmetric Channels (BSC); the originator's information sequence suffers from independent random binary errors; at the forwarding nodes, they just further interleave, encode the received bit sequence, and then forward it, without making heavy efforts for correcting errors that may occur in the originator-relay links, to the final destination (FD) over Additive White Gaussian Noise (AWGN) channels. Hence, this strategy reduces the complexity of the relay significantly. A joint iterative decoding technique at the FD is proposed by utilizing the knowledge of the correlation due to the errors occurring in the link between the originator and forwarding nodes (referred to as intra-link). The bit-error-rate (BER) performances show that the originator's information can be reconstructed at the FD even by using a very simple coding scheme. We provide BER performance comparison between joint decoding and separate decoding strategies. The simulation results show that excellent performance can be achieved by the proposed system. Furthermore, extrinsic information transfer (EXIT) chart analysis is performed to investigate convergence property of the proposed technique, with the aim of, in part, optimizing the code rate at the originator.

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.