Information-Centric Networking (ICN) treats contents as first class citizens and adopts name-based routing for content distribution and retrieval. Content names rather than IP addresses are directly used for routing. However, due to the location-independent naming and the huge namespace, name-based routing faces scalability and efficiency issues including large routing tables and high path stretches. This paper proposes a universal Scalable Name-based Geometric Routing scheme (SNGR), which is a careful synthesis of geometric routing and name resolution. To provide scalable and efficient underlying routing, a universal geometric routing framework (GRF) is proposed. Any geometric routing scheme can be used directly for name resolution based on GRF. To implement an overlay name resolution system, SNGR utilizes a bi-level grouping design. With this design, a resolution node that is close to the consumer can always be found. Our theoretical analyses guarantee the performance of SNGR, and experiments show that SNGR outperforms similar routing schemes in terms of node state, path stretch, and reliability.

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.

Community detection is a pivotal task in data mining, and users' emotional behaviors have an important impact on today's society. So it is very significant for society management or marketing strategies to detect emotional communities in social networks. Based on the emotional homophily of users in social networks, it could confirm that users would like to gather together to form communities according to emotional similarity. This paper exploits multivariate emotional behaviors of users to measure users' emotional similarity, then takes advantage of users' emotional similarity as edge weight to remodel an emotional network and detect communities. The detailed process of detecting emotional communities is as follows: 1) an emotional network is constructed and emotional homophily in experimental dataset is verified; 2) both CNM and BGLL algorithms are employed to detect emotional communities in emotional network, and emotional characters of each community are analyzed; 3) in order to verify the superiority of emotional network for detecting emotional communities, 1 unweighted network and 3 other weighted and undirected networks are constructed as comparison. Comparison experiments indicate that the emotional network is more suitable for detecting emotional communities, the users' emotional behaviors are more similar and denser in identical communities of emotional network than the contrastive networks' communities.

Energy conservation is an important issue in mobile ad hoc networks (MANET), where the terminals are always supplied with limited energy. A new routing protocol is presented according to the study on the influence of low-energy nodes in ad hoc networks. The novel routing protocol (energy sensing routing protocol, ESRP) is based on the energy sensing strategy. Multiple strategy routing and substitute routing are both adopted in this paper. Referring to the level of the residual energy and the situation of energy consumption, different routes are chosen for packets transmission. The local maintenance is adopted, which can reduce packets retransmission effectively when the link breaks. We focus on the network lifetime most in all performances. The evaluation is done in comparison with other routing protocols on NS2 platform, and the simulation results show that this routing protocol can prolong the network lifetime and balance energy consumption effectively.

In this paper, a novel hybrid technique for analyzing complex antennas around the coated object is proposed, which is termed as “iterative vector fields with Physical Optics (PO)”. A closed box is used to enclose the antennas and the complex field vectors on the box' surfaces can then be obtained using Huygens principle. The equivalent electromagnetic currents on Huygens surfaces are computed by Higher-order Method of Moments (HOB-MoM) and the fields scattered from the coated object are calculated by PO method. In addition, the parallel technique based on Message Passing Interface (MPI) and Scalable Linear Algebra Package (ScaLAPACK) is employed so as to accelerate the computation. Numerical examples are presented to validate and to show the effectiveness of the proposed method on solving the practical engineering problem.

Up until now, the best public key encryption with multi-dimensional range query (PKMDRQ) scheme has two problems which need to be resolved. One is that the scheme is selectively secure. The other is that the time of decryption is long. To address these problems, we present a method of converting a predicate encryption supporting inner product (IPE) scheme into a PKMDRQ scheme. By taking advantage of this approach, an instance is also proposed. The comparison between the previous work and ours shows that our scheme is more efficient over the time complexity. Moreover, our scheme is adaptively secure.

Spectrum and Bit Error Rate (BER) performance of a coded π/2 phase shift Non-Square (NS) 8 Quadrature Amplitude Modulation (QAM) system are studied in this letter. The modulation process of this scheme removes all 180 phase shift between adjacent constellation points and contains inherent memory which can be treated as a type of inner coding in coded system. Simulation results show that this modulation scheme has much lower spectrum regrowth and better BER performance when passing through nonlinear channel compared with conventional mode.

Based on the expectation-maximization (EM) algorithm, an iterative time-domain channel estimation approach capable of using a priori information is proposed for orthogonal frequency division multiplexing (OFDM) systems in this letter: it outperforms its noniterative counterpart in terms of estimation accuracy as well as bit error rate (BER) performance. Numerical simulations demonstrate that an SNR gain of 1 dB at BER=10-4 with only one iteration and estimation mean square error (MSE) which nearly coincides with the Cramer-Rao bound (CRB) in the low SNR region can be obtained, thanks to the efficient use of a priori information.

This paper analyzes the conventional unequal erasure protection (UXP) scheme for scalable video transmission, and proposes a dynamic hybrid UXP/ARQ transmission framework to improve the performance of the conventional UXP method for bandwidth-constrained scalable video transmission. This framework applies automatic retransmission request (ARQ) to the conventional UXP scheme for scalable video transmission, and dynamically adjusts the transmission time budget of each group of picture (GOP) according to the feedback about the transmission results of the current and previous GOPs from the receiver. Moreover, the parameter of target video quality is introduced and optimized to adapt to the channel condition in pursuit of more efficient dynamic time allocation. In addition, considering the play-out deadline constraint, the time schedule for the proposed scalable video transmission system is presented. Simulation results show that compared with the conventional UXP scheme and its enhanced method, the average peak signal to noise ratio (PSNR) of the reconstructed video can be improved significantly over a wide range of packet loss rates. Besides, the visual quality fluctuation among the GOPs can be reduced for the video which has much movement change.

A unified construction for transforming binary sequences of balance or unbalance into quaternary sequences is presented. On the one hand, when optimal and balanced binary sequences with even period are employed, our construction is exactly the same Jang, et al.'s and Chung, et al.'s ones, which result in balanced quaternary sequences with optimal autocorrelation magnitude. On the other hand, when ideal and balanced binary sequences with odd period N are made use of, our construction produces new balanced quaternary sequences with optimal autocorrelation value (OAV), in which there are N distinct sequences in terms of cyclic shift equivalence, and includes Tang, et al.'s and Jang, et al.'s ones as special cases. In addition, when binary sequences without period 2n-1 or balance are employed, the transformation of Jang, et al.'s method is invalid, however, the proposed construction works very good. As a consequence, this unified construction allows us to construct optimal and balanced quaternary sequences from ideal/optimal balanced binary sequences with arbitrary period.

This letter presents three methods for producing 8-QAM+ sequences. The first method transforms a ternary complementary sequence set (CSS) with even number of sub-sequences into an 8-QAM+ periodic CSS with both of the period and the number of sub-sequences unaltered. The second method results in an 8-QAM+ aperiodic CSS with confining neither the period nor the number of sub-sequences. The third method produces 8-QAM+ periodic sequences having ideal autocorrelation property on the real part of the autocorrelation function. The proposed sequences can be potentially applied to suppression of multiple access interference or synchronization in a communication system.

A zig-zag Gardner algorithm with parallel architecture is presented in this letter. This algorithm performs timing adjustment in each individual burst independently for high speed wireless burst communication with a short guard. Over sampling data are stored in RAM initially and read forward and backward alternately later. The proposed algorithm has distinct symmetric characteristic in the forward and backward process, which makes the alternate sequences achieve nearly the same effect as a continuous sequence. The performance of the proposed algorithm is very close to the theoretical curve.

As semiconductor manufacturing processing scaling down, leakage current of CMOS circuits is becoming a dominant contributor to power dissipation. This paper provides an efficient leakage current reduction (LCR) technique for low-power and low-frequency circuit designs in terms of design rules and layout parameters related to layout dependent effects. We address the LCR technique both for analog and digital circuits, and present a design case when applying the LCR techniqe to a successive-approximation-register (SAR) analog-to-digital converter (ADC), which typically employs analog and digital transistors. In the post-layout simulation results by HSPICE, an SAR-ADC with the LCR technique achieves 38.6-nW as the total power consumption. Comparing with the design without the LCR technique, we attain about 30% total energy reduction.

Efficient road-lane detection is expected to be achievable by application of the Hough transform (HT) which realizes high-accuracy straight-line extraction from images. The main challenge for HT-hardware implementation in actual applications is the trade-off optimization between accuracy maximization, power-dissipation reduction and real-time requirements. We report a HT-hardware architecture for road-lane detection with parallelized voting procedure, local maximum algorithm and FPGA-prototype implementation. Parallelization of the global design is realized on the basis of θ-value discretization in the Hough space. Four major hardware modules are developed for edge detection in the original video frames, computation of the characteristic edge-pixel values (ρ,θ) in Hough-space, voting procedure for each (ρ,θ) pair with parallel local-maximum-based peak voting-point extraction in Hough space to determine the detected straight lines. Implementation of a prototype system for real-time road-lane detection on a low-cost DE1 platform with a Cyclone II FPGA device was verified to be possible. An average detection speed of 135 frames/s for VGA (640x480)-frames was achieved at 50 MHz working frequency.

General purpose computing on GPU (GPGPU) has become a popular computing model for high-performance, data-intensive applications. Accordingly, there is a strong need to develop highly efficient data structures to ease the development of GPGPU applications. In this work, we proposed an efficient concurrent queue data structure for GPU computing. The GPU based provably correct, lock-free FIFO queue allows a massive number of concurrent producers and consumers. Warp-centric en-queue and de-queue procedures are introduced to better match the underlying Single-Instruction, Multiple-Thread execution model of modern GPUs. It outperforms the best previous GPU queues by up to 40 fold. The correctness of the proposed queue operations is formally validated by linearizability criteria.

Based on quadriphase perfect sequences and their cyclical shift versions, three families of almost perfect 16-QAM sequences are presented. When one of two time shifts chosen equals half a period of quadriphase sequence employed and another is zero, two of the proposed three sequence families possess the property that their out-of-phase autocorrelation function values vanish except one. At the same time, to the other time shifts, the nontrivial autocorrelation function values in three families are zero except two or four. In addition, two classes of periodic complementary sequence (PCS) pairs over the 16-QAM constellation, whose autocorrelation is similar to the one of conventional PCS pairs, are constructed as well.

In this letter, we explored the usage of spatio-temporal information in one unified framework to improve the performance of multichannel speech recognition. Generalized cross correlation (GCC) is served as spatial feature compensation, and an attention mechanism across time is embedded within long short-term memory (LSTM) neural networks. Experiments on the AMI meeting corpus show that the proposed method provides a 8.2% relative improvement in word error rate (WER) over the model trained directly on the concatenation of multiple microphone outputs.

This paper improves the family size of quadrature amplitude modulation (QAM) complementary sequences with binary inputs. By employing new mathematical description: B-type-2 of 4q-QAM constellation (integer q ≥ 2), a new construction yielding 4q-QAM complementary sequences (CSs) with length 2m (integer m ≥ 2) is developed. The resultant sequences include the known QAM CSs with binary inputs as special cases, and the family sizes of new sequences are approximately 22·2q-4q-1(22·2q-3-1) times as many as the known. Also, both new sequences and the known have the same the peak envelope power (PEP) upper bounds, when they are used in an orthogonal frequency-division multiplexing communication system.

We consider the problem of fast identification of high-rate flows in backbone links with possibly millions of flows. Accurate identification of high-rate flows is important for active queue management, traffic measurement and network security such as detection of distributed denial of service attacks. It is difficult to directly identify high-rate flows in backbone links because tracking the possible millions of flows needs correspondingly large high speed memories. To reduce the measurement overhead, the deterministic 1-out-of-k sampling technique is adopted which is also implemented in Cisco routers (NetFlow). Ideally, a high-rate flow identification method should have short identification time, low memory cost and processing cost. Most importantly, it should be able to specify the identification accuracy. We develop two such methods. The first method is based on fixed sample size test (FSST) which is able to identify high-rate flows with user-specified identification accuracy. However, since FSST has to record every sampled flow during the measurement period, it is not memory efficient. Therefore the second novel method based on truncated sequential probability ratio test (TSPRT) is proposed. Through sequential sampling, TSPRT is able to remove the low-rate flows and identify the high-rate flows at the early stage which can reduce the memory cost and identification time respectively. According to the way to determine the parameters in TSPRT, two versions of TSPRT are proposed: TSPRT-M which is suitable when low memory cost is preferred and TSPRT-T which is suitable when short identification time is preferred. The experimental results show that TSPRT requires less memory and identification time in identifying high-rate flows while satisfying the accuracy requirement as compared to previously proposed methods.

With the development of blockchain technology, the automatic generation of smart contract has become a hot research topic. The existing smart contract automatic generation technology still has improvement spaces in complex process, third-party specialized tools required, specific the compatibility of code and running environment. In this paper, we propose an automatic smart contract generation method, which is domain-oriented and configuration-based. It is designed and implemented with the application scenarios of government service. The process of configuration, public state database definition, code generation and formal verification are included. In the Hyperledger Fabric environment, the applicability of the generated smart contract code is verified. Furthermore, its quality and security are formally verified with the help of third-party testing tools. The experimental results show that the quality and security of the generated smart contract code meet the expect standards. The automatic smart contract generation will “elegantly” be applied on the work of anti-disclosure, privacy protection, and prophecy processing in government service. To effectively enable develop “programmable government”.