Optimal Block Size Research Articles

Deadline-Aware Scheduling With Adaptive Network Coding for Real-Time Traffic

We study deadline-aware scheduling with adaptive network coding (NC) for real-time traffic over a single-hop wireless network. To meet hard deadlines of real-time traffic, the block size for NC is adapted based on the remaining time to the deadline so as to strike a balance between maximizing the throughput and minimizing the risk that the entire block of coded packets may not be decodable by the deadline. This sequential block size adaptation problem is then cast as a finite-horizon Markov decision process. One interesting finding is that the optimal block size and its corresponding action space monotonically decrease as the deadline approaches, and that the optimal block size is bounded by the greedy block size. These unique structures make it possible to significantly narrow down the search space of dynamic programming, building on which we develop a monotonicity-based backward induction algorithm (MBIA) that can find the optimal block size in polynomial time. Furthermore, a joint real-time scheduling and channel learning scheme with adaptive NC is developed to adapt to channel dynamics in a mobile network environment. Then, we generalize the analysis to multiple flows with hard deadlines and long-term delivery ratio constraints. We devise a low-complexity online scheduling algorithm integrated with the MBIA, and then establish its asymptotical utility optimality. The analysis and simulation results are corroborated by high-fidelity wireless emulation tests, where actual radio transmissions over emulated channels are performed to demonstrate the feasibility of the MBIA in finding the optimal block size in real time.

A novel reversible image data hiding scheme based on pixel value ordering and dynamic pixel block partition

Recently, various efficient reversible data-hiding schemes based on pixel value ordering have been proposed for embedding messages into high-fidelity images. In these schemes, after dividing the cover image into equal-sized blocks, the pixels within a given block are ordered according to their values, and data embedding is achieved by modifying the maximum and minimum values of each block. For a given embedding capacity, the optimal block size is exhaustively searched so that the embedding distortion is minimized. These pixel value ordering-based schemes perform fairly well, especially for low embedding capacity. However, to obtain a larger embedding capacity, a smaller block size should be used, which usually leads to a dramatic quality degradation of the marked image. In this paper, to address this drawback and to enhance the performance of pixel value ordering-based embedding further, a novel reversible data hiding method is proposed. Instead of using equal-sized blocks, a dynamic blocking strategy is used to divide the cover image adaptively into various-sized blocks. Specifically, flat image areas are preferentially divided into smaller blocks to retain high embedding capacity, whereas rough areas are divided into larger blocks to avoid decreasing peak signal-to-noise ratio. As a result, the proposed scheme can provide a larger embedding capacity than current pixel value ordering-based schemes while keeping distortion low. The superiority of the proposed method is also experimentally verified.

Multifocus Image Fusion Using Biogeography-Based Optimization

For multifocus image fusion in spatial domain, sharper blocks from different source images are selected to fuse a new image. Block size significantly affects the fusion results and a fixed block size is not applicable in various multifocus images. In this paper, a novel multifocus image fusion algorithm using biogeography-based optimization is proposed to obtain the optimal block size. The sharper blocks of each source image are first selected by sum modified Laplacian and morphological filter to contain an initial fused image. Then, the proposed algorithm uses the migration and mutation operation of biogeography-based optimization to search the optimal block size according to the fitness function in respect of spatial frequency. The chaotic search is adopted during iteration to improve optimization precision. The final fused image is constructed based on the optimal block size. Experimental results demonstrate that the proposed algorithm has good quantitative and visual evaluations.

Translocation and induced permeability of random amphiphilic copolymers interacting with lipid bilayer membranes.

We investigate adsorption and passive translocation of random amphiphilic copolymers interacting with a self-assembled lipid bilayer membrane. By using the bond fluctuation model with explicit solvent, we consider random copolymers under variation of the fraction, H̅, of hydrophobic sites and chain length. Our results indicate a point of balanced hydrophobicity, where a slight excess of hydrophobic monomers compensates an additional insertion barrier due to the self-organized packing of the bilayer. Close to balanced hydrophobicity, we observe translocation events of shorter polymers through the membrane. Compared to homopolymers, surface localization of amphiphilic polymers is considerably increased due to the polar nature of the molecules with respect to the amphiphilic environment, and translocations are suppressed for longer chains. Close to balanced hydrophobicity, the polymer induces dynamic and static perturbations in the bilayer, and permeability with respect to solvent is significantly increased around the copolymer. We discuss how to design membrane-active copolymers with a desired emphasis on either translocation or permeabilization based on a systematic sequence analysis. Our results indicate that alternating copolymers with an optimal block size smaller than the lipid size maximize perturbation of the bilayer, whereas for passive translocation, the limit of small block size or homopolymers with balanced hydrophobicity are most relevant.

Optimal blockwise subcarrier allocation policies in single-carrier FDMA uplink systems

In this paper, we analyze the optimal (blockwise) subcarrier allocation schemes in single-carrier frequency division multiple access (SC-FDMA) uplink systems without channel state information at the transmitter side. The presence of the discrete Fourier transform (DFT) in SC-FDMA/orthogonal frequency division multiple access OFDMA systems induces correlation between subcarriers which degrades the transmission performance, and thus, only some of the possible subcarrier allocation schemes achieve better performance. We propose as a performance metric a novel sum-correlation metric which is shown to exhibit interesting properties and a close link with the outage probability. We provide the set of optimal block-sizes achieving the maximum diversity and minimizing the inter-carrier sum-correlation function. We derive the analytical closed-form expression of the largest optimal block-size as a function of the system’s parameters: number of subcarriers, number of users, and the cyclic prefix length. The minimum value of sum-correlation depends only on the number of subcarriers, number of users and on the variance of the channel impulse response. Moreover, we observe numerically a close strong connection between the proposed metric and diversity: the optimal block-size is also optimal in terms of outage probability. Also, when the considered system undergoes carrier frequency offset (CFO), we observe the robustness of the proposed blockwise allocation policy to the CFO effects. Numerical Monte Carlo simulations which validate our analysis are illustrated.

English

Network technologies and media services provide ubiquitous conveniences for individuals and organizations to gather and process the images in multimedia networks Image compression is the major challenge in storage and bandwidth requirements. A good strategy of image compression gives a better solution for high compression rate without much reducing the quality of the image. In present paper we proposed a simple and effective Method by filtering the image as a preprocessing step and adaptive block size in Block truncation coding at the encoding stage. The results are appealing for finding optimal block size when compare to the JPEG2000 standard.

Analytical Model Determining the Optimal Block Size in the Block Caving Mining Method

Nowadays along with population growth, industry development, consumption of mineral resources and the fact that the reserves on hand are running out, the depth of surface and underground mines for further exploitation are increasing. During recent years, in underground mining, the block caving method for low-grade and large-scale deposits has shown a growing rate of application. The dimensions of blocks are one of the most important parameters which should be taken into account since it has been proved to have a great deal of effect on technical issues such as commencement of caving and mine design. In this study, some assumptions were considered and having used these assumptions for estimation of optimized length and width of block, a relationship was explored. And finally, it was transformed into an inequality. Solving this inequality provides us with the optimized length and width of the block. The explored relationship was analysed using MATLAB and the resulting graphs thereof were drawn. Simulation was carried out using the Phase2 software and the results were compared with the different modes of the block. In the blocks that were 55, 60 and 65 m in length, the total displacement (the total displacement as a result of applying force in order to cave), yielded elements (percent) and Yielded Joints reached a satisfactory condition which enables perfect caving to occur. In addition, in the 70 m block, these values reached their maximum. It was concluded in this paper that the optimal block size is between 55 and 65 m.

IFrag: interference-aware frame fragmentation scheme for wireless sensor networks

Reliable data transmission is a fundamental challenge in resource-constrained wireless sensor networks. In current implementations, a single bit error requires retransmitting the entire frame. This incurs extra processing overhead and power consumption, especially for large frames. Frame fragmentation into small blocks with individual error detection codes can reduce the unnecessary retransmission of the correctly received blocks. The optimal block size, however, varies based on the wireless channel conditions. In this paper, we propose an interference-aware frame fragmentation scheme called iFrag. iFrag dynamically adjusts the number of blocks inside a frame based on current channel conditions, and effectively addresses all challenges associated with such dynamic partitioning. Through analytical and experimental results, we show that iFrag achieves up to $$3\times$$ improvement in goodput when the channel is noisy, while reducing the delay by 12 % compared to other static fragmentation approaches. On average, it shows a 13 % gain in goodput across all channel conditions used in our experiments. Our testbed results also show that iFrag lowers the energy consumed per useful bit by 60 %, as improved data transmission reliability reduces the number of frame retransmissions which increases the motes energy efficiency.

Relative phase noise estimation and mitigation in Raman amplified coherent optical communication system

The interplay between the stochastic intensity fluctuation of Raman pump laser and cross-phase modulation (XPM) effect in transmission optical fiber leads to additional phase noise, namely, relative phase noise (RPN) of signal in multi-level modulated coherent optical communication system. Both theoretical analysis and quantitative simulation have been performed to investigate the characteristics and impact of RPN. Being low-pass in nature, RPN is different from XPM induced phase noise in PSK/OOK hybrid system, and has not been considered yet. The noise power of RPN can accumulate incoherently along transmission links. With a proper signal model, we study the impact of RPN to the coherent optical communication system through Monte Carlo simulation. RPN will cause more cycle slips in Viterbi-and-Viterbi (V-V) phase estimation (PE), and the quantitative analysis of cycle slip probability is carried out. When using sliding window V-V without any optimization, the Q factor penalty of RPN on DQPSK signal can be as large as around 5 dB in strong RPN condition. However, it can be reduced by over 3 dB when using an optimal block size or optimal averaging weights.

Reversible Encrypted Data Hiding In Encrypted Video

A data hiding scheme for encrypted image has been proposed by Xinpeng Zhang (11). In this paper however, we put forward a data hiding scheme on an encrypted video. The data to be embedded is encrypted ensuring greater security. Each video frame is a jpg image, which is then encrypted using any stream cipher. The data to be embedded is encrypted. It is then embedded by modifying a small portion of the encrypted cover image. The decryption of video is done first followed by the decryption of the data. With the aid of the data hiding key and spatial correlation in natural image, the embedded data can be successfully extracted and the original video can be perfectly recovered. The accuracy of receiver is very much dependant on the block size of the cover image and consequently, an optimum block size is suggested as an experimental value. Index Terms: Video Encryption, Data Embedding, Frames I. INTRODUCTION Data embedding helps data to be stored inside any cover media. The cover media may be image, audio or video. Reversible data hiding ensures that the cover media is unaltered after decryption and data extraction. That is, the cover that was used for data embedding shoud be as such recovered after data extraction. Encryption is a technique that ensures secure sharing of data. Only the sender and receiver would have access to the encrypted data, by means of the key. Encryption may be symmetric or asymmetric, based on the keys being used. Joining the two schemes of data hiding and encryption provides added security and convenience in transmission.

Modeling of nano piezoelectric actuator based on block matching algorithm with optimal block size

In order to model the hysteresis behavior of a nano piezoelectric actuator (PA) on nano scale in a real time system, a new hysteresis modeling method based on an improved sub-pixel blocking matching algorithm with an optimal block size is proposed in this paper. First, Preisach model is introduced to model the hysteresis behavior of a piezoelectric actuator. Then, a real time block matching algorithm is researched and its block size is optimized with a standard object. Finally, experiments are performed with respect to a nanometer movement platform system, and the results show the feasibility and validity of the sub-pixel estimation based block matching algorithm and its application in modeling the hysteresis behavior of PA.

GPU acceleration of the WSM6 cloud microphysics scheme in GRAPES model

The microphysical process that leads to cloud and precipitation formation is one of the most important physical processes in numerical weather prediction (NWP) and climate models. The Weather Research Forecast (WRF) Single Moment 6-class (WSM6) microphysics scheme in the Global/Regional Assimilation and Prediction System (GRAPES) includes predictive variables of water vapor, cloud water, cloud ice, rain, snow and graupel. The computation of WSM6 is the most time-consuming portion among that of the entire GRAPES model. In recent years, with the advent of the Compute Unified Device Architecture (CUDA), modern graphics processing units (GPUs) with the advantage of low-power, low-cost, and high-performance computing capacity have been exploited to accomplish the arithmetic operations in scientific and engineering simulations. In this paper, we present an implementation of the WSM6 scheme in GRAPES using GPU to accelerate the computation. After a brief introduction to the WSM6 scheme, the data dependence for the GPU implementation of the WSM6 scheme is discussed. The data parallel method is employed to exploit the massive fine-grained parallelism. The CUDA programming model is used to convert the original WSM6 module into GPU programs. To achieve high computational performance, mapping horizontal domain onto an optimal block size is proposed. The experimental results demonstrate that the GPU version obtains over 140× speedup compared with the CPU serial version, and is an efficient parallel implementation.

Fast intermode decision algorithm based on general and local residual complexity in H.264/AVC

The state-of-the-art video coding standard H.264/AVC achieves significant coding performance by adopting variable block sizes for motion estimation (ME) and mode decision. However, this technique brings out high computational complexity since the optimal mode is determined by exhaustively performing rate-distortion optimization (RDO) on each coding mode with different block sizes. In this paper, the fast intermode decision algorithm is proposed to reduce the computational complexity. Based on the high correlation between the residual error of ME and the optimal block size, general residual complexity (GRC) and local residual complexity (LRC) are defined. According to MB activity evaluated on GRC and LRC, candidate intermodes are determined and RDO processes are only performed on selected intermodes. The experimental results demonstrate that the proposed algorithm achieves time saving by 63% on average with negligible degradation of coding efficiency.

Optimal Bacon-Shor codes

We study the performance of Bacon-Shor codes, quantum subsystem codes which are well suited for applications to fault-tolerant quantum memory because the error syndrome can be extracted by performing two-qubit measurements. Assuming independent noise, we find the optimal block size in terms of the bit-flip error probability $p_X$ and the phase error probability $p_Z$, and determine how the probability of a logical error depends on $p_X$ and $p_Z$. We show that a single Bacon-Shor code block, used by itself without concatenation, can provide very effective protection against logical errors if the noise is highly biased ($p_Z/p_X\gg 1)$ and the physical error rate $p_Z$ is a few percent or below. We also derive an upper bound on the logical error rate for the case where the syndrome data is noisy.

Fault-tolerant quantum computation with asymmetric Bacon-Shor codes

We develop a scheme for fault-tolerant quantum computation based on asymmetric Bacon-Shor codes, which works effectively against highly biased noise dominated by dephasing. We find the optimal Bacon-Shor block size as a function of the noise strength and the noise bias, and estimate the logical error rate and overhead cost achieved by this optimal code. Our fault-tolerant gadgets, based on gate teleportation, are well suited for hardware platforms with geometrically local gates in two dimensions.

Intra Prediction Block Size Estimation Algorithm in H.264/AVC Encoder for Mobile Smart Devices Using in Wireless Networks

In this paper, we propose an efficient block size estimation algorithm for the Intra prediction of H.264/ AVC to reduce the encoding complexity. Firstly, the macroblock (MB) is split into 4x4 sub-blocks, and the corresponding information in them is extracted. And then, the opposite variance intensity (OVI) between the sub-block and the MB is calculated as the main judgment factor. With the statistical analysis, the Intra prediction block size is estimated by OVI, and the optimal block size of Intra prediction is selected instead of the original three mode sizes. The simulation results show that the proposed algorithm could reduce around 45% encoding time for H.264/AVC encoder, and the quality and output bitrate of the encoded video signal are significantly maintained. It could be widely used for the video coding and communication systems with the mobile devices which have limited power supply and low processing ability.

A sub-block-based eigenphases algorithm with optimum sub-block size

Several algorithms have been proposed for constrained face recognition applications. Among them the eigenphases algorithm and some variations of it using sub-block processing, appears to be desirable alternatives because they achieves high face recognition rate, under controlled conditions. However, their performance degrades when the face images under analysis present variations in the illumination conditions as well as partial occlusions. To overcome these problems, this paper derives the optimal sub-block size that allows improving the performance of previously proposed eigenphases algorithms. Theoretical and computer evaluation results show that, using the optimal block size, the identification performance of the eigenphases algorithm significantly improves, in comparison with the conventional one, when the face image presents different illumination conditions and partial occlusions respectively. The optimal sub-block size also allows achieving a very low false acceptance and false rejection rates, simultaneously, when performing identity verification tasks, which is not possible to obtain using the conventional approach; as well as to improve the performance of other sub-block-based eigenphases methods when rank tests are performed.

Object reconstruction in block-based compressive imaging

A block-based compressive imaging (BCI) system using sequential architecture is presented in this paper. Feature measurements are collected using the principal component analysis (PCA) projection. The linear Wiener operator and a nonlinear method based on the Field-of-Expert (FoE) prior model are used for object reconstruction. Experimental results are given to demonstrate the superior reconstruction performance of the FoE-based method over the Wiener operator. In addition, the effects of system parameters, such as the object block size, the number of features per block, and the noise level to the BCI reconstruction performance are discussed with different kinds of objects. Then an optimal block size is defined and studied for BCI.

Block Bootstraps for Time Series With Fixed Regressors

This article examines block bootstrap methods in linear regression models with weakly dependent error variables and nonstochastic regressors. Contrary to intuition, the tapered block bootstrap (TBB) with a smooth taper not only loses its superior bias properties but may also fail to be consistent in the regression problem. A similar problem, albeit at a smaller scale, is shown to exist for the moving and the circular block bootstrap (MBB and CBB, respectively). As a remedy, an additional block randomization step is introduced that balances out the effects of nonuniform regression weights, and restores the superiority of the (modified) TBB. The randomization step also improves the MBB or CBB. Interestingly, the stationary bootstrap (SB) automatically balances out regression weights through its probabilistic blocking mechanism, without requiring any modification, and enjoys a kind of robustness. Optimal block sizes are explicitly determined for block bootstrap variance estimators under regression. Finite sample performance and practical uses of the methods are illustrated through a simulation study and two data examples, respectively. Supplementary materials are available online.

Interim CRC: A Novel Method to Read Large-Size Data from Tags in RFID Systems

Large capacity tags are becoming available to meet the demands of industry, but the UHF RFID protocol is unable to reliably and efficiently read large data sets from tags. First of all, large data sets are not well protected. The tag merely relies on 16-bit CRC for ensuring the validity of up to 4,096-bit user-specific data in EPCglobalC1G2 protocol. Furthermore, the reliability will be even worse if large capacity tags are implemented using semi-active technology which is likely to prevail among sensor-integrated RFID tags. Since semi-active tags greatly alleviate the performance limitation imposed by the turn-on power of the tag chip, backscattering signal of semi-active tags could be a serious challenge for most readers because it is much weaker than signals emitted by passive tags due to longer reading distance. In this paper, Interim CRC is presented to enhance transmission reliability and efficiency when the tag is backscattering a large data set. By taking advantage of Interim CRC, the large data set can be divided into several blocks, and 16-bit checksum is calculated over each block. The tag backscatters all blocks at the first time and only retransmits certain blocks if CRC error occurs in those blocks. The result of simulation shows that the reading error rate can be confined to a preset threshold and the accumulative total of transmitted data are greatly reduced if optimal block size and transmission times are complied with. The simulation also conclusively proves that semi-active tags derive even longer reading range from Interim CRC. In addition, Interim CRC is totally compliant with the EPCglobalC1G2 protocol. It fully makes use of CRC-16 encoder and does not involve any other data encoding schematics and hardware modifications.