In the secure multicast communication, data is transmitted in such a manner that only authorized group members are able to receive the data. The main challenging issue in dynamic and secure multicast communication is ...
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In the secure multicast communication, data is transmitted in such a manner that only authorized group members are able to receive the data. The main challenging issue in dynamic and secure multicast communication is to design a centralized group key distribution protocol with minimum computation and storages complexity. This paper, proposes a more efficient centralized group key distribution (CGKD) protocol that minimizes the computation cost of key server (KS) during key updating. The computation cost of members is balanced during key recovery. This reduction in computation cost of KS is achieved by performing one addition, one multiplication and one encryption during single member join and one subtraction, one division and one encryption during a single member leave operation. Moreover, the storage complexity of KS is also minimized. Further, this paper also proposes an extended CGKD protocol based on clustered tree which is very scalable and efficient to deal with enormous membership changes. By comparing with existing similar protocols, the proposed protocol has significantly reduced computation and storage complexity of KS while maintaining less and balanced communication overhead of KS and storage load of each group member. The proposed protocol is implemented and tested on key-star and cluster tree based structure. The experimental results show that the proposed protocol is efficient in terms of computational overhead of KS and group members. (C) 2018 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University.
摘要摘要本文提出一種運輸網路中邊長改變後尋找各點對間最短路徑的矩陣算法。算法的衩雜性分析表明，運用該算法，計算量確實能少于用現有方法對改變網路重新計算所需耍的計算量。AbstractIn this paper, we propose a matrix algorith...
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摘要摘要本文提出一種運輸網路中邊長改變後尋找各點對間最短路徑的矩陣算法。算法的衩雜性分析表明，運用該算法，計算量確實能少于用現有方法對改變網路重新計算所需耍的計算量。AbstractIn this paper, we propose a matrix algorithm to determine the shortest paths in a changed network. The analyses indicate that the algorithm takes less computation time than the original algorithms.
Background: Searching optima is one of the most challenging tasks in clustering genes from available experimental data or given functions. SA, GA, PSO and other similar efficient global optimization methods are used b...
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Background: Searching optima is one of the most challenging tasks in clustering genes from available experimental data or given functions. SA, GA, PSO and other similar efficient global optimization methods are used by biotechnologists. All these algorithms are based on the imitation of natural phenomena. Results: This paper proposes a novel searching optimization algorithm called Gravitation Field Algorithm (GFA) which is derived from the famous astronomy theory Solar Nebular Disk Model (SNDM) of planetary formation. GFA simulates the Gravitation field and outperforms GA and SA in some multimodal functions optimization problem. And GFA also can be used in the forms of unimodal functions. GFA clusters the dataset well from the Gene Expression Omnibus. Conclusions: The mathematical proof demonstrates that GFA could be convergent in the global optimum by probability 1 in three conditions for one independent variable mass functions. In addition to these results, the fundamental optimization concept in this paper is used to analyze how SA and GA affect the global search and the inherent defects in SA and GA. Some results and source code (in Matlab) are publicly available at http://***/CSBG/GFA.
This paper proposes a new demodulation structure by quantizing the constellation and using a lookup table. When the modulated noisy symbols are received by demodulation end, it's not to calculate the Euclidean dis...
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ISBN:
(纸本)9781510817982
This paper proposes a new demodulation structure by quantizing the constellation and using a lookup table. When the modulated noisy symbols are received by demodulation end, it's not to calculate the Euclidean distances between a symbol and every constellation points, but quantize each dimension of this symbol's coordinate value in the constellation, and check the bit soft values corresponding to this quantification point against a lookup table which is known by a pretreatment. The proposed method will omit a large number of the calculations for demodulation and simplifies the system. Employing look-up table instead of traditional computing can reduce the delay by 72.4% to 93.9% when the quantification interval is from 0.1 to 0.4. Meanwhile, the performance gain only reduces about 0.1d B.
The simplex growing algorithm (SGA) suffers from two issues in its practical *** is that it needs to reduce the original data’s dimensionality in *** other one is its excessive *** order to solve the first issue,a ne...
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The simplex growing algorithm (SGA) suffers from two issues in its practical *** is that it needs to reduce the original data’s dimensionality in *** other one is its excessive *** order to solve the first issue,a new simplex growing algorithm (N-SGA) which uses a new simplex volume formula with no need for dimension reduction is proposed in this ***,a developed approach called Fast N-SGA is put forward to reduce the computation *** conducted experiments demonstrate that the proposed algorithms N-SGA and Fast N-SGA perform better than the tradition SGA.
Algebraic multigrid is often used as the preconditioner in Krylov subspace iterations to solve general sparse linear systems, and the aggregation based version is one of the most popular, for its cheap complexity to s...
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Algebraic multigrid is often used as the preconditioner in Krylov subspace iterations to solve general sparse linear systems, and the aggregation based version is one of the most popular, for its cheap complexity to setup. In this paper, when this version used as the preconditioner, two schemes are provided to improve its implementation. The first is to remove the trivial computation in the smoothing for zero initial vectors before the restriction process. For this case, part of the computation is related to the multiplication of an operator to a zero vector, and then it can be omitted without any changes to the derived result. The second is to reconstruct the restriction process, which can reduce the computation complexity at the cost of a little more storage. The analyses and the numerical experiments for the solution of sparse linear systems from a model partial differential equation with preconditioned conjugate gradients show that the provided schemes can reduce the solution time significantly. The improvements are much more significant when more nodes are aggregated each time, and are more significant to W-cycle than to V-cycle and K-cycle.
A spatial and temporal attention strategy based on Non-local Networks is proposed for video-based person re-identification. The most existing methods design attention mechanisms on high-level features, which ignore th...
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ISBN:
(纸本)9781450376631
A spatial and temporal attention strategy based on Non-local Networks is proposed for video-based person re-identification. The most existing methods design attention mechanisms on high-level features, which ignore the low-level features with more details. The proposed method adopts non-local networks which can aggregate features according to feature correlation at any level. There are two contributions of this work can be summarized as follows: (i) The spatial and temporal redundancy in video-based person Re-ID is analyzed in this work; (ii) An Efficient Non-local Attention Network is designed to reduce the computation complexity by exploring spatial and temporal redundancy for video-based person Re-ID. We conduct extensive experiments on two large-scale benchmarks, i.e. MARS and DukeMTMC-VideoReID. The experiments show that our model achieve 85.2% mAP, 88.3% rank-1 accuracy on MARS dataset and 95.4% mAP, 95.6% rank-1 on DukeMTMC-VideoReID without re-ranking, which significantly outperforms the state-of-arts.
A new nonlinear Guassian filter named new 5th-degree cubature Kalman filter is proposed based on the conventional 3rd-degree CKF,for a higher filter accuracy,stronger numeric stability,acceptable computation *** heart...
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ISBN:
(纸本)9781479946983
A new nonlinear Guassian filter named new 5th-degree cubature Kalman filter is proposed based on the conventional 3rd-degree CKF,for a higher filter accuracy,stronger numeric stability,acceptable computation *** heart of new CKF is 5th-degree spherical and radial rule that a new sampling approach for points and corresponding *** 5th-degree CKF may provide a suboptimal solution for high-dimensional nonlinear system with higher accuracy than 3rd-degree and lower calculation than 5th-degree Gauss-Hermite quadrature *** is a comparison of filter accuracy and numeric stability in nonlinear initial alignment of SINS between 3rd,5th and new *** results demonstrate that the new CKF has higher estamination accuracy and stronger stability with important application value.
Fulcrum combines two encoding stages, first using one high Galois field, such as GF(2~8) and then with the binary Galois field GF(2). This allows intermediate and end devices, depending their computation power, to sel...
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ISBN:
(纸本)9783800749485
Fulcrum combines two encoding stages, first using one high Galois field, such as GF(2~8) and then with the binary Galois field GF(2). This allows intermediate and end devices, depending their computation power, to select either field to recode and decode coded packets. To ensure a high decoding probability, Fulcrum codes introduce r expansion packets at the outer coding stage, to increase the chance of producing linearly independent packets. However, the fixed number r hinder the chance of obtaining both high decoding probability and efficient transmission at a reduced computation complexity. We propose tunable expansion packet (TEP) protocols, which adjust the extra coefficients in the outer coding stage based on feedback from receivers. Comprehensive evaluations show that TEP protocols significantly increase goodput and reduce computation complexity while maintaining a low overhead.
The requirement of algorithm for detecting small target in infrared image sequences is not only a high rate to identify the true target and a low false alarm rate, but also the computation efficiency. By employing the...
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ISBN:
(纸本)0780393953
The requirement of algorithm for detecting small target in infrared image sequences is not only a high rate to identify the true target and a low false alarm rate, but also the computation efficiency. By employing the selective attention mechanism, biological visual system can interpret a complex incoming image in real time with limited hardware resources. Much evidence has suggested that the biological visual system processes information in a serial strategy which rapidly selects a small relevant region in scene for further complex and time consuming analysis. In this paper, a two component computation scheme is proposed to detect dim targets in infrared image sequences. In the first process stage, an efficient method is applied to extract the potential targets which are further identified in second phase, the true targets are detected, and the spurious objects are rejected. The attention-based approach reduces the computation complexity, while the other performance aspects are not traded off. Experimental results indicate that the proposed extraction and recognition modules exhibit excellent performance of detecting small target in infrared image sequences, especially in process speed aspect.
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