Recently, blockchain-based covert communication has gained momentum, for the decentralization, anonymity, and immutability feature of blockchain. Nevertheless, some challenges impair its security and efficiency. Most ...
详细信息
ISBN:
(纸本)9798350333398
Recently, blockchain-based covert communication has gained momentum, for the decentralization, anonymity, and immutability feature of blockchain. Nevertheless, some challenges impair its security and efficiency. Most schemes have a weak generalization ability, and can merely be applied to a specific blockchain platform. Storage-based covert transmission schemes usually have limited space for data embedding, affecting their Information delivery efficiency. Besides, static data sifting rules raise the risk of information leakage. In this paper, we design DLCCB(Dynamic Labeling based Covert Communication on Blockchain). We first split the information to be delivered into several pieces and utilize the destination address of each transaction to embed them. Then a dynamic labeling method is proposed for updating sifting rules without extra negotiation between sender and receiver. Besides, we design two kinds of sifting algorithms, namely online and offline sifting algorithm. We perform our solution on Ropsten, a test net of Ethereum. The experiment result verifies the feasibility of our scheme.
As billions of transistors arc being placed on a few square millimeters of silicon, power dissipation is becoming a more crucial factor to be tackled for high performance computing. Reversible circuit synthesis has be...
详细信息
ISBN:
(纸本)9781538692769
As billions of transistors arc being placed on a few square millimeters of silicon, power dissipation is becoming a more crucial factor to be tackled for high performance computing. Reversible circuit synthesis has been considered as a promising direction for low power design due to its information lossless behavior. In addition, it forms the basis for quantum computing. However, synthesis of reversible circuits cannot be achieved with the classical approaches for irreversible logic due to the additional imposed constraints, consequently, neither fan-out nor feedback are allowed. Binary Decision Diagrams (BDDs) have been proposed as a compact data structure to represent a boolean function. They have been exploited to synthesize reversible circuits through proper mapping of each BDD's node into a cascade of reversible Toffoli gates. Nevertheless, reordering of BDD's nodes before circuit synthesis significantly impacts the overall cost of the synthesized circuit. In this paper, we present a comparative study for BDD reordering algorithms in terms of the cost of the generated reversible circuit. The studied algorithms include greedy, dynamic programming, and heuristic based approaches. The cost metric includes the number of lines, gate count, and quantum cost. Experimental results show that meta heuristic-based BDD reordering algorithms outperform other algorithms in terms of the overall synthesized circuit cost with slightly additional runtime. Thereafter, we conclude with a proposal for a new framework for reversible logic synthesis.
In this work, the authors focus on the quantum evolutionary quantum hybridization and its contribution in solving the binary decision diagram ordering problem. Therefore, a problem formulation in terms of quantum repr...
详细信息
In this work, the authors focus on the quantum evolutionary quantum hybridization and its contribution in solving the binary decision diagram ordering problem. Therefore, a problem formulation in terms of quantum representation and evolutionary dynamic borrowing quantum operators are defined. The sifting search strategy is used in order to increase the efficiency of the exploration process, while experiments on a wide range of data sets show the effectiveness of the proposed framework and its ability to achieve good quality solutions. The proposed approach is distinguished by a reduced population size and a reasonable number of iterations to find the best order, thanks to the principles of quantum computing and to the sifting strategy.
The empirical mode decomposition (EMD) was a method pioneered by (N. Huang et al., The empirical mode decomposition and the Hilbert spectrum for nonlinear nonstationary time series analysis, Proc. Roy. Soc. Lond. A 45...
详细信息
The empirical mode decomposition (EMD) was a method pioneered by (N. Huang et al., The empirical mode decomposition and the Hilbert spectrum for nonlinear nonstationary time series analysis, Proc. Roy. Soc. Lond. A 454 (1998) 903-995) as an alternative technique to the traditional Fourier and wavelet techniques for studying signals. It decomposes a signal into several components called intrinsic mode functions (IMFs), which have shown to admit better behaved instantaneous frequencies via Hilbert transforms. In this paper, we propose an alternative algorithm for EMD based on iterating certain filters, such as Toeplitz filters. This approach yields similar results as the more traditional sifting algorithm for EMD. In many cases the convergence can be rigorously proved.
There are some methods to decompose a signal into different components such as: Fourier decomposition and wavelet decomposition. But they have limitations in some aspects. Recently, there is a new signal decomposition...
详细信息
There are some methods to decompose a signal into different components such as: Fourier decomposition and wavelet decomposition. But they have limitations in some aspects. Recently, there is a new signal decomposition algorithm called the Empirical Mode Decomposition (EMD) algorithm which provides a powerful tool for adaptive multiscale analysis of nonstationary signals. Recent works have demonstrated that EMD has remarkable *** in time series decomposition, but EMD also has several problems such as scale mixture and convergence property. This paper proposes two key points to design Bandwidth EMD to improve on the empirical mode decomposition algorithm. By analyzing the simulated and actual signals, it is confirmed that the Intrinsic Mode Functions (IMFs) obtained by the bandwidth criterion can approach the real components and reflect the intrinsic information of the analyzed signal. In this paper, we use Bandwidth EMD to decompose electricity consumption data into cycles and trend which help us recognize the structure rule of the electricity consumption series.
In a decision diagram, the average path length (APL) is the average number of nodes on a path from the root node to a terminal node over all assignments of values to variables. Smaller APL values result in faster eval...
详细信息
In a decision diagram, the average path length (APL) is the average number of nodes on a path from the root node to a terminal node over all assignments of values to variables. Smaller APL values result in faster evaluation of the function represented by a decision diagram. For some functions, the APL depends strongly on the variable order. In this paper, we propose an exact and a heuristic algorithm to determine the variable order that minimizes the APL. Our exact algorithm uses branch-and-bound. Our heuristic algorithm uses dynamic reordering, where selected pairs of variables are swapped. This paper also proposes an exact and a heuristic algorithm to determine the pairs of binary variables that reduce the APL of multi-valued decision diagrams (MDDs) for a 4-valued input 2-valued output function. Experimental results show that the heuristic algorithm is much faster than the exact one but produces comparable APLs. Both algorithms yield an improvement over an existing algorithm in both APL and runtime. Experimental results for 2-valued cases and 4-valued cases are shown.
Ordered binary decision diagrams (OBDDs) have been widely used in many CAD applications as efficient data structures for representing and manipulating Boolean functions. For the efficient use of the OBDD, it is essent...
详细信息
Ordered binary decision diagrams (OBDDs) have been widely used in many CAD applications as efficient data structures for representing and manipulating Boolean functions. For the efficient use of the OBDD, it is essential to find a good variable order, because the size of the OBDD heavily depends on its variable order. Dynamic variable reordering is a promising solution to the variable ordering problem of the OBDD. Dynamic variable reordering with the sifting algorithm is especially effective in minimizing the size of the OBDD and reduces the need to find a good initial variable order. However, it is very time-consuming for practical use. In this paper, we propose two new implementation techniques for fast dynamic variable reordering. One of the proposed techniques reduces the number of variable swaps by using the lower bound of the OBDD size, and the other accelerates the variable swap itself by recording the node stares before the swap and the pivot nodes of the swap. By using these new techniques, we have achieved the speed-up ranging from 2.5 to 9.8 for benchmark circuits. These techniques have reduced the disadvantage of dynamic variable reordering and have made it more attractive for users.
暂无评论