In order to solve the security issues of mobile vehicles in the Internet of vehicles, such as identity authentication and integrality verification, we apply the trusted cryptography module (TCM) into the on-vehicle el...
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In order to solve the security issues of mobile vehicles in the Internet of vehicles, such as identity authentication and integrality verification, we apply the trusted cryptography module (TCM) into the on-vehicle electronic systems. TCM has many security features, such as integrality measurement, integrality report and protected storage, by which the on-vehicle electronic systems achieve a trusted boot process. Data and information of vehicles are encrypted before storage and transmission. The experiments show that with the authorization on the vehicular platform, the TCM will improve the credibility and security of the Internet of Vehicles.
With the rapid development of vehicle electronic systems, the vehicle software failure rate has also been rising over time. Providing the convenient and effective maintenance on the vehicle software has become a funda...
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ISBN:
(纸本)9787894631046
With the rapid development of vehicle electronic systems, the vehicle software failure rate has also been rising over time. Providing the convenient and effective maintenance on the vehicle software has become a fundamental block constraining the progress of vehicle electronic industry. A trusted remote remediation framework for vehicle software is presented and realized to enable drivers to online upgrade version or fix bug without needing for driving the vehicles back to the factories or using the specific devices. In this framework, the trusted remediation server takes responsibility for managing and providing the patch programs and the trusted remediation client can download directly from the remediation server to upgrade programs or fix software errors, achieving the self-repair in complex vehicular networks.
The rigorous theoretical analyses of algorithms for #SAT have been proposed in the literature. As we know, previous algorithms for solving #SAT have been analyzed only regarding the number of variables as the paramete...
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The satisfiability problem is the core problem in artificial intellgence. The algorithm directional resolution(DR) is a well known method based on resolution for satisfiability problem. But the number of clauses has g...
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The satisfiability problem is the core problem in artificial intellgence. The algorithm directional resolution(DR) is a well known method based on resolution for satisfiability problem. But the number of clauses has great impact on the efficiency of the method. In this paper, an algorithm SRDR is proposed to solve the problem. SRDR is based on algorithm DR and splitting rule. By using splitting rule, the number of clauses can be reduced obviously. Furthermore, the strategy MO is designed for SRDR. With the strategy, we can get a better order of variables and the efficiency of SRDR is improved. The experimental data shows that SRDR is more efficient that DR.
In recent years, with the development of the wireless sensor networks, the localization method receives the attention of many researchers. However, due to the network cost and characteristics of sensor nodes, most of ...
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In recent years, with the development of the wireless sensor networks, the localization method receives the attention of many researchers. However, due to the network cost and characteristics of sensor nodes, most of the localization algorithms are not well suitable for the wireless sensor network, positioning error is relatively large. Based on the regular moving anchor node and RSSI ranging technique assisting positioning, in this paper, we proposed the RMADV-Hop (Regular Moving Anchor DV-Hop) localization algorithm to improve the DV-Hop algorithm. In the same network condition, we simulated these two localization algorithms using the omnet++ simulation software. Simulation results show that RMADV-Hop algorithm uses less anchor nodes than the DV-Hop algorithm, reduces the cost of network hardware, approximately achieves the evenly distribution of anchor nodes, and can get higher positioning accuracy than the DV-Hop algorithm in the randomly distributed network.
A novel self-adaptive differential evolution (SADE) algorithm is proposed in this paper. SADE adjusts the mutation rate F and the crossover rate CR adaptively, taking account of the different distribution of populatio...
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The satisfiability (SAT) problem is an important problem of automated reasoning. In the past decades, many methods of SAT are proposed, such as method based on resolution, method based on tableau and method based on e...
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The satisfiability (SAT) problem is an important problem of automated reasoning. In the past decades, many methods of SAT are proposed, such as method based on resolution, method based on tableau and method based on extension rule. Based on the study of extension rule, we find that the SAT problem can be solved with hitting set algorithms. If we can find a hitting set of a clause set, and if there is not any pair of complementary literals in the hitting set, the clause set is satisfiable. Algorithm BHS based on Boolean algebra proposed by Jiang is an efficient hitting set algorithm. SSBF proposed in this paper is a revised algorithm of BHS that can be used to judge the satisfiability of a clause set. The test result shows that SSBF is an efficient algorithm.
The major problem in developing a useful formalism for reasoning about spatial information is the trade off between expressive power and computational tractability. Based on Bennett's modal representation of conve...
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The major problem in developing a useful formalism for reasoning about spatial information is the trade off between expressive power and computational tractability. Based on Bennett's modal representation of convex-hull and the RCC62 model which describes the topological relation between simple concave regions, the modal representation of RCC62 is presented in this paper, which has a theoretical advantage over 1st-order representations.
Particle swarm optimization (PSO) algorithm is a robust and efficient approach for solving complex real-world problems. In this paper, a modified particle swarm algorithm (IMPSO) is introduced for unconstrained global...
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Particle swarm optimization (PSO) algorithm is a robust and efficient approach for solving complex real-world problems. In this paper, a modified particle swarm algorithm (IMPSO) is introduced for unconstrained global optimization. The whole swarm is partitioned to three different sub-populations according to their fitness, and different velocity updating strategies are used to different sub-populations. Besides, we take advantage of crossover to maintain the diversity of the swarm and avoid getting into local optimum. IMPSO are extensively compared with other two modified PSO algorithms on three well-known benchmark functions with different dimensions. Experimental results show that IMPSO achieves not only better solutions but also faster convergence.
Conventional models based on crisp regions can not deal with the Direction Relations between Uncertain Regions (DRUR). Using broad boundary to represent the uncertain boundary, a novel approach is proposed based on mo...
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Conventional models based on crisp regions can not deal with the Direction Relations between Uncertain Regions (DRUR). Using broad boundary to represent the uncertain boundary, a novel approach is proposed based on model SK for modeling DRUR in this paper. DRUR are described as the combinations of basic cardinal direction relations, then we study the composition of DRUR, and a method is put forward for calculating this composition.
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