ISSN 1000-1239 CN 11-1777/TP

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    Journal of Computer Research and Development    2017, 54 (11): 2419-2420.  
    Abstract1042)   HTML11)    PDF (450KB)(689)       Save
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    Trajectory Prediction Algorithm in VANET Routing
    Li Yang, Wang Zhe, Zhang Chuwen, Dai Huichen, Xu Wenquan, Ji Xuefeng, Wan Ying, Liu Bin
    Journal of Computer Research and Development    2017, 54 (11): 2421-2433.   DOI: 10.7544/issn1000-1239.2017.20170359
    Abstract1498)   HTML5)    PDF (5253KB)(997)       Save
    In vehicular ad hoc network (VANET), geographic routing protocols can preferably adapt to frequent topology changes and unstable link quality. Beacon messages are needed to share the positions of neighboring nodes, so forwarding decisions in the interval of successive beacon messages may be inaccurate due to the movement of the vehicle nodes. In this situation, trajectory prediction is needed to amend the positions of the vehicle nodes. Existing prediction algorithms are either lack of universality or suffered from large prediction errors. To solve the problems above, this paper proposes a new trajectory prediction algorithm, which is based on the measurement result that the vehicle accelerations obey normal distribution. The new algorithm uses linear regression to do the prediction and applies a feedback mechanism to amend error. The new trajectory prediction algorithm can greatly improve the prediction accuracy in several real trajectory trace tests. Then this paper proposes a new position based instant routing protocol. In instant routing protocol, a forwarder uses the predicted position of neighboring nodes and destination node to calculate the next hop. We apply our new trajectory prediction algorithm in instant routing to predict and update vehicle positions in real time. We use SUMO to generate real maps and vehicle trajectory traces, and use NS3 to do the simulation. Experimental results show that instant routing with the new trajectory prediction algorithm outperforms the traditional GPSR protocol and instant routing without trajectory prediction in terms of packet delivery ratio and network latency, while reducing protocol processing overhead remarkably.
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    Adaptive Trajectory Prediction for Moving Objects in Uncertain Environment
    Xia Zhuoqun, Hu Zhenzhen, Luo Junpeng, Chen Yueyue
    Journal of Computer Research and Development    2017, 54 (11): 2434-2444.   DOI: 10.7544/issn1000-1239.2017.20170309
    Abstract1118)   HTML3)    PDF (4266KB)(804)       Save
    The existing methods for trajectory prediction are difficult to describe the trajectory of moving objects in complex and uncertain environment accurately. In order to solve this problem, this paper proposes an self-adaptive trajectory prediction method for moving objects based on variation Gaussian mixture model (VGMM) in dynamic environment (ESATP). Firstly, based on the traditional mixture Gaussian model, we use the approximate variational Bayesian inference method to process the mixture Gaussian distribution in model training procedure. Secondly, variational Bayesian expectation maximization iterative is used to learn the model parameters and prior information is used to get a more precise prediction model. This algorithm can take a priory information. Finally, for the input trajectories, parameter adaptive selection algorithm is used automatically to adjust the combination of parameters, including the number of Gaussian mixture components and the length of segment. Experimental results perform that the ESATP method in the experiment shows high predictive accuracy, and maintains a high time efficiency. This model can be used in products of mobile vehicle positioning.
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    Joint Routing and Scheduling in Cognitive Radio Vehicular Ad Hoc Networks
    Zhang Huyin, Wang Jing, Tang Xing
    Journal of Computer Research and Development    2017, 54 (11): 2445-2455.   DOI: 10.7544/issn1000-1239.2017.20170377
    Abstract1003)   HTML2)    PDF (2538KB)(703)       Save
    Cognitive radio vehicular ad hoc networks (CR-VANETs) have been envisioned to solve the problem of spectrum scarcity and improved spectrum resource efficiency in vehicle-to-vehicle communication by exploiting cognitive radio into the vehicular ad hoc networks. Most existing routing protocols for cognitive radio networks or vehicular ad hoc networks cannot be applied to CR-VANETs directly due to the high-speed mobility of vehicles and dynamically changing availability of cognitive radio channels. At present, the routing research for CR-VANETs is relatively few. How to utilize the spectrum resources effectively and moreover reduce the spectrum band consumption caused by routing hops is still a pending problem. Aspiring to meet these demands and challenges, this paper presents a joint routing and scheduling, which combines the scheduling of spectrum resources and the goal of minimizing routing hops in CR-VANETs. To achieve this goal, we first establish a network model and a CR spectrum model to predict the contact duration between vehicles and the probability of spectrum availability. We define the communication link consumption and the weight of channel according to these parameters. Then we transform the optimization objective into a routing scheme with minimizing hop count, subject to constraint on the scheduling of spectrum resource, and moreover prove this routing scheme is NP-hard. To tackle this issue, a hybrid heuristic algorithm is composed by a particle swarm optimization with fast convergence and a genetic algorithm with population diversity. Simulation results demonstrate that our proposal provides better routing hop counts compared with other CR-VANETs protocols.
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    Attribute Based Encryption Method with Revocable Dynamic and Static Attributes for VANETs
    He Qian, Liu Peng, Wang Yong
    Journal of Computer Research and Development    2017, 54 (11): 2456-2466.   DOI: 10.7544/issn1000-1239.2017.20170373
    Abstract1099)   HTML1)    PDF (2531KB)(598)       Save
    The data secure sharing in vehicular ad hoc network (VANET) usually uses group encryption mode. However it is difficult to construct group and to manage group key for vehicular terminal with high mobility. Ciphertext-policy attribute-based encryption (CP-ABE) is a kind of new solution for VANETs' communication security. In the traditional CP-ABE strategy, it has several shortcomings, such as high decryption computation complex, and attributes revoking requires the re-encrypting of the whole cipher-text and the inflexible construction of access policy tree. These shortcomings lead to the limited application of CP-ABE in VANETs. In order to solve these problems, an ABE with revocable dynamic and static attributes (ABE-RDS) is proposed for the data secure sharing of cloud storage in VANETs. In the ABE-RDS, dynamic attribute and static attribute are managed separately, and combination policy tree is constructed, and main decryption part with high computation cost is delegated to servers using decryption proxy. In addition, the vehicular terminal can revoke attributes and refresh dynamic attributes through global and local trusted authority. The proposed ABE-RDS is secure, and it has superiority over traditional CP-ABE in space and time complexity. The performance of ABE-RDS in vehicular terminal decryption, attribute revocation, and system concurrent is evaluated with experiments.
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    Trajectory Privacy Protection Based on Road Segment Report in VANETs
    Wu Xuangou, Wang Pengfei, Zheng Xiao, Fan Xu, Wang Xiaolin
    Journal of Computer Research and Development    2017, 54 (11): 2467-2474.   DOI: 10.7544/issn1000-1239.2017.20170371
    Abstract925)   HTML3)    PDF (3328KB)(747)       Save
    Vehicular ad hoc networks (VANETs) provide the related techniques and solutions for intelligent transportation, urban planning, pollution reduction and other issues. VANET applications usually require vehicle users to report continuous road location information, which brings a serious threat to personal trajectory privacy. However, the existing trajectory protection techniques are mainly focused on location-based protection, which cannot be applied to road segment based trajectory privacy protection effectively. In this paper, we propose a new road segment data gathering framework with trajectory privacy protection consideration in VANETs. In our framework, we give the trajectory privacy protection definition, formulate the problem model of road segment based data report, and prove that the problem is a NP-hard problem. In addition, we also present approximated algorithms to solve the problem. The experimental results show that our algorithms have good performance in both user's trajectory protection and coverage rate of data gathering.
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    Emergency Message Broadcast Method Based on Huffman-Like Coding
    Wu Libing, Fan Jing, Wang Jing, Nie Lei, Wang Hao
    Journal of Computer Research and Development    2017, 54 (11): 2475-2486.   DOI: 10.7544/issn1000-1239.2017.20170368
    Abstract917)   HTML5)    PDF (4552KB)(667)       Save
    The development of urban city greatly promotes the application of vehicular ad-hoc network, among which the safety-related emergency message broadcast is one of the key research points. The emergency message broadcast needs to meet the requirements for the quality of service such as low latency, high reliability, high scalability and so on. Most existing emergency message broadcasting methods, when selecting the next hop forwarding node, assume that there is an approximately equal probability of being selected as the relay area for each location, and the nodes of all positions are treated equally, which lacks the study of the distribution of the optimal node position so that it cannot adapt well to the distribution of the optimal forwarding node. However, the key to reducing the delay in emergency messaging is to quickly determine the appropriate relay forwarding node. Therefore, in order to further improve the timeliness of emergency message broadcasting and reduce the propagation delay, in this paper, we propose a Huffman coding-based emergency message broadcasting method. Generally, we first analyze the probability distribution of the optimal forwarding nodes in urban roads. And based on it, we then use the principle of Huffman coding to design a fast partition method, which can achieve the goals of quickly selecting optimal relay node, reducing the delay of emergency message broadcast, and improving the speed of emergency message transmission by minimizing the optimal node selection time. Our simulation results show that the proposed method can reduce the delay of emergency message broadcasts in different scenarios by 5.3%~18.0%, and improve the speed of emergency message transmission by 8.9%~24.5%.
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    Cited: Baidu(3)