Abstract:Because of the opening of In-vehicle network, there are several important problems to be dealt with, such as the security and validity of data. Firstly, the article builds a construct model based on driving behavior and speed. Secondly, it makes an analysis of preventing data injection by using the construct model above and the naive Bayesian network classifier, so as to take effective measures to guarantee the vehicle security. In the end, an experimental simulation is carried out to prove that the proposed method can effectively improve the accuracy of data quality analysis and lower the false rate as well.

Abstract:Intelligence has given the Internet more practical value, but the dual requirements for both the computing power and low power consumption in the current single-processor networking equipment have not been met. The heterogeneous multiprocessor architecture can combine the advantages of different processors with a single or isomorphic multiprocessor to select the right processor to meet the requirements for both high-performance and low-power intelligent device. At present, the software programming under heterogeneous multiprocessor structure and how to optimize the performance of top-level applications on multiprocessor devices are the technical problems that need to be solved. In view of the problems above, this paper designs and implements an adaptive command interpretation system for heterogeneous multiprocessor devices. First, the system allows users to install the Internet of Things application to the device in the form of URL access, and the application is presented in the form of a command script contained in the URL. Secondly, the system designs an automatic distribution algorithm for commands on heterogeneous multiprocessor devices, which adds the energy consumption parameters on the basis of the DAG graph model, and designs a command distribution scheme with the best energy consumption under the condition of satisfying the time limit. Finally, the system is faced with the problem of satisfying the needs of different users at the same time, but the resources of the equipment in the Internet of Things are limited. So the system needs to be customized according to the specific users. This paper presents a self-adaptive scheme of command interpretation system based on users' habits, which can automatically complete the system adapting based on users' specific habits.

Abstract:This paper considers using Rechargeable Sensor nodes (RS) to capture important events. For the defect of simple atomic event information, it considers the composite events composed of multiple atomic events. The paper proposes a novel composite event capture strategy. Firstly, it turns the composite event capture rate into an optimization problem through establishing a mathematical model, and analyzes the main factors affecting composite event capture rate on the whole. Then, it translates the multi-node cooperative problem into a task allocation problem. A total tasks assignment allocation algorithm based on greedy algorithm (TTAA) is put forward, and according to the specific circumstances of each RS (CTAA), a child task allocation algorithm is proposed. Finally, the paper has carried out the simulation experiment, the experimental results show that the proposed strategy can achieve higher rate for the composite event.

Abstract:Energy saving and the tracking performance are two important issues in moving target tracking. This paper presents a Voronoi structure-based nodes selection algorithm, which constructs a network model based on the property of Voronoi, and selects sensor nodes which are more close to the target to participate in tracking. This paper also presents a nodes scheduling mechanism, which minimizes the number of awaking nodes with tracking quality guarantee. Finally, a set of simulation experiments are made to analyze the effects of various parameters on the network performance. Experimental results show the excellent performance of the proposed algorithm in terms of energy saving and tracking quality.

Abstract:During the process of Least Square localization, some negative factors may give rise to different levels of noise, such as the environmental noise, the reflection, refraction, multipath and non-line-of sight (NLOS) complex propa gation of wireless signal, and the limitation of distance estimation method. And they also lead to low localization accuracy of Least Square localization. For this problem, this paper proposes an improved Least Square localization method, which is called Least Square localization based on anchor nodes optimization selection through minimum standard deviation (LS-ANOS). In LS-ANOS method, nanoLOC-based Symmetric Double Sided Two Way Ranging (SDS-TWR) is utilized to conduct distance estimation repeatedly between unknown nodes and anchor nodes. And statistical computation is performed on these distance estimation results. Then, from the influential mechenism of input measurement noise on localization result, the paper adopts slide window-based single scanning strategy to optimize the selection of the distance estimation result with higher quality and the corresponding anchor nodes. Lastly, based on the least square localization computation, it gets the accurate localization result. Simulation and experimental results demonstrate that the proposed method could improve the accuracy of Least Square localization method effectively.

Abstract:With the breakthrough in the technology of wireless power transmission, wireless-powered body sensor nodes are able to harvest radio frequency (RF) energy from RF-based chargers and thus operate continuously. Rational planning of the number and positions of the chargers is an effective way to improve the charging efficiency and save deployment budget. Previous studies on RF-based charger placement mainly consider the scenario that nodes are static, or convert to the static scenario using probability statistical model. With the background of mobile body area network, this paper considers the situation that users carrying sensor nodes have specific sojourn-move behavior patterns. Based on this behavior model, charger placement optimization problem is formulated with the constraint of node's non-outage probability. Both greedy and divide-and-conquer based particle swarm optimization (D&C-PSO) approaches are proposed to solve the problem. Finally, performances of the two proposed algorithms are evaluated and compared with existing path provisioning approach through various simulations. Simulation results show that the divide-and-conquer based particle swarm optimization outperforms both greedy and path provisioning approaches in the charger placement cost while it guarantees the node's non-outage probability.

Abstract:Connectivity is the guarantee of network communication, and connective equilibrium is an important indicator of the network connectivity. With the frequent changes of topology of opportunistic sensor network, the traditional graph model is not applicable for modeling opportunistic sensor network. This paper aims at how to accurately depict the connective equilibrium degree of opportunistic sensor network. The contribution degree and clustering coefficient of Ferry nodes are defined, and connective equilibrium degree is defined as well, which can reflect the connectivity balance of the network. The connective equilibrium model of opportunistic sensor network is proposed based on the temporal varying graph. The simulation results show that the proposed model can reflect the connective equilibrium of the network. Furthermore, it can provide an effective support for exploiting involution and maintenance of opportunistic sensor network.

Abstract:In mobile social networks, nodes are clustered by their interests and hobbies, and take part in some activities periodically. This paper puts forward an activity-based message opportunistic forwarding algorithm (AMOF) for the network characteristics. The main idea is that the biggest delivery probability node is selected and message is transferred to it, if the source node and destination node are both present in the same activities. While they are not in the same activities, the best link of the indirect delivery probability is found, and message will be transferred to it. Simulation results show that the proposed routing algorithm can not only improve the success of message delivery, but also reduce the network delay and overhead, compared with classical routing algorithms, such as Epidemic, PRoPHET, CMOT and CMTS.

Abstract:Energy is the main problem that restricts the development of wireless sensor networks. The emergence of rechargeable sensor networks has played a significant role in its development. This paper presents a cooperative wireless charging strategy for wireless sensor networks based on RFID tags and according to different communication methods, specifically it proposes two schemes:TBR and TDC.The nodes in the network are clustered, and the nodes in the cluster are charged and the data is collected by cluster readers. Bus readers are moving among these clusters and collecting data from cluster reader. Finally, bus readers transfer the data to the sink node for data processing. By clustering the node charging and the hierarchical processing of data collection are completed. The simulation results show that the cooperative charging strategy can be applied to the network deployed in large areas, and the minimum number of mobile readers is guaranteed. The delay of data transmission to the sink nodes is the shortest, and the TBR scheme and TDC scheme are effective.

Abstract:The incentive mechanism based on electronic money, a common method in the field of information network, plays an important role in promoting the resource sharing, stimulating crowd sensing and promoting cooperative communication, and it is the key to improve the quality and efficiency of information network service. This paper summarizes the existing work of the incentive mechanisms, describes the objectives and challenges of the incentive mechanism, and focuses on the incentive mechanism on a trust center and the distributed incentive mechanism based on the block chain. It also discusses the security, credibility, privacy protection and extensibility of incentive mechanism based on electronic money.

Abstract:With the rapid growth of the number of motor vehicles in China, inevitably there would appear a series of severe problems concerning safety and traffics. At the same time, the video image files are increasing at an explosive speed, which has brought a lot of trouble to the public security monitoring, criminal investigation and the case detection. It is important to research an efficient and accurate vehicle detection algorithm. This paper proposes a new deep convolution neural networks frame for vehicle detection and coarse grained recognition based YOLO method. Multilayer perceptron convolution layers are added in the new network structure framework to enhance nonlinear ability of feature mapping. This framework deletes fully connected layers and predicts the bounding boxes using anchor boxes. The new framework improves recall rates of object detection and effectively reduces computational complexity. Experimental results show that the improved method has an average accuracy of 94.7% for vehicle detection under iteration 20000 times. Compared with other detection methods, the processing speed and accuracy of the new method have been improved.

Abstract:Traditional stationary wireless sensor networks usually have problems, such as low tracking quality, high energy consumption and so on, during the process of target tracking. More and more mobile elements, i.e., mobile sensors, are used in wireless sensor networks and thus bring new solutions for target tracking. The existing research usually confuses detecting the target with locating the target. After distinguishing between the detection-centric and localization-centric methods, this paper reviews specifically the current research status of the detection-centric target tracking methods. By comparing the merits and demerits of the existing methods in aspects like tracking quality, energy consumption, etc., it reveals their problems. In the end, it summarizes some possible research hotspots and tendency of mobile solutions in many aspects.