Current Issue : July - September Volume : 2021 Issue Number : 3 Articles : 5 Articles
How to improve delay-sensitive traffic throughput is an open issue in vehicular communication networks, where a great number of vehicle to infrastructure (V2I) and vehicle to vehicle (V2V) links coexist. To address this issue, this paper proposes to employ a hybrid deep transfer learning scheme to allocate radio resources. Specifically, the traffic throughput maximization problem is first formulated by considering interchannel interference and statistical delay guarantee. The effective capacity theory is then applied to develop a power allocation scheme on each channel reused by a V2I and a V2V link. Thereafter, a deep transfer learning scheme is proposed to obtain the optimal channel assignment for each V2I and V2V link. Simulation results validate that the proposed scheme provides a close performance guarantee compared to a globally optimal scheme. Besides, the proposed scheme can guarantee lower delay violation probability than the schemes aiming to maximize the channel capacity....
Source location privacy, one of the core contents of Wireless Sensor Network (WSN) security, has a significant impact on extensive application of WSNs. In this paper, a novel location privacy protection routing scheme called Energy Balanced Branch Tree (EBBT) is proposed by using multibranch and fake sources. This scheme has three phases. In the first place, the data of the source are randomly sent to a certain intermediate node. Then, a minimum hop routing (MHR) from the intermediate node to the base station is formed. Then, branch paths with fake sources are generated dynamically from some nodes on the MHR path. Finally, a tree-shaped structure from real source nodes and fake source nodes to the base station is achieved. In difference to the previous schemes, the location of the real source in the EBBT scheme does not affect the location and the number of fake sources. During the formation of the tree-shaped multibranch paths, the residual energy of nodes is considered sufficiently, and the control of the direction of each branch path is also involved. The influence of the number and length of branches on the network lifetime and network security is also investigated. Experimental results show that the proposed algorithm has the advantages of long network security period and lifetime, as well as high path diversity. Our simulation further illustrates that the EBBT scheme has favorable privacy of the source location without changing the network lifetime....
The rapid development of the Global Positioning System (GPS) devices and location-based services (LBSs) facilitates the collection of huge amounts of personal information for the untrusted/unknown LBS providers. This phenomenon raises serious privacy concerns. However, most of the existing solutions aim at locating interference in the static scenes or in a single timestamp without considering the correlation between location transfer and time of moving users. In this way, the solutions are vulnerable to various inference attacks. Traditional privacy protection methods rely on trusted third-party service providers, but in reality, we are not sure whether the third party is trustable. In this paper, we propose a systematic solution to preserve location information. The protection provides a rigorous privacy guarantee without the assumption of the credibility of the third parties. The user’s historical trajectory information is used as the basis of the hidden Markov model prediction, and the user’s possible prospective location is used as the model output result to protect the user’s trajectory privacy. To formalize the privacy-protecting guarantee, we propose a new definition, L&A-location region, based on k-anonymity and differential privacy. Based on the proposed privacy definition, we design a novel mechanism to provide a privacy protection guarantee for the users’ identity trajectory. We simulate the proposed mechanism based on a dataset collected in real practice. The result of the simulation shows that the proposed algorithm can provide privacy protection to a high standard....
Deep reinforcement learning is one kind of machine learning algorithms which uses the maximum cumulative reward to learn the optimal strategy. The difficulty is how to ensure the fast convergence of the model and generate a large number of sample data to promote the model optimization. Using the deep reinforcement learning framework of the AlphaZero algorithm, the deployment problem of wireless nodes in wireless ad hoc networks is equivalent to the game of Go. A deployment model of mobile nodes in wireless ad hoc networks based on the AlphaZero algorithm is designed. Because the application scenario of wireless ad hoc network does not have the characteristics of chessboard symmetry and invariability, it cannot expand the data sample set by rotating and changing the chessboard orientation. The strategy of dynamic updating learning rate and the method of selecting the latest model to generate sample data are used to solve the problem of fast model convergence....
A class of nonlinear networked systems with external interference is designed in this paper. Currently, we have witnessed that networked control technology has played a key role in the Internet of Things (IoT). However, the amount of big data in the Internet of Things will cause network congestion in the data transmission of the network control system. In order to solve this problem, event-driven control scheme can effectively save the network resources of the network control system. But when there is interference in the system, the conventional constant threshold parameter is difficult to achieve the expected energy-saving effect. In order to solve this challenge, this paper proposes a design with a continuously variable threshold. After each trigger to transmit data, the threshold gets changed accordingly, and the sliding mode approach rate is changed simultaneously. Compared with the constant threshold event drive, the number of transmissions in this design can be greatly reduced, while sliding mode jitter is suppressed. The simulation results show that the scheme can achieve higher resource utilization efficiency and better robustness....
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