A multicast-tree construction algorithm for efficient data collection over mobile networks of military vehicles

被引：0

作者：

Chang T.-Y. ^{[1
]}

Tsai J. ^{[1
]}

Huang W.-T. ^{[1
]}

机构：

[1] Department of Electrical Engineering, National Chung Hsing University, Taichung

来源：

Tsai, Jichiang (jichiangt@nchu.edu.tw) | 2018年 / Computer Society of the Republic of China卷 / 29期

关键词：

Data collection; Internet of Vehicles (IoV); Multicast tree;

D O I：

10.3966/199115992018102905001

中图分类号：

学科分类号：

摘要：

Due to tanks moving, joining and leaving, the wireless network topology formed by them will continuously change. Hence, how to make moving tanks to form a smart networking system is an important research issue. Moreover, the information exchange between nodes in a networking system can be performed via a multicast tree structure, and the root node can collect information from all the nodes in the structure. So in this paper, an algorithm is proposed to build an efficient distributed multicast tree construction algorithm for a mobile network. Such a multicast tree can be continually adjusted according to the latest topology information carried on message packets propagated among nodes. In addition, in all possible routing paths, a path with the lowest weight will be dynamically selected to improve the overall system messaging throughput. The above technique can be applied to make military vehicles form a smart networking system, including tanks, armored vehicles and transport vehicles, etc. Furthermore, through this network, the fast-changing situation of the battle can be immediately sent back to the server for the commander to refer to. © 2018 Computer Society of the Republic of China. All rights reserved.

引用

页码：1 / 4

页数：3

共 28 条

[1]

Jahanshahi M., Barmi A.T., Multicast routing protocols in wireless mesh networks: A survey, Computing, 96, 11, pp. 1029-1057, (2014)

[2]

Kolias C., Kambourakis G., Stavrou A., Gritzalis S., Intrusion detection in 802.11 networks: Empirical evaluation of threats and a public dataset, IEEE Communications Surveys & Tutorials, 18, 1, pp. 184-208, (2016)

[3]

Narmada A., Rao P.S., Zigbee based WSN with IP connectivity, Proc. 2012 International Conference on Computational Intelligence, Modelling and Simulation, (2012)

[4]

Yu B., Xu L., Li Y., Bluetooth low energy (BLE) based mobile electrocardiogram monitoring system, Proc. 2012 International Conference on Information and Automation, (2012)

[5]

Sheng Z., Mahapatra C., Zhu C., Leung V., Recent advances in industrial wireless sensor networks towards efficient management in IoT, IEEE Access, 3, pp. 622-637, (2015)

[6]

Al-Fuqaha A., Guizani M., Mohammadi M., Aledhari M., Ayyash M., Internet of things: A survey on enabling technologies, protocols, and applications, IEEE Communications Surveys & Tutorials, 17, 4, pp. 2347-2376, (2015)

[7]

Al-Fuqaha A., Khreishah A., Guizani M., Rayes A., Mohammadi M., Toward better horizontal integration among IoT services, IEEE Communications Magazine, 53, 9, pp. 72-79, (2015)

[8]

Cheng J.-J., Cheng J.-L., Zhou M.-C., Liu F.-Q., Gao S.-C., Liu C., Routing in internet of vehicles: A review, IEEE Transactions on Intelligent Transportation Systems, 16, 5, pp. 2339-2352, (2015)

[9]

Alam K.M., Saini M., Saddik A.E., Toward social Internet of Vehicles: Concept, architecture and applications, IEEE Access, 3, pp. 343-357, (2015)

[10]

Guo L., Dong M., Ota K., Li Q., Ye T., Wu J., Li J., A secure mechanism for big data collection in large scale Internet of Vehicle, IEEE Internet of Things Journal, 4, 2, pp. 601-610, (2017)

← 1 2 3 →