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Liu Si, Zhang Degan, Liu Xiaohuan, Zhang Ting, Wu Hao. An Adaptive Repair Algorithm for AODV Routing Based on Decision Region[J]. Journal of Computer Research and Development, 2020, 57(9): 1898-1910. DOI: 10.7544/issn1000-1239.2020.20190508
Citation: Liu Si, Zhang Degan, Liu Xiaohuan, Zhang Ting, Wu Hao. An Adaptive Repair Algorithm for AODV Routing Based on Decision Region[J]. Journal of Computer Research and Development, 2020, 57(9): 1898-1910. DOI: 10.7544/issn1000-1239.2020.20190508

An Adaptive Repair Algorithm for AODV Routing Based on Decision Region

Funds: This work was supported by the National Natural Science Foundation of China (61571328), the Tianjin Key Natural Science Foundation (18JCZDJC96800), the Major Projects of Science and Technology in Tianjin (15ZXDSGX 00050), the Training Plan of Tianjin Science and Technology Innovation Team (TD12-5016, TD13-5025, TD2015-23), and the Major Projects of Science and Technology for Their Services in Tianjin (16ZXFWGX00010, 17YFZCGX00360).
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  • Published Date: August 31, 2020
  • The significant advantages of ad hoc on-demand distance vector (AODV) in control overhead, energy consumption and bandwidth occupation make it widely used in mobile ad hoc networks (MANET). However, in the high-speed mobile environment such as emergency rescue and disaster relief, and in the environment with high requirements for delay, the self-repair of AODV routing has the problem of delay. In order to solve this problem and make the improved AODV routing protocol more suitable for the environment of rescue and relief, an adaptive repair algorithm for AODV routing based on decision region (AR-AODV) is proposed. Firstly, according to the characteristics of the network for the environment, i.e. the nodes are uniformly deployed, a search formula is proposed, and the optimal solution of the formula is obtained. Then, the condition threshold for initiating the self-repair process is determined. Finally, in order to reduce the control cost, an algorithm for determining the optimization area is given. The simulation results show that the repair algorithm improves the efficiency of the routing. The mobile devices such as vehicles that are uniformly deployed are taken as the network nodes. The adaptive repair algorithm is tested in the actual scene of rescue and relief environment. The results show that the algorithm is consistent with the simulation results, and the overall performance is improved significantly.
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