4.7 Article

Geographical and Topology Control-Based Opportunistic Routing for Ad Hoc Networks

Journal

IEEE SENSORS JOURNAL
Volume 21, Issue 6, Pages 8691-8704

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2021.3049519

Keywords

Routing; Interference; Energy consumption; Fading channels; Prediction algorithms; Topology; Pareto optimization; Topology control; opportunistic routing; ad hoc network; multi-objective optimization

Funding

  1. National Key Research and Development Program of China [2018YFB1800202, 2017YFB0803001]
  2. National Science Foundation of China [61571144, 61972089, 61672156]

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This paper proposes an efficient and reliable transmission power control-based opportunistic routing (ERTO) for wireless ad hoc networks. By considering network interference and fading channel, optimizing transmission power and forwarding node degree, introducing multi-objective optimization and Pareto optimal solutions, the energy consumption, transmission delay, and network throughput have been greatly improved in ERTO compared to previous works.
The opportunistic routing has great advantages on improving packet delivery probability between the source node and candidate forwarding set. For improving and reducing energy consumption and network interference, in this paper, we propose an efficient and reliable transmission power control-based opportunistic routing (ERTO) for wireless ad hoc networks. In ERTO, the network interference and fading channel, which are critical to routing performance but not considered in previous works, are investigated during the prediction of . The , the expected energy consumption, and the relationship between transmission power and node degree are applied to optimize the transmission power and forwarding node degree jointly. For improving routing effectiveness and reducing computational complexity, we introduce multi-objective optimization and Pareto optimal into ERTO. During the routing process, nodes calculate the optimal transmission power and forwarding node degree according to the properties of Pareto optimal solution set. Based on these innovations, the energy consumption, the transmission delay, and the network throughput have been improved greatly in ERTO compared with previous work. For instance, when the number of nodes is 120, the network throughput of ERTO is 1.41, 1.42, and 2.63 times larger than that in EEOR, TCOR, and ExOR, respectively.

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