SD-GPSR: A Software-Defined Greedy Perimeter Stateless Routing Method Based on Geographic Location Information
Shaopei Gao,
Qiang Liu (),
Junjie Zeng and
Li Li
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Shaopei Gao: Beijing Key Lab of Transportation Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
Qiang Liu: Beijing Key Lab of Transportation Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
Junjie Zeng: Institute of Telecommunication and Navigation Satellites, China Academy of Space Technology, Beijing 100094, China
Li Li: Wuhan Maritime Communication Research Institute, Wuhan 430079, China
Future Internet, 2024, vol. 16, issue 7, 1-17
Abstract:
To mitigate the control overhead of Software-Defined Mobile Ad Hoc Networks (SD-MANETs), this paper proposes a novel approach, termed Software-Defined Greedy Perimeter Stateless Routing (SD-GPSR), which integrates geographical location information. SD-GPSR optimizes routing functions by decentralizing them within the data plane of SD-MANET, utilizing the geographic location information of nodes to enhance routing efficiency. The controller is primarily responsible for providing location services and facilitating partial centralized decision-making. Within the data plane, nodes employ an enhanced distance and angle-based greedy forwarding algorithm, denoted as GPSR_DA, to efficiently forward data. Additionally, to address the issue of routing voids in the data plane, we employ the A* algorithm to compute an optimal routing path that circumvents such voids. Finally, we conducted a comparative analysis with several state-of-the-art approaches. The evaluation experiments demonstrate that SD-GPSR significantly reduces the control overhead of the network. Simultaneously, there is a notable improvement in both end-to-end latency and packet loss rate across the network.
Keywords: Software-Defined Networking (SDN); routing computation; Mobile Ad-Hoc Networks (MANET); A* algorithm (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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