A Review of AI-based MANET Routing Protocols
Fatemeh Safari, Izabela Savić, Herb E. Kunze, Jason B. Ernst, Daniel J. Gillis
University of Guelph
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摘要与影响
Developing scalable and robust routing protocols for Mobile ad hoc Networks (MANETs) can be challenging given issues related to limited energy, node mobility, and changing topology. While a variety of MANET routing protocols are available, they are often hindered by node mobility. Artificial Intelligence (AI) approaches (i.e. biologically inspired and machine learning algorithms) provide a novel approach to MANET routing problems that are better equipped to address these issues. These approaches can improve network performance by minimizing energy consumption, improving overhead, and more. This paper’s main contribution is that it promotes the use of AI to provide high-performance routing protocols. Our work surveys both biologically inspired and machine learning approaches and discusses the contributions made to provide readers with a greater understanding of these approaches and methods that can be taken to improve routing and other performance metrics.
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学术脉络
学科主题
计算机 / AIMobile Ad Hoc Networks
Opportunistic and Delay-Tolerant Networks · Cooperative Communication and Network Coding
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