2nd International ICST Conference on Communications and Networking in China

Research Article

MARP: A Multi-Agent Routing Protocol for Ad-hoc Network

  • @INPROCEEDINGS{10.1109/CHINACOM.2007.4469371,
        author={Mohammad Taghi Kheirabadi and Hossein Mohammadi},
        title={MARP: A Multi-Agent Routing Protocol for Ad-hoc Network},
        proceedings={2nd International ICST Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2008},
        month={3},
        keywords={Mobile Ad-hoc Networks Routing and Distributed Artificial Intelligence},
        doi={10.1109/CHINACOM.2007.4469371}
    }
    
  • Mohammad Taghi Kheirabadi
    Hossein Mohammadi
    Year: 2008
    MARP: A Multi-Agent Routing Protocol for Ad-hoc Network
    CHINACOM
    IEEE
    DOI: 10.1109/CHINACOM.2007.4469371
Mohammad Taghi Kheirabadi1,*, Hossein Mohammadi2,*
  • 1: Islamic Azad University, Gorgan Branch
  • 2: Islamic Azad University Azadshahr Branch
*Contact email: mtkheirabadi@hotmail.com, Hussein_moh2005@yahoo.com

Abstract

Mobile Ad-hoc Networks are networks that have a dynamic topology without any fixed infrastructure. To transmit information in ad-hoc networks, we need robust protocols that can cope with constant changes in the network topology. The known routing protocols for mobile ad-hoc networks can be classified in two major categories: proactive routing protocols and reactive routing protocols. Proactive routing protocols keep the routes up-to-date to reduce delay in real-time applications but they have high control overhead. The control overhead in reactive routing protocols is much less than proactive routing protocols; however, the routes are discovered on demand, which is not suitable for real-time applications. In this paper, we have introduced a new routing system for mobile ad-hoc networks called MARP, which is based on the concepts of Distributed Artificial Intelligence (DAI). In MARP, every node acts as an independent and autonomous agent that collaborates with other agents in the system. Our experimental results have verified the efficiency and robustness of MARP under dynamic conditions of ad-hoc networks