Document Type : Original Article
Authors
1
PhD student Department of Computer and Information Technology, Faculty of Electrical, Computer and Medical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran
2
Assistant Professor, Computer Engineering, Faculty of Engineering, Islamic Azad University, Tabriz, Iran
3
Assistant Professor, Department of Computer and Information Technology, Qazvin Branch, Islamic Azad University, Qazvin, Iran
4
Associate Professor, Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran
Abstract
Wireless multi-hop networks are networks in which communications are not constant, and packets delivery occurs hop-by-hop through a group of relay nodes. One of the primary challenges in these networks is routing and ensuring cooperation among relay nodes over long distances with short transmission range. Previous methods have tackled routing issues by utilizing cooperative nodes. Most of these methods consider cooperative nodes either as a group for the entire network or determine them for each source node based on specific characteristics, Such as node neighborhood or movement history, etc. However, due to the dynamic nature of wireless multi-hop networks and intermittent communications, issues such as high delay and low packet delivery ratio remain, which reduce network performance. This paper proposes a method in which a group of nodes is selected as cooperative nodes relative to a specific destination node. In the proposed method, a genetic algorithm is used to determine the cooperative nodes for each destination node. In the first step, a bargaining game is employed to generate the initial population. Then, a group of nodes is selected as cooperative nodes using the genetic algorithm, and routing is performed based on these nodes. Simulation results and comparison with previous methods indicate that the proposed method improves performance by reducing average delay by approximately 15%, increasing the packet delivery ratio by around 16%, and reducing network overhead by about 12%.
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