The UNT College of Engineering strives to educate and train engineers and technologists who have the vision to recognize and solve the problems of society. The college comprises six degree-granting departments of instruction and research.
This paper discusses dynamic agent population in agent-based distance vector routing.
Physical Description
6 p.
Notes
Abstract: The Intelligent mobile agent paradigm can be applied to a wide variety of intrinsically parallel and distributed applications. Network routing is one such application that can be mapped to an agent-based approach. The performance of any agent-based system will depend on its agent population. Although a lot of research has been conducted on agent-based systems, little consideration has been given to the importance of agent population in dynamic networks. A large number of constituent agents can increase the resource overhead of the system, thereby impeding the overall performance of the network. Hence, it is imperative to find the optimal number of agents in the system that would maximize the efficiency of the agent-based mechanism in the network. This optimal value cannot be determined manually, thereby emphasizing the need for an adaptive approach that manipulates the number of agents in the system based on its resource availability. This paper discusses an agent-based approach to Distance Vector Routing, referred as Agent-based Distance Vector Routing and also describes an adaptive approach controlling the number of agents in the network using pheromones and discusses their limitations.
This paper is part of the following collection of related materials.
UNT Scholarly Works
Materials from the UNT community's research, creative, and scholarly activities and UNT's Open Access Repository. Access to some items in this collection may be restricted.
