Kaizar Amin » Mobile Agents

Dynamic agent population in agent-based distance vector routing

kaizar — Thu, 30 Oct 2008 12:02:31 +0000

Title:

Dynamic agent population in agent-based distance vector routing, Kaizar Amin, Armin Mikler, Prasanna Iyengar. Neural, Parallel & Scientific Computations, special issue on Advances in intelligent systems and applications, Volume 11 , Issue 1 & 2 (March 2003) Pages: 127 – 142 . (pdf)

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 the size of its agent population. Although a significant amount of research has been conducted on mobile agent-based systems, little consideration has been given to the importance of dynamically and autonomously adapting the size of the agent population as function of circumstances in the environment. A large number of constituent agents can consume considerable amounts of network resources, thereby impeding the overall performance of the network. Hence, it is imperative to have a control mechanism whereby the agent population can be adjusted in a distributed manner to balance the resource overhead in the network. This paper briefly discusses an agent-based approach to Distance Vector Routing, referred as Agent-based Distance Vector Routing. It also describes a framework for an adaptive approach to control the number of agents in the network using pheromones and discusses its limitations.

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Agent-based Distance Vector Routing: A Resource Efficient and Scalable approach to Routing

kaizar — Thu, 30 Oct 2008 11:55:23 +0000

Title:

Agent-based Distance Vector Routing: A Resource Efficient and Scalable approach to Routing. Kaizar Amin and Armin Mikler. Journal of Systems and Software, 71(3): 215-227 (2004). (pdf)

Abstract:

In spite of the ever-increasing availability of computation and communication resources in modern networks, the overhead associated with network management protocols, such as traffic control and routing, continues to be an important aspect in the design of new methodologies. Resource efficiency of such protocols has become even more prominent with the recent developments of wireless and ad hoc networks, which are marked by much more severe resource constraints in terms of bandwidth, memory, and computational capabilities. This paper presents an agent-based approach to distance vector routing (ADVR) that addresses these resource constraints. ADVR is a resource efficient implementation of distance vector routing that is fault tolerant and scales well for large networks. ADVR draws upon some basic biologically inspired principles to facilitate coordination among the mobile agents that implement the routing task. Specifically, simulated pheromones are used to control the movement of agents within the network and to dynamically adjust the number of agents in the population. The behavior of ADVR is analyzed and compared to that of traditional distance vector routing.

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Agent-Based Distance Vector Routing

kaizar — Thu, 30 Oct 2008 09:31:35 +0000

Title:

Agent-Based Distance Vector Routing. Kaizar A. Amin, John T. Mayes, and Armin R. Mikler. Mobile Agents for Telecommunication Applications, Third International Workshop, MATA 2001, Montreal, Canada, August 14-16, 2001. (pdf)

Abstract:

Mobile Agents are being proposed for an increasing variety of applications. Distance Vector Routing (DVR) is an example of one application that can benefit from an agent-based approach. DVR algorithms, such as RIP, have been shown to cause considerable network resource overhead due to the large number of messages generated at each host/router throughout the route update process. Many of these messages are wasteful since they do not contribute to the route discovery process. However, in an agent-based solution, the number of messages is bounded by the number of agents in the system. In this paper, we present an agent-based solution to DVR. In addition, we will describe agent migration strategies that improve the performance of the route discovery process, namely Random Walk and Structured Walk.

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