Agent-based Distance Vector Routing: A Resource Efficient and Scalable approach to Routing in Large Communication Networks Page: 3
The following text was automatically extracted from the image on this page using optical character recognition software:
Although DVR-class algorithms like the distributed Bellman-Ford are sim-
ple to implement, they can suffer from the routing loops and the counting to
infinity problem (Rajagopalan and Faiman 1989). However, there are a wide
range of Distance Vector-based algorithms that eliminate temporary and per-
manent routing loops and avoid the counting to infinity problem altogether
(Rajagopalan and Faiman 1989; Cheng et al. 1989). This paper aims at re-
ducing the message complexity of conventional DVR-class algorithms. It does
not aim at solving the looping problem and counting to infinity associated with
them. Ongoing research focusses on implementing the agent based approach
to certain Loop-Free routing algorithms, thereby making ADVR loop-free, re-
source efficient, and scalable.
The following section summarizes some of the research effort in agent-based
routing during recent years and highlights principle approaches. The design
of Agent-Based Distance Vector Routing (ADVR) is discussed in Section 3.
We will revisit Conjectures 1 and 2 in Sections 4 where we present the experi-
mental analysis of ADVR. Section 5 concludes the paper with a summary and
direction for future work in the area of agent-based network-centric algorithms.
2 Mobile Agents in Routing
Intelligent Mobile Agent is a term that describes the concept of mobile comput-
ing or mobile code (Bradshaw; Fugetta et al. 1998). The appeal of the mobile
agent paradigm is quite alluring - mobile agents roaming the network could
search for or distribute information, meet and interact with other agents or
remain bound to a single host or node. In general, an agent manifests four
distinct characteristics, namely, intelligence, communication, autonomy, and
mobility. Intelligence is the ability of agents to adapt their actions to circum-
stances brought upon by the dynamics of the system (or network). Commu-
nication is the property whereby the agents collaborate or coordinate their
actions by the means of explicit or implicit exchange of information. Auton-
omy allows agents to make decisions and act upon them without the explicit
control of a user. Last but not least, mobility is the property that makes agents
conducive for distributed systems and network applications, as it allows the
agent to migrate among the constituent nodes of the environment.
Most of the work in agent-based network routing is biologically inspired and
based on insect colonies (Di Caro and Dorigo 1997; White 1997). It relies on
the principles that individual insects exhibit a simple behavior while collec-
tive communities of these insects exhibit complex problem solving capabilities.
Considerable research has been conducted in mapping the foraging activi-
ties of ants to routing and network management activities of mobile agents.
Real ants are represented as artificial agents that traverse the network collect-
Here’s what’s next.
This article can be searched. Note: Results may vary based on the legibility of text within the document.
Tools / Downloads
Get a copy of this page or view the extracted text.
Citing and Sharing
Basic information for referencing this web page. We also provide extended guidance on usage rights, references, copying or embedding.
Reference the current page of this Article.
Amin, Kaizar A. & Mikler, Armin R. Agent-based Distance Vector Routing: A Resource Efficient and Scalable approach to Routing in Large Communication Networks, article, March 25, 2002; [New York, New York]. (digital.library.unt.edu/ark:/67531/metadc111275/m1/3/: accessed December 19, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.