A Peer-to-Peer System Architecture for Multi-Agent Collaboration

A Peer-to-Peer System Architecture

for Multi-Agent Collaboration

Prithviraj Dasgupta

Computer Science Department

University of Nebraska, Omaha, NE 68182

E-mail: pdasgupta@

Phone: (402) 554 4966 Fax: (402) 554 3284

Abstract

A peer-to-peer(P2P) network comprises a collection of nodes that can cooperate and collaborate with each other in a de-centralized and distributed manner. A node in a P2P network can access information present in the network using peer discovery followed by a search and retrieval phase. At present, most P2P systems employ message communication to implement the operations in a P2P network. In this paper, we propose the use of mobile software agents to implement the protocols in a P2P system. Mobile software agents are autonomous, economic in terms of size and bandwidth consumption, and can operate remotely without the continuous supervision of a central server. Our research indicates that mobile software agents provide a suitable paradigm for implementing P2P systems that is both scalable and robust.

1. Introduction

An agent is a software entity that can operate autonomously without continuous supervision by a central authority. Intelligent software agents can also learn from their environment, react to changes in the environment and take decisions based on their beliefs. Software agents have been applied to different problem domains [Weiss99] including solving complex mathematical problems, assisting humans in complex medical surgeries, computer network management, distributed databases and data mining, and financial decision support systems. With the rapid growth of the Internet over the past decade, software agents called bots are being used extensively to aid online users with different tasks including intelligent Web searches, comparing prices of items from different online shops, and customizing Web sites according to user preferences. However, most of these Internet bots perform their tasks individually and possibly independently of each other. Most of the information that is available online is duplicated across many sites. For example, an Internet search for the value of U. S. stock indices yields more than a hundred Web sites containing an hourly report of the values of the stock indices. Due to this vast redundancy in online information, it is quite likely that many of the Internet bots gather and analyze information that has already been collected and, perhaps analyzed as well previously by another bot. Therefore, we envisage that a significant performance improvement can be obtained in agent enabled online processing if Internet agents can share information, analysis of that information and even computational load with one another.