Distributed Multi-agent System Architecture for Mobile Traders

Ananta Charan Ojha School of IT,

ICFAI University, Hyderabad, INDIA

acojha2002@yahoo.co.in

Sateesh Kumar Pradhan Dept. of Computer Science,

Utkal University, Bhubaneswar, INDIA

sateeshind@yahoo.com

Manas Ranjan Patra Dept. of Computer Science,

Berhampur University, Berhampur, INDIA

manasrpbu@yahoo.com

Abstract

Multi-agent system has been recognized as the most promising technology for e-commerce due to its ability to deal with complexity through partitioning and cooperation. Software agents acting on behalf of human traders help automate several business processes that are time-consuming and difficult in e- commerce. They move from marketplace to marketplace on the Internet and display on-demand behaviour based on market dynamics. In this paper, we present a multi-agent system architecture for mobile traders and claim that it improves their mobility, intelligence and capability in agent-based e-commerce. Keywords: Architecture, Mobile Agent, Agent-based E-Commerce, Multi-agent System

1. Introduction

The Internet and web technologies facilitate development of efficient e-commerce solutions that are cost-effective and less time-consuming for global business. Electronic marketplaces on the Internet are mushrooming. Popular sites such as eBay, Yahoo and Amazon deal with a large number of goods and services for buying and selling. Millions of users perform varieties of transactions on the Internet daily. However, these transactions involve large amount of human interactions through web interfaces. Although some sites provide automation and monitoring tools like proxy bidding agents [1] and shopbots [2], their capability is limited and they still require human involvement substantially. Of late, multi-agent system has been recognized as the most promising technology to offer next-generation e-commerce applications. It deals with complexity through partitioning and cooperation [3]. Software agents acting on behalf of human buyers, sellers and other market entities help automate several business processes such as product and merchant brokering, negotiation, payment

and delivery etc. that are time-consuming and difficult in e-commerce [4].

Several research efforts have been made towards agent-based e-commerce and found in literature [5, 6, 7, 8, 9, 10]. Most of them use predefined and non-adaptive behaviours for negotiation. Although mobile agents are very attractive for the Internet applications they are separately considered from intelligent agents that are stationary in most of the agent-based e-commerce applications. However, in real life commerce activities human traders often move from market to market, negotiate on multiple issues, have fuzzy preferences and use intelligent behaviours that are adaptive based on market dynamics. Thus, a trader in a true agent-based e-commerce system should be adequately intelligent, adaptive and mobile to carry out successful e-commerce transactions.

Recent advances in multi-agent technology, computational intelligence, agent development tools [11] and agent-oriented software engineering approaches [12] motivate the research community to develop and realize real-world models of e-commerce. Software architecture plays a crucial role in engineering complex system. It models the organizational structure and associated behaviour of a system at the highest level of abstraction. It highlights early design decisions that have profound impact on the overall success of the software system. Further, it enables effective communication among stakeholders in a software development project. A detail discussion on software architecture can be found in [13].

We present a multi-agent system architecture for real-world mobile traders using both stationary and mobile agents. The architecture for such traders consists of a stationary agent that provides intelligent behaviour support to a mobile agent when the latter demands it. The mobile agent moves from marketplace to marketplace and takes advantage of these on-demand behaviours to carry out successful e-commerce transactions to fulfill the

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assigned goals. The architecture improves mobility, intelligence and capability of the trading agent.

Next, section 2 describes the proposed architecture. We brief on the implementation in section 3. Then the paper concludes. 2. Architecture

In our agent-based e-commerce system, a trading agent representing a human trader (either a buyer or a seller) originates from a trader subsystem and moves from marketplace to marketplace on the Internet. It needs to carry out successful interactions with other agents in these marketplaces with different market mechanisms. We identify some of the desirable characteristics of this mobile trading agent as follows:

i. Efficient Mobility: A mobile trading agent should be lightweight and able to move across the network hosts freely not being affected by low bandwidth of the network connections.

ii. Market Adaptability: A mobile trading agent should posses the ability to deal with different market mechanisms, which may not be known in advance to the agent. It should display its behaviours dynamically.

iii. Improved Intelligence: A mobile trading agent should have enough knowledge and intelligence to reason about the past and present e-commerce deals autonomously and efficiently.

iv. Persistence: Once a mobile trading agent is dispatched to a marketplace it should not stay connected to the originating trader subsystem. The agent should persist even if the subsystem is disconnected from the Internet.

v. Flexible Role: A mobile trading agent should have greater flexibility in terms of peer-to-peer communication. It can play a buyer role or a seller role whichever is most appropriate to it at the current location at a particular time.

To realize the above characteristics, we propose a

multi-agent architecture for the mobile trading agent. The architectural style is distributed and decouples the behaviour modules from the mobile agent. The architecture for the trading agent is illustrated in Figure 1. The trading agent consists of the following components:

i. Trader Interface: Trader interface is a GUI through which the human trader interacts with the agent to provide his preferences.

ii. Behaviour Database: This component represents the behaviour modules of the trading agent. A behaviour module describes the

reasoning ability of the agent. It encapsulates protocols as well as knowledge for the agent.

iii. Stationary Agent: This Stationary Agent resides at the trader subsystem and receives inputs from the human trader through the trader interface. The Stationary Agent creates the Mobile Agent and informs it to travel to the desired marketplace. When the Stationary Agent receives request from the Mobile Agent for a specific behaviour it then locates that behaviour on the trader subsystem and sends it to the Mobile Agent in an ACL (Agent Communication Language) message.

iv. Mobile Agent: The Mobile Agent moves to different marketplaces as instructed and may follow an itinerary. After reaching the marketplace it interacts with the market agents such as the Registrar and the Matchmaker to know about the market mechanisms (see [14] for details). Then it requests the Stationary Agent to send the required behaviour. On receiving the behaviour, the Mobile Agent loads it dynamically and participates in e-commerce negotiation.

Figure 1: Trading Agent Architecture

3. Implementation

We have implemented the architecture in an e-marketplace prototype that simulates simple auction mechanisms and evaluated it to find its relative performance in terms of agent mobility. The simulation was repeated for 10 times during different traffic conditions and the mean migration time (MMT) of the agent was computed with respect to its file size (FS). Table 1 shows that the mobility time is less in case of agents implementing the architecture.

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Table 1: Mobility Performance

Buyer Agent Seller Agent

Agents MMT (ms)

FS (kb)

MMT (ms)

FS (kb)

Monolithic 7.26 6.15 9.76 8.24

Architecture 5.31 4.19 5.31 4.19

In this architecture, the trading agent is modeled as a multi-agent system instead of a single agent. The approach makes the trading agent lightweight, intelligent and adaptive to market conditions. It reduces the complexity of the trading agent through partitioning and cooperation. The mobile trading agent that moves on the Internet is decoupled from the behaviour modules. This decoupling ensures the agent to be lightweight and travel freely on the Internet without being affected by bad network conditions such as heavy traffic and low bandwidth. The decoupling also enhances scaling of agent intelligence and capability to any possible extent by simply adding behaviour modules to the trader subsystem. Since the Stationary Agent when requested sends behaviour modules and the Mobile Agent loads them dynamically, it facilitates adaptable and on-demand behaviour of the trading agent based on market mechanisms. Since a buyer role or a seller role depends on the agent behaviour, the decoupling also enables role flexibility. That means, a trading agent can be a buyer or a seller based on the behaviour its loads at a particular point of time. The development tool that provides mobile agents may support persistence of the trading agent and its ability to perform disconnected operation. We have achieved this using a third party mobility service [15] in our prototype implementation.

However, the architecture introduces communication overheads due to remote interactions as well as human interference (if any). Thus, it increases the overall time taken by a trading agent to complete a business task. Since the Mobile Agent depends on the Stationary Agent for behaviour loading, the computer hosting the trader subsystem must stay connected to the market subsystem until the required behaviour is dispatched successfully.

4. Conclusion

We have proposed a multi-agent system architecture for mobile trading agents and shared our experience in this paper. Our architecture is simple and elegant because the same mobile agent is used as a buyer as well as a seller when required. The mobile agent is also interoperable with different markets based on products, negotiation

protocols and strategies. We claim that the architecture improves mobility, intelligence, capability and usability of the trading agents. Further, we believe that mobile agent-based e-commerce systems will benefit from it.

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