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Bee-gent: Bonding and Encapsulation Enhancement Agent

Framework for Development of Distributed Systems

Takahiro Kawamura, Yasuyuki Tahara, Tetsuo Hasegawa, Akihiko Ohsuga, and Shinichi Honiden

Corporate R&D Center, Toshiba Corp., Saiwai, Kawasaki, Japan 210-8501

SUMMARY

With the recent fast expansion of networks, intercon-

nection of heterogeneous systems via networks is drawing

increasing attention. In this context, the authors propose the

Bee-gent (Bonding and Encapsulation Enhancement

aGENT) agent framework, whose objective is to allow

flexible interconnection between legacy systems, data-

bases, and other existing systems by providing coordination

and communication functions for distributed system com-

ponents. With the proposed network, interaction protocols

describing interactions between system components are

divided between global processing related to problem solv-

ing, and component-specific local processing. Coordina-

tion between system components in the global processing

is ensured through consistent control by mobile mediation

agents. This facilitates design and maintenance if the sys-

tem is modified or extended. In the paper the practical

implementation of the proposed system is discussed and

specific practical examples are presented to demonstrate the

Comp Jpn, 31(13): 4256, 2000

Key words: Distributed system; adjustment; com-

munication; mobile agent.

1. Introduction

With recent developments in high-speed network

infrastructure and trends toward open-oriented software,

the demand for interconnectivity between network applica-

tions is increasing [1]. In particular, there is strong interest

in the design and operation of distributed systems that

support the utilization and linking with older special-pur-

pose software (often called legacy systems) or existing

databases. CALS and corporate electronic commerce may

be mentioned as typical fields. Numerous standards (e.g.,

SGML, STEP) are available to implement data exchange

between systems via networks.

However, to ensure consistent operation of a distrib-

uted system, more than knowledge sharing based on data

exchange is required: an important further issue is how to

coordinate interaction between the systems involved. All

the advantages of a distributed system will be reduced by

half unless there is a coordination function to solve this

problem. Unfortunately, few development tools are avail-

able to build distributed systems supporting such coordina-

tion functions. Recently, distributed-object systems that

treat structural components as objects, and multiagent sys-

tems that employ multiple agents for coordination, have

been extensively developed. However, most tools used for

such development are focused mainly on communications

between structural components while providing little or no

support for coordination functions. A framework is required

that would not only ensure communications but also pro-

vide coordination.

In this context, we propose an agent framework,

Bee-gent (Bonding and Encapsulation Enhancement

aGENT) [2], which provides coordination between struc-

tural components of a distributed system for the purpose of

flexible linkage between legacy systems, package software,

and other existing systems. With the proposed framework,

Systems and Computers in Japan, Vol. 31, No. 13, 2000

Translated from Denshi Joho Tsushin Gakkai Ronbunshi, Vol. J82-D-I, No. 9, September 1999, pp. 11651180

coordination between structural components is imple-

mented via multiple mobile agents rather than by linking

individual components to each other. Other related ap-

proaches are discussed in Section 2, and Section 3 explains

the configuration and features of the proposed system. In

Section 4, the practical implementation and development

examples are discussed. Section 5 discusses possible appli-

cations of the proposed system.

2. Approaches to the Development of

Distributed Systems

Recently, the mainstream in distributed architectures

has been shifting from the previous client-server model

toward the distributed-object model, which offers more

flexibility. However, the distributed-object model normally

requires mutual understanding between the systems to be

connected as well as precise interface specifications. For

example, preliminary knowledge about an object (e.g.,

method name, argument) is required for remote access to

the object. In addition, object descriptions for cooperative

processing of multiple objects are not supported, which

means that the developer has to incorporate cooperative

logic of this kind into each individual object.

On the other hand, in research related to multiagent

models, components of a distributed system are treated as

agents, and some models have been proposed to implement

cooperative processing among multiple objects.

Typical models of this sort include KQML facilitator

and federation architecture [35]. In this model, however,

the emphasis is placed on message routing when multiple

agents interact through exchange of KQML messages: no

support is provided for direct coordination to promote

problem solving by individual agents based on sent or

received messages.

COOL [6], JAFMAS [7], and AgenTalk [8] are ex-

amples of agent development tools that offer more direct

coordination. These systems offer general methodologies

for the development of Speech-Act-based [9] multiagent

systems while supporting the description of interaction

protocols (IP, explained in detail in Section 4), which ex-

plicitly represents the interdependencies between KQML

messages. With these tools, however, it is extremely diffi-

cult to produce IPs because they must be tailored to indi-

vidual agents without loss of compatibility. Therefore, an

addition or correction to a problem-solving algorithm

would require a complicated iterative procedure to modify

the overall interaction between agents while avoiding con-

flicts with individual IPs. Such a procedure becomes im-

practicable if there are many agents or complicated

problem-solving algorithms. Besides, it is not an easy task

to verify the total compatibility of individual IPs. In this

context, we propose the agent framework Bee-gent [2],

which provides coordination between structural compo-

nents of a distributed system via mobile agents rather than

introducing complicated IPs into the individual compo-

nents. In the proposed architecture, global IP processing

related to problem solving is separated from local process-

ing related to individual components, and the global proc-

essing is subject to centralized control by mediation agents.

Such an approach facilitates IP development while support-

ing coordination between components, which is indispen-

sable in building an efficient distributed system.

3. Bee-gent Agent Framework

3.1. System configuration

The basic concept of the proposed system is shown

in Fig. 1. The system consists of distributed components

such as applications and databases, agent wrappers [10]

(below referred to as wrappers) that connect these elements

via a network, and mediation agents that realize cooperative

processing between components via wrappers.

A mediation agent supports coordination functions

(assurance of consistent operation of the whole system),

communication functions (communication with wrappers),

and migration functions (movement between wrappers via

Fig. 1. System concept.

the network). A variety of functions of agent wrappers are

supported, such as communications with mediation agents

and use of the native interfaces of connected applications

(e.g., SQL queries for databases or http-access for Web

servers), as shown in Fig. 2.

Migration functions provide for the travel of a media-

tion agent among wrappers. A wrapper may also be consid-

ered as a platform that allows operationsimultaneous or

exclusiveof multiple mediation agents. Coordination

functions are implemented by means of mediation agents

acting through their IPs, which will be explained in more

detail later. Communication functions provide message

exchange between mediation agents and wrappers, which

will be described later as well.

The implementation of the system will be explained

in Section 4. Below we describe simple functional links

between mediation agents, wrappers, and connected appli-

cations.

(1) Application A issues an event to connected wrap-

per A using its native interface.

(2) Wrapper A receives the event (if necessary) and

sends a message to the mediation agent by means of the

communication function.

(3) The mediation agent receives the message by

means of the communication function and takes an appro-

priate action in accordance with the IP (in our case, migra-

tion to wrapper B).

(4) Using the migration function, the mediation agent

goes to wrapper B and takes the next action in accordance

with the IP (in our case, sending a message to wrapper B).

(5) The mediation agent sends a message to wrapper

B by means of the communication function.

(6) Wrapper B receives the message by means of the

communication function and (if necessary) accesses appli-

cation B via its native interface.

3.2. Coordination functions

The mediation agent supports coordination functions

to ensure cooperative problem solving among the compo-

nents of the distributed system. The coordination functions

provide interdependence of Speech-Act-based messages

exchanged between wrappers and mediation agents, and are

explicitly defined by the IP.

3.2.1. Interaction protocols

In essence, IPs are based on the organizational theory

of Fox and colleagues [11, 12]. This approach considers, at

the structural level, the problems of coordination between

different subjects, and presupposes a priori knowledge

about interactive processes between such subjects, which

may be considered as a top-down approach. The IP repre-

sents such interactive processes as a dialog between sub-

jects using the rules of Speech-Act-based message

exchange. The IP may also be thought of as a plan that

allows each subject to achieve its own goals while interact-

ing with other subjects. In many cases, this is represented

as a finite state machine, including possible states for a

subject, actions, and transitions to next states. Subject

autonomy appears as a choice between possible states for

transition. Some studies consider dynamic modification of

state transitions during IP run-time [13].

An example of an IP modeled as a state transition

diagram is shown in Fig. 3. In the diagram, the IP performs

requests from one subject to another; in the process, re-

peated message exchanges take place, obtaining the results

(inform Done or failure). The rectangles correspond to

states of the subject that are possible during IP execution,

namely, from top to bottom, precondition, action, and state

transition rule. If a precondition is matched, then the action

included in the states is called. The action (also referred to

as an action function, etc.) determines the subjects opera-

Fig. 2. Mediation agent and agent wrappers.

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