·182· 智能系统学报 第3卷 ices for mo bile agents came form two considera- programming context and a closely coupled system tions.First,the agents possess local knowledge of provides database query interface as a subset or an the network and have a limited functionality,since extension of the language for featuring dynamic only agents of limited size and complexity can effi- query formulation and view access.For example, ciently migrate in a network and have little over- SWFProlog and KB-Prolog!belong to the first head.Hence specific services are required which and CGWI and Quintus!fall into the second aim at deploying mobile agents efficiently in system category. and network management.Secondly,mobile a- In this paper we present the design and imple- gents are subject to strong security restrictions, mentation of a mobile agent system,which couples which are enforced by the system security mecha-a logic language based application programming in- nism.Thus,mobile agents should find services terface for DDM.Two important system modules, that help to complete security-critical tasks,other namely,service discovery and database access, than execute code,which might jeopardize remote have been encapsulated and installed inside of the servers.Following this trend,it becomes increas existing IMAGO (intelligent mobile Agent gliding ingly important to give agents the ability of finding omline)system.The IMAGO system is an infra- and making use of data services that are available structure for mobile agent applications.It includes in a network A variety of Service Discovery code for the IMAGO servera Multi-threading Log- Protocols (SDPs)are currently under development ic Virtual Machine,the IMA GO-Prologa Prolog by some companies and research groups.The most like programming language extended with a rich well known schemes are Sun's Java based API for implementing mobile agent and DDM ap- Jini TM!41,Salutation!51,Microsoft's UPPls1, plications,and the IMA GO IDE,a Java-GUI based IETFs draft Service Location Protocoll7 and OA- program from which users can do editing,compi- SIS UDDIs).Some of these SDPs are extended andI ling,and invoking an agent application.The re- applied by several mobile agent systems to solve mainder of the paper is organized as follows.Sec- the service discovery problem. tion 2 gives an overview of the design of service In a DDM environment,data may be stored a- discovery module and integration with the IMA GO mong physically distributed sites and may be artifi-system.In Section 3,we discuss definitions of the cially partitioned among different sites for better database predicates and the principle of data driven scalability.Therefore endowing mobile agents implementation.In Section 4,we present a simple with the ability of accessing remote databases is database access example and briefly explain how to the basis for DDM applications.This encourages use database interface presented by the IMA GO us to explore the strategies of coupling a mobile a- system.Finally,we give the concluding remarks gent programming language with database access as well as future work. facilities.In recent years numerous approaches have been made under the topic of designing a cou- 1 Data service discovery pled system that integrates a relational database The general idea of distributed data services is and a logic programming language.They all enable that a DDM application may be separated from the programmers to access large amounts of shared da- data sites needed to fulfill a task.These data sites ta for knowledge processing,manage data effi-are mostly modeled by local and centralized data- ciently as well as process data intelligently.Gener- bases,which are independent of,or sometimes un- ally speaking,coupling a logic programming lan- known to the application.A commonly used DDM guage with database access facility can be roughly approach is to apply traditional data mining algo- divided into two categories.A loosely coupled sys rithms to an aggregation of data retrieved from tem embeds a nom-logic language,such as the physically distributed data sources.However,this structure query language (SQL),within the logic- approach may be impractical to a large scale of data 1994-2009 China Academic Journal Electronic Publishing House.All rights reserved.http://www.cnki.netices for mobile agents came form two considera2 tions. First , t he agents possess local knowledge of t he network and have a limited f unctionality , since only agents of limited size and complexity can effi2 ciently migrate in a network and have little over2 head. Hence specific services are required which aim at deploying mobile agents efficiently in system and network management. Secondly , mobile a2 gents are subject to strong security restrictions , which are enforced by t he system security mecha2 nism. Thus , mobile agents should find services t hat help to complete security2critical tasks , ot her t han execute code , which might jeopardize remote servers. Following this trend , it becomes increas2 ingly important to give agents the ability of finding and making use of data services that are available in a network [3 ] . A variety of Service Discovery Protocols (SDPs) are currently under development by some companies and research group s. The most well known schemes are Sun ’ s J ava based Jini TM [4 ] , Salutation [5 ] , Microsoft ’ s U PP [6 ] , IETF’s draft Service Location Protocol [7 ] and OA2 SIS UDDI [8 ] . Some of these SDPs are extended and applied by several mobile agent systems to solve t he service discovery problem. In a DDM environment , data may be stored a2 mong p hysically distributed sites and may be artifi2 cially partitioned among different sites for better scalability. Therefore endowing mobile agents with t he ability of accessing remote databases is t he basis for DDM applications. This encourages us to explore the strategies of coupling a mobile a2 gent programming language with database access facilities. In recent years numerous app roaches have been made under t he topic of designing a cou2 pled system t hat integrates a relational database and a logic programming language. They all enable programmers to access large amounts of shared da2 ta for knowledge processing , manage data effi2 ciently as well as process data intelligently. Gener2 ally speaking , coupling a logic programming lan2 guage with database access facility can be roughly divided into two categories. A loosely coupled sys2 tem embeds a non2logic language , such as the struct ure query language (SQL) , wit hin t he logic2 programming context and a closely coupled system provides database query interface as a subset or an extension of t he language for feat uring dynamic query formulation and view access. For example , SWI2Prolog and KB2Prolog [9 ] belong to t he first and CGW [10 ] and Quintus [11 ] fall into the second category. In this paper we present t he design and imple2 mentation of a mobile agent system , which couples a logic language based application programming in2 terface for DDM. Two important system modules , namely , service discovery and database access , have been encap sulated and installed inside of t he existing IMA GO (intelligent mobile Agent gliding on2line) system. The IMA GO system is an infra2 struct ure for mobile agent applications. It includes code for t he IMA GO server2a Multi2t hreading Log2 ic Virt ual Machine , t he IMA GO2Prolog2a Prolog2 like programming language extended with a rich API for implementing mobile agent and DDM ap2 plications , and t he IMA GO IDE , a J ava2GU I based program from which users can do editing , compi2 ling , and invoking an agent application. The re2 mainder of t he paper is organized as follows. Sec2 tion 2 gives an overview of t he design of service discovery module and integration wit h t he IMA GO system. In Section 3 , we discuss definitions of t he database p redicates and the principle of data driven implementation. In Section 4 , we present a simple database access example and briefly explain how to use database interface presented by t he IMA GO system. Finally , we give the concluding remarks as well as f uture work. 1 Data service discovery The general idea of distributed data services is t hat a DDM application may be separated from t he data sites needed to f ulfill a task. These data sites are mostly modeled by local and centralized data2 bases , which are independent of , or sometimes un2 known to t he application. A commonly used DDM approach is to apply traditional data mining algo2 rit hms to an aggregation of data retrieved from p hysically distributed data sources. However , this approach may be impractical to a large scale of data ·182 · 智 能 系 统 学 报 第 3 卷