• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.545-549
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• 2007

The Bio-Inspired System focuses on the creation of an effective system model for massive network applications and is being widely developed. However, the system has a problem-difficulty implementing three features in the system, which includes scalability, adaptability and survivability. To solve this problem, we designed an Ecogent as a multiple intelligence agent, and a Bio-platform to address the three features of scalability, adaptability and survivability. The Bio-Inspired System Platform consists of an ERS (Ecogent Runtime Services) Platform and a Bio-Platform. The ERS platform serves the basic functions of mobile agents, such as Registration, Life Cycle, Migration, Communication, Location and Fault Tolerance. The Bio-Platform includes the functions of Evolution Control and Stigmergy Control to address evolution and adaptation.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.9
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• pp.416-424
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• 2007

The Bio-Inspired system is a computing model that emulates the objects in ecosystem which are evolving themselves and cooperate each other to perform some tasks. Since it could be used to solved the complex problems that have been very difficult to resolve with previous algorithms, there have been a lot of researches to develop an application based on the Bio-Inspired system. However, since this computing model requires the process of evolving and cooperating with a lot of objects and this process takes a lot of times, it has been very hard to develop an application based on this computing model. This paper presents a parallel simulator for a Bio-Inspired system that is designed and implemented with OMNeT++ on PC clusters, and proves its usefulness by showing its simulation performance for a couple of applications. In the proposed parallel simulator, the functions required in the ERS platform for evolving and cooperating between objects (called Ecogent) are mapped onto the functions of OMNeT++, and they are simulated on PC clusters simultaneously to reduce the total simulation time. The simulation results could be monitored with a GUI In realtime, and they are also recorded into DBMS for systematic analyses afterward. This paper shows the usefulness of the proposed system by analyzing its performances for simulating various applications based on Bio-Inspired system on PC clusters with 4 PCs.