TY - GEN
T1 - Simulation of a Self-Optimising Digital Ecosystem
AU - Kurz, T.
AU - Heistracher, T.J.
N1 - Conference code: 70254
Cited By :8
Export Date: 14 December 2023
Correspondence Address: Kurz, T.; ITS Department, , Puch/Salzburg, Austria; email: [email protected]
References: T. Heistracher, T. Kurz, C. Masuch, P. Ferronato, M. Vidal, A. Corallo, P. Dini, and G. Briscoe. Pervasive service architecture for a Digital Business Ecosystem. In Proc. First International Workshop on Coordination and Adaptation Techniques for Software Entities, WCAT04, 71-80, 2004; T. Kurz, G. Marcon, C. Masuch, and T. Heistracher. A network of SMEs for competitive services. In Proc. Managing Global Trends and Challenges in a Turbulent Economy, 2005; T. Heistracher, T. Kurz, G. Marcon and C. Masuch. Collaborative Software Engineering with a Digital Ecosystem. In Proc. International Conference on Global Software Engineering, 2006 (in print); (2005) Semantics of Business Vocabulary and Business Rules (SBVR), draft adopted specification, , OMG; David, H., Adaptive Learning by Genetic Algorithms (1999) Second, Revised and Enlarged, , Edition, Springer, Berlin Heidelberg NewYork; Dijkstra, E.W., A note on two problems in connexion with graphs (1959) Numerische Mathematik, 269-271; Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C., (2001) Introduction to Algorithms, , The MIT Press, Cambridge, Massachusetts, US, second edition; Tobias, R., Hofmann, C., (2003) Evaluation of Free Java-libraries for Social-scientific Agent Based Simulation, Journal of Artificial Societies and Social Simulation, 7 (1). , University of Surrey
PY - 2007
Y1 - 2007
N2 - Small and medium enterprises (SMEs) most often lack resources for custom-made software solutions that support best their core businesses. In this paper a simulation framework for self-optimising SME networks, namely Evolutionary Environment Simulator (EvESimulator), is introduced. The Evolutionary Environment, which the framework bases on, is an infrastructural component for distributed and decentralised service creation and service improvement based on mechanisms that are operating similarly in the living environment. This paper concentrates on the simulation of these mechanisms for SME networks. Built upon the widely-used simulation framework Repast, the cooperation behaviour of companies is investigated that use self-optimizing software services and distribute related information amongst them. The simulator is capable of importing real-world data from real businesses thereby enabling conceptual studies and hypothesis testing. It is applied in the context of three utilisation scenarios that investigate critical mass for sustainability, clustering in general, and usage-based clustering. The first results of the EvESimulator reveal a dynamic creation of a growing network of businesses that is clearly outperforming centralized topologies in the long run. © 2007 IEEE.
AB - Small and medium enterprises (SMEs) most often lack resources for custom-made software solutions that support best their core businesses. In this paper a simulation framework for self-optimising SME networks, namely Evolutionary Environment Simulator (EvESimulator), is introduced. The Evolutionary Environment, which the framework bases on, is an infrastructural component for distributed and decentralised service creation and service improvement based on mechanisms that are operating similarly in the living environment. This paper concentrates on the simulation of these mechanisms for SME networks. Built upon the widely-used simulation framework Repast, the cooperation behaviour of companies is investigated that use self-optimizing software services and distribute related information amongst them. The simulator is capable of importing real-world data from real businesses thereby enabling conceptual studies and hypothesis testing. It is applied in the context of three utilisation scenarios that investigate critical mass for sustainability, clustering in general, and usage-based clustering. The first results of the EvESimulator reveal a dynamic creation of a growing network of businesses that is clearly outperforming centralized topologies in the long run. © 2007 IEEE.
KW - Agent
KW - Digital business ecosystem
KW - Evolutionary environment
KW - Simulation
KW - Administrative data processing
KW - Computer simulation
KW - Distributed computer systems
KW - Enterprise resource management
KW - Evolutionary algorithms
KW - Small and medium enterprises (SME)
KW - Software services
KW - Industrial management
U2 - 10.1109/DEST.2007.371964
DO - 10.1109/DEST.2007.371964
M3 - Conference contribution
SN - 1-4244-0467-3
SP - 165
EP - 170
BT - 2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference, DEST 2007
Y2 - 21 February 2007 through 23 February 2007
ER -
