{"title":"Biology of Applied Digital Ecosystems","authors":"G. Briscoe, S. Sadedin, G. Paperin","doi":"10.1109/DEST.2007.372015","DOIUrl":null,"url":null,"abstract":"A primary motivation for research in digital ecosystems is the desire to exploit the self-organising properties of natural ecosystems. Ecosystems are thought to be robust, scalable architectures that can automatically solve complex, dynamic problems. However, the biological processes that contribute to these properties have not been made explicit in digital ecosystem research. Here, we discuss how biological properties contribute to the self-organising features of natural ecosystems. These properties include populations of evolving agents, a complex dynamic environment, and spatial distributions which generate local interactions. The potential for exploiting these properties in artificial systems is then considered. An example architecture, the digital business ecosystem (DBE), is considered in detail. Simulation results imply that the DBE performs better at large scales than a comparable service-oriented architecture. These results suggest that incorporating ideas from theoretical ecology can contribute to useful self-organising properties in digital ecosystems.","PeriodicalId":448012,"journal":{"name":"2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"41","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEST.2007.372015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 41
Abstract
A primary motivation for research in digital ecosystems is the desire to exploit the self-organising properties of natural ecosystems. Ecosystems are thought to be robust, scalable architectures that can automatically solve complex, dynamic problems. However, the biological processes that contribute to these properties have not been made explicit in digital ecosystem research. Here, we discuss how biological properties contribute to the self-organising features of natural ecosystems. These properties include populations of evolving agents, a complex dynamic environment, and spatial distributions which generate local interactions. The potential for exploiting these properties in artificial systems is then considered. An example architecture, the digital business ecosystem (DBE), is considered in detail. Simulation results imply that the DBE performs better at large scales than a comparable service-oriented architecture. These results suggest that incorporating ideas from theoretical ecology can contribute to useful self-organising properties in digital ecosystems.