Abstract
We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures (EOA) where the word ecosystem is more than just a metaphor.
Original language | English |
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Pages (from-to) | 1143-1194 |
Number of pages | 52 |
Journal | Natural Computing |
Volume | 10 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Sept 2011 |
Keywords
- Ecosystem
- Architecture
- Distributed
- Evolution
- Agents
- WEB SERVICES
- EVOLUTIONARY ALGORITHMS
- MANAGEMENT
- COMMUNITIES
- TECHNOLOGY
- COMPLEXITY
- NETWORKS
- ECOLOGY
- SYSTEMS
- SEARCH