Emergent Robustness in Software Systems through Decentralized Adaptation: an Ecologically-Inspired ALife Approach

The ecosystem of web applications faces a critical paradox: on one hand, the Internet is a constantly evolving and unpredictable computing platform, on the other hand, the software services that run on top of it hardly have the ability to adapt to the evolution of this platform. Among the software services, we distinguish between service providers that provide micro services and service consumers that aggregate several micro services to deliver macro services to customers. Providers and consumers must handle uncertainty: providers cannot know in advance what consumers need; consumers rely on third-parties that can disappear at any time. Our proposal analogizes the software consumer / provider network to a bipartite ecological graph. This analogy provides the foundations for the design of EVOSERV, an individual-based ALife simulator used to experiment with decentralized adaptation strategies for providers and consumers. The initial model of a software network is tuned according to observations gathered from real-world software networks. The key insights about our experiments are that, 1) we can successfully model software systems as an ALife system, and 2) we succeed in emerging a global property from local decisions: when consumers and providers adapt with local decision strategies, the global robustness of the network increases. We show that these results hold with different initial situations, different scales and different topological constraints on the network.