Issues addressed in the project:
The Bio-Phoenix project aims to revolutionize software system design by leveraging biological processes. The co-DNA approach, it enables the reconstruction of software systems from near-extinct states. Core processes for co-DNA transmission, injection, combination, activation, and deactivation are derived from fundamental biological DNA processes. The project develops a co-DNA specification and verification tool, along with a runtime platform for executing co-DNA. Evaluation focuses on SDN scenarios, assessing performance indicators like computational complexity and security. Bio-Phoenix advances innovative tools for managing complex systems, pushing the boundaries of research and technology.
Importance for Society:
The Bio-Phoenix project holds immense value for the European Community and plays a vital role in enhancing the European Research Area (ERA). By forging interdisciplinary collaborations between experimental biological sciences and engineering, Bio-Phoenix bridges gaps and promotes knowledge exchange. This aligns with the ERA's objective of fostering sustainable multidisciplinary partnerships and reducing research fragmentation. The project's innovative nature lies in its holistic approach to developing models for complex systems on the verge of extinction. By optimizing resilience through self-healing mechanisms, Bio-Phoenix addresses computational and security threats, making it relevant across various domains. This inclusive approach not only strengthens connections among European institutions but also aligns with the goals of the HORIZON 2020 Program, emphasizing multidisciplinary research and translating findings into practical applications in software engineering. Ultimately, Bio-Phoenix's collaborative efforts pave the way for transformative initiatives that enable European society and economy to thrive amidst evolving challenges.
Overall objectives:
Bio-Phoenix establishes five scientific and technological (S&T) objectives that transcend the boundaries of biology, bioengineering, software, and network engineering in order to achieve its ground-breaking goals. To achieve its overall aim, Bio-Phoenix undertakes innovation and development activities driven by the following objectives:
Scientific & Technical Objective 1: Develop a framework for designing co-DNA-based systems, encompassing a modelling language that encodes the "genetic code" of software systems. The goal is to enable the reconstruction of software functionality from near-extinct states, inspired by the structure of DNA.
Scientific & Technical Objective 2: Discover key biological DNA processes, analyze their abstract control mechanisms, and utilize them as a basis for defining core processes. These core processes involve transmitting, injecting, combining, activating, and deactivating co-DNA, enabling the reconstruction of software systems from near-extinct states.
Scientific & Technical Objective 3: Investigate the preservation and verification of emergent system properties, such as survivability, resilience, and security, in the co-DNA approach. The focus is on core biological system reconstruction processes. The objective is to develop generic mechanisms within co-DNA that can assess and validate these properties during system specification and in real-time during runtime.
Scientific & Technical Objective 4: To validate the Bio-Phoenix approach, the project aims to develop a proof-of-concept prototype consisting of two components. A tool will be created for specifying and verifying co-DNA models, while a runtime platform will facilitate co-DNA transmission, execution, and interaction with CCI devices. The platform will prioritize security and offer device-specific and platform-agnostic services to integrate new devices into the Bio-Phoenix ecosystem.
Scientific & Technical Objective 5: The evaluation of the Bio-Phoenix approach will involve using SDN scenarios to assess its effectiveness and validating the ability to specify complex systems using the co-DNA paradigm. Key performance indicators including computational complexity, reconstruction convergence, resource utilization, sensitivity to contextual conditions, security, resilience, and cost will be considered.
