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Biologically Inspired Programming for Self-Healing Systems

This work explores a biologically inspired programming model designed for self-healing systems, drawing from natural processes and cellular automata. The model reflects how biological cells sense their surroundings and communicate via chemical diffusion. It highlights concepts such as redundancy, decentralized processes, and self-awareness. The study provides insights into implementing these principles in programming, targeting efficient system recovery and resilience. Learnings from nature's engineering solutions are emphasized, encouraging the application of biological strategies to technological challenges.

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Biologically Inspired Programming for Self-Healing Systems

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  1. A Biologically Inspired Programming Modelfor Self-Healing Systems David Evans Computer Science Lance Davidson Biology Selvin George Computer Science U N I V E R S I T Y O F V I R G I N I A Selvin George

  2. Self Healing in Nature Selvin George

  3. Diffusion – Local Communication Cells are aware of surroundings by sensing chemicals emitted by other cells Selvin George

  4. Nature’s Programs – Observations • Aware • Of self • Of environment • Redundant • Decentralized • Expressive • Human program – 3 billion base pairs (~250MB) • Two human programs differ by about 0.5MB (< 1% of Windows 2000) Selvin George

  5. Our Programming Model • Similar to cellular automata • Simple chemical diffusion model • Correspondence to biological cells • Genes turn on and off  state changes • Emit different chemicals depending on state • Change state based on sensed chemicals • Cells can divide asymmetrically Selvin George

  6. state s1 { emits (a, 0.1) transitions (0 <= a <= 0.375) -> (s2, s2) axis; -> (s1); } state s2 { emits (a, 0.1) transitions (0 <= a <= 0.375) -> (s3, s3) normal-X; -> (s2); } state s3 { emits (a, 0.1) transitions (0 <= a <= 0.375) -> (s1, s1) normal-Y; -> (s3); } Blastula Program s1 a s2 a s3 a Selvin George

  7. Self-Healing Blastula state s1 { emits (a, 0.1) transitions (0 <= a <= 0.375) -> (s2, s2) axis; -> (s1); } state s2 { emits (a, 0.1) transitions (0 <= a <= 0.375) -> (s3, s3) normal-X; -> (s2); } state s3 { emits (a, 0.1) transitions (0 <= a <= 0.375) -> (s1, s1) normal-Y; -> (s3); } Kill Cell Selvin George

  8. Selvin George

  9. Distributed Wireless File ServiceFile Distribution and Update Server inhibit replicate Selvin George

  10. Distributed Wireless File ServiceFile Distribution and Update Selvin George

  11. DWFS Simulation Purple Nodes – store File 1 Concentric Circles – Inhibit/Replicate Green Circle – File Request White Circle – Server Response Selvin George

  12. Mantra • Biology has killed trillions of organisms over millions of years to solve complex engineering problems • Engineers should be able to learn from these solutions • Simulator available: http://swarm.cs.virginia.edu/cellsim Selvin George

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