Modular RADAR: Immune System Inspired Strategies for Distributed Systems
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The document presents a comparative analysis between the natural immune system (NIS) and distributed systems, highlighting that both operate under similar constraints regarding physical space and resource limitations. It introduces the concept of 'modular radar', a strategy derived from the architecture of the NIS that allows for scale-invariant search and response times, which can improve performance in peer-to-peer systems and multi-robot control. The findings suggest that adapting this modular radar strategy could lead to enhanced efficiency in various distributed systems.
Modular RADAR: Immune System Inspired Strategies for Distributed Systems
- 1. Modular RADAR: Immune System Inspired Strategies for Distributed Systems Soumya Banerjee and Melanie Moses University of New Mexico
- 2. Outline • Distributed systems and the natural immune system (NIS) operate under similar constraints • Effect of body size on NIS search and response times • Scale invariant detection and response • Hypothesis: architecture of the lymphatic system leads to invariant search and response times • Modular RADAR strategy • Number and size of lymph nodes increases with organism size • Distributed systems – P2P system – Multi-robot control • Future directions
- 3. Properties of Distributed Systems • Physical space is important • Resource constrained (power, bandwidth) • Performance scalability is a desirable feature
- 4. Properties of the Natural Immune System (NIS) • Operates under constraints of physical space • Resource constrained (metabolic input, number of immune system cells) • Performance scalability is an important concern (mice to horses)
- 5. Problems Faced by the NIS • Only a few NIS cells are specific to a particular pathogen (1 in 6 10 T-cells)
- 6. Search Problem • They have to search throughout the whole body to locate small quantities of pathogens
- 7. Response Problem • Have to respond by producing antibodies
- 8. West Nile Virus infection 25 species of birds and 4 species of mammals infected with WNV • Bunning et al. (2002) • Komar et al. (2002) Unimodal peak at ~ 2 to 4 days post infection Immune response rates and times are not correlated with host mass • assuming immune response causes peak • B-cell response in mice ~ 4 days Komar et al. 2002
- 9. Nearly Scale-Invariant Search and Response • Experimental data indicates that the NIS can search for pathogens and respond by producing antibodies in time invariant of organism body size
- 10. Nearly Scale-Invariant Search and Response • How does the immune system search and respond in almost the same time irrespective of the size of the search space?
- 11. Solution: Lymph Nodes (LN) • A place in which IS cells and the pathogen can encounter each other in a small volume • Form a decentralized detection network Crivellato et al. 2004
- 12. Modular RADAR • Search is now – modular – efficient – parallel We call this a modular RADAR (Robust Adaptive Decentralized search Automated Response)
- 13. Hypothesis • Architecture of the immune system is responsible for nearly scale-invariant search and response properties • We now focus on West Nile Virus www.lymphadvice.com
- 18. DC DC cTcell,DC T t detect t migrate t detect trecruit
- 19. Scaling of LN Size and Number T t local t global DC DC DC,cTcell T t detect t migrate t detect t recruit After minimizing we have 4 /7 N M ,where N is the number of LNs 3/7 VLN M ,where VLN is the size of a LN • this is in qualitative agreement with data • need more data Banerjee and Moses 2010, Swarm Intelligence (under review)
- 22. Modular RADAR Architecture T t local t global M1/ 7
- 23. Summary • There are increasing costs to global communication as organisms grow bigger • Semi-modular architecture balances the opposing goals of detecting pathogen (local communication) and recruiting IS cells (global communication) • This leads to scale invariant detection and response • Can we emulate this modular RADAR strategy in distributed systems?
- 24. Peer-to-Peer Systems • Used to provide distributed services like search, content integration and administration • Computer nodes store data or service • No single node has complete global information • Decentralized search using local information to locate data
- 25. Semantic Small World (SSW) P2P Overlay Network • Represents objects by a collection of attribute values derived from object content • Aggregates data objects with similar semantics close to each other in clusters in order to facilitate efficient search • It maintains short and long-distance connections between clusters. • The long-distance connections follow a precise probability distribution making the whole overlay network small-world (Kleinberg 2000) * M. Li et al. 2004
- 26. Semantic Small World (SSW) P2P Overlay Network adapted from M. Li et al. 2004
- 27. Bounds for Efficient Decentralized Search in SSW • Average search path length for search across clusters is 2 log (n /c) tglobal O l where n is the total number of nodes, c is the number of nodes in a cluster, l is the number of long-distance connections per node M. Li et al. 2004
- 28. SSW with Modular RADAR • Our contribution is to – vary the cluster size – vary the number of long-distance connections as l log(n /c) log(numclusters) t global O(log(n /c)) – such densification is seen as an emergent property of technological networks (Kleinberg 2004) and also incorporates redundant paths
- 29. Time to Search in SSW with Modular RADAR T t local t global 1/ 2 T 1c 2 log(n /c) minimizing by differentiating with respect to c we have c O(log 2 n) T O(log n log log n)
- 30. SSW with Modular RADAR
- 31. Wireless Mobile Devices: Original System adapted from Nair et al. 2008
- 32. Tradeoffs • Potential communication bottlenecks – local communication between robots and computer servers – global communication between computer servers • If both local and global communication are constrained, then sub-modular architecture balances tradeoff
- 33. System modified with modular RADAR
- 34. Future Directions • Strategy is widely applicable • A modular RADAR strategy can be used to augment – Intrusion Detection Systems (Hofmeyr and Forrest 1999) – Multi-Robot Control – Wireless Sensor Networks – Wireless Devices (Specknets: Hart and Davoudani 2009) – Collective Robotic Systems using Artificial Lymph Node Architectures (Mokhtar, Timmis, Tyrrell and Bi 2008)
- 35. Summary • The NIS and distributed systems operate under similar constraints • Physical space of organism body constrains NIS search and response times • The NIS has evolved a sub-modular RADAR architecture in which LN numbers and sizes increase with organism body size • This balances the tradeoff between local communication (pathogen detection) and global communication (antibody production); this leads to scale invariant detection and response • Similar tradeoffs also exist in distributed systems • Such a modular RADAR approach is shown to improve search times in P2P and multi-robot control systems • Can be applied in other distributed systems
- 36. Acknowledgements • Dr. Melanie Moses • SFI Complex Systems • Dr. Alan Perelson Summer School • Dr. Stephanie • Travel grants from Forrest PIBBS (Dept. of Biology, UNM) • Dr. Jedidiah Crandall • Travel grants from • Dr. Rob Miller RPT and SCAP • Dr. Sam Loker (UNM) • NIH COBRE CETI grant (RR018754)