Modular RADAR: An Immune System Inspired Search and Response Strategy for Distributed Systems [chapter]

Soumya Banerjee, Melanie Moses
<span title="">2010</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
The Natural Immune System (NIS) is a distributed system that solves challenging search and response problems while operating under constraints imposed by physical space and resource availability. Remarkably, NIS search and response times do not scale appreciably with the physical size of the animal in which its search is conducted. Many distributed systems are engineered to solve analogous problems, and the NIS demonstrates how such engineered systems can achieve desirable scalability. We
more &raquo; ... esize that the architecture of the NIS, composed of a hierarchical decentralized detection network of lymph nodes (LN) facilitates efficient search and response. A sub-modular architecture in which LN numbers and size both scale with organism size is shown to efficiently balance tradeoffs between local antigen detection and global antibody production, leading to nearly scale-invariant detection and response. We characterize the tradeoffs as balancing local and global communication and show that similar tradeoffs exist in distributed systems like LN inspired artificial immune system (AIS) applications and peer-to-peer (P2P) systems. Taking inspiration from the architecture of the NIS, we propose a modular RADAR (Robust Adaptive Decentralized search with Automated Response) strategy for distributed systems. We demonstrate how two existing distributed systems (a LN inspired multi-robot control application and a P2P system) can be improved by a modular RADAR strategy. Such a sub-modular architecture is shown to balance the tradeoffs between local communication (within artificial LNs and P2P clusters) and global communication (between artificial LNs and P2P clusters), leading to efficient search and response.
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