FAWN: A Fast Array of Wimpy Nodes

  • David Andersen ,
  • Jason Franklin ,
  • Michael Kaminsky ,
  • Amar Phanishayee ,
  • Lawrence Tan ,
  • Vijay Vasudevan

Communications of the ACM | , Vol 54: pp. 101-109

This paper presents a new cluster architecture for low-power data-intensive computing. FAWN couples low-power embedded CPUs to small amounts of local flash storage, and balances computation and I/O capabilities to enable efficient, massively parallel access to data.

The key contributions of this paper are the principles of the FAWN architecture and the design and implementation of FAWN-KV–a consistent, replicated, highly available, and high-performance key-value storage system built on a FAWN prototype. Our design centers around purely log-structured datastores that provide the basis for high performance on flash storage, as well as for replication and consistency obtained using chain replication on a consistent hashing ring. Our evaluation demonstrates that FAWN clusters can handle roughly 350 key-value queries per Joule of energy–two orders of magnitude more than a disk-based system.