Small Cache, Big Effect: Provable Load Balancing for Randomly Partitioned Cluster Services

ACM Symposium on Cloud Computing (SOCC'11), Cascais, Portugal, October, 2011.

Bin Fan, Hyeontaek Lim, David Andersen and Michael Kaminsky*

School of Computer Science
Carnegie Mellon University
Pittsburgh, PA 15213

*Intel Labs


Load balancing requests across a cluster of back-end servers is critical for avoiding performance bottlenecks and meeting service-level objectives (SLOs) in large-scale cloud computing services. This paper shows how a small, fast popularity-based front-end cache can ensure load balancing for an important class of such services; furthermore, we prove an O(n log n) lower-bound on the necessary cache size and show that this size depends only on the total number of back-end nodes n, not the number of items stored in the system. We validate our analysis through simulation and empirical results running a key-value storage system on an 85-node cluster.





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