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In this work we present a cost-based memory partitioning and management mechanism for Memcached, an in-memory key-value store used as Web cache, that is able to dynamically adapt to user requests and manage the memory according to both object sizes and costs. We then present a comparative analysis of the vanilla memory management scheme of Memcached and our approach, using real traces from a major content delivery network operator. Our results indicate that our scheme achieves near-optimal performance, striking a good balance between the performance perceived by end-users and the pressure imposed on back-end servers.

Cost-based Memory Partitioning and Management in Memcached