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Distributed in-memory caching systems such as memcached have become crucial for improving the performance of web applications. However, memcached by itself does not control which node is responsible for each data object, and inefficient partitioning schemes can easily lead to load imbalances. Further, a statically sized memcached cluster can be insufficient or inefficient when demand rises and falls. In this paper, the authors present an automated cache management system that both intelligently decides how to scale a distributed caching system and uses a new, adaptive partitioning algorithm that ensures that load is evenly distributed despite variations in object size and popularity.
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