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@@ -10,7 +10,7 @@ Anna is a low-latency, autoscaling key-value store developed in the [RISE Lab](h
 
 The core design goal for Anna is to avoid expensive locking and lock-free atomic instructions, which have recently been [shown to be extremely inefficient](http://www.jmfaleiro.com/pubs/latch-free-cidr2017.pdf). Anna instead employs a wait-free, shared-nothing architecture, where each thread in the system is given a private memory buffer and is allowed to process requests unencumbered by coordination. To resolve potentially conflicting updates, Anna encapsulates all user data in [lattice](https://en.wikipedia.org/wiki/Lattice_(order)) data structures, which have associative, commutative, and idempotent merge functions. As a result, for workloads that can tolerate slightly stale data, Anna provides best-in-class performance. A more detailed description of the system design and the coordination-free consistency mechanisms, as well as an evaluation and comparison against other state-of-the-art systems can be found in our [ICDE 2018 paper](http://db.cs.berkeley.edu/jmh/papers/anna_ieee18.pdf).
 
-Anna also is designed to be a cloud-native, autoscaling system. When deployed in a cluster, Anna comes with a monitoring subsystem that tracks workload volume, and responds with three key policy decisions: (1) horizontal swelasticity to add or remove resources from the cluster; (2) selective replication of hot keys; and (3) data movement across two storage tiers (memory- and disk-based) for cost efficiency. This enables Anna to maintain its extremely low latencies while also being orders of magnitude more cost efficient than systems like [AWS DynamoDB](https://aws.amazon.com/dynamodb). A more detailed description of the cloud-native design of the system can be found in our [VLDB 2019 paper](http://www.vikrams.io/papers/anna-vldb19.pdf).
+Anna also is designed to be a cloud-native, autoscaling system. When deployed in a cluster, Anna comes with a monitoring subsystem that tracks workload volume, and responds with three key policy decisions: (1) horizontal elasticity to add or remove resources from the cluster; (2) selective replication of hot keys; and (3) data movement across two storage tiers (memory- and disk-based) for cost efficiency. This enables Anna to maintain its extremely low latencies while also being orders of magnitude more cost efficient than systems like [AWS DynamoDB](https://aws.amazon.com/dynamodb). A more detailed description of the cloud-native design of the system can be found in our [VLDB 2019 paper](http://www.vikrams.io/papers/anna-vldb19.pdf).
 
 ## Using Anna