Transactional Causal Consistency (TCC) is the strongest consistency model compatible with availability and, therefore, it avoids the pitfalls of the CAP theorem while simplifying the programming of cloud applications. Unfortunately, with previous implementations, TCC came at the cost of expensive reads. TCC has been implemented either using conservative approaches, that always require two communication rounds, or using optimistic approaches that, in good cases, require just one round, but in face of skewed workloads, that are common in real applications, can require three communication rounds. In this paper we propose a novel algorithm, named PrompTCC, that in most cases offers reads in just one round and that, even in face of skewed workloads, never takes more than two rounds. As a result, PrompTCC is able to closely approximate the performance of an eventually consistent system while providing stronger guarantees, achieving only 12% throughput and 20% latency penalty in realistic scenarios, outperforming state-of-the-art systems which present up to 37% and 60% throughput and latency degradation respectively.

Edge computing offers support for latencyconstrained applications, by replicating data in the edge. Edge storage systems need to adopt both partial replication, as only data of interest needs to be replicated, and weak consistency models, to avoid the overhead and latency induced by the coordination mechanisms of strong consistency models. In this context, session guarantees are a powerful tool that can be used to simplify the design of edge applications. This paper presents Engage, a storage system that offers efficient support for session guarantees in a partially replicated edge setting. To achieve this, Engage combines the use of vector clocks and distributed metadata propagation services with a payload propagation scheme tailored for the edge. We have implemented Engage and evaluated its performance experimentally. The results show that, when compared with previous proposals, the combination of techniques employed by Engage reduce both the number of false dependencies, that can slow down the system, and the signaling overhead, while improving the freshness of data exposed to clients.

In this paper we study mechanisms that permit to augment the FaaS middleware with support for Transactional Causal Consistency (TCC). At first glance, it may seem that offering TCC to FaaS applications can trivially be achieved, given that the FaaS paadigm does not prevent applications from selecting the storage service with the properties they need. Unfortunately, most TCC storage services ensure consistency only to individual client processes, while a FaaS application is executed by multiple, independent, worker processes. Therefore, there is the need to coordinate the workers, a task that can be a significant source of overhead. We propose a novel architecture to support TCC in FaaS, named FaaSTCC, that significantly reduces the coordination overhead. FaaSTCC achieves this goal by augmenting the workers with a caching layer and by implementing novel mechanisms that maximize the cache usage. First, our storage layer offers to the caching layer a promise, that sets a horizon where the versions retrieved by the cache are guaranteed to be consistent. Second, in FaaSTCC, functions coordinate using snapshot intervals, that support the lazy identification of the read snapshot, increasing the chances of using the cached values. We have implemented and experimentally evaluated FaaSTCC. Our results show that FaaSTCC achieves up to 5x lower average latency and 6x lower tail latency than previous work.