A novel causally consistent replication protocol with partial geo-replication

• Autor(a) principal: Fouto, Pedro Filipe Veiga
• Data de Publicação: 2018
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10362/63048
• topic: Distributed datastore systems; causal+ consistency; geo-replication; partial replication; Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática

Distributed storage systems are a fundamental component of large-scale Internet services. To keep up with the increasing expectations of users regarding availability and latency, the design of data storage systems has evolved to achieve these properties, by exploiting techniques such as partial replication, geo-replication and weaker consistency models. While systems with these characteristics exist, they usually do not provide all these properties or do so in an inefficient manner, not taking full advantage of them. Additionally, weak consistency models, such as eventual consistency, put an excessively high burden on application programmers for writing correct applications, and hence, multiple systems have moved towards providing additional consistency guarantees such as implementing the causal (and causal+) consistency models. In this thesis we approach the existing challenges in designing a causally consistent replication protocol, with a focus on the use of geo and partial data replication. To this end, we present a novel replication protocol, capable of enriching an existing geo and partially replicated datastore with the causal+ consistency model. In addition, this thesis also presents a concrete implementation of the proposed protocol over the popular Cassandra datastore system. This implementation is complemented with experimental results obtained in a realistic scenario, in which we compare our proposal withmultiple configurations of the Cassandra datastore (without causal consistency guarantees) and with other existing alternatives. The results show that our proposed solution is able to achieve a balanced performance, with low data visibility delays and without significant performance penalties.