On the Behaviour of General-Purpose Applications on Cloud Storages

Managing data over cloud infrastructures raises novel challenges with respect to existing and well studied approaches such as ACID and long running transactions. One of the main requirements is to provide availability and partition tolerance in a scenario with replicas and distributed control. This comes at the price of a weaker consistency, usually called eventual consistency. These weak memory models have proved to be suitable in a number of scenarios, such as the analysis of large data with Map-Reduce. However, due to the widespread availability of cloud infrastructures, weak storages are used not only by specialised applications but also by general purpose applications. We provide a formal approach, based on process calculi, to reason about the behaviour of programs that rely on cloud stores. For instance, one can check that the composition of a process with a cloud store ensures `strong' properties through a wise usage of asynchronous message-passing

BaseFs - Basically Acailable, Soft State, Eventually Consistent Filesystem for Cluster Management

A peer-to-peer distributed filesystem for community cloud management. https://github.com/glic3rinu/basef

Eventual Consistency: Origin and Support

Eventual consistency is demanded nowadays in geo-replicated services that need to be highly scalable and available. According to the CAP constraints, when network partitions may arise, a distributed service should choose between being strongly consistent or being highly available. Since scalable services should be available, a relaxed consistency (while the network is partitioned) is the preferred choice. Eventual consistency is not a common data-centric consistency model, but only a state convergence condition to be added to a relaxed consistency model. There are still several aspects of eventual consistency that have not been analysed in depth in previous works: 1. which are the oldest replication proposals providing eventual consistency, 2. which replica consistency models provide the best basis for building eventually consistent services, 3. which mechanisms should be considered for implementing an eventually consistent service, and 4. which are the best combinations of those mechanisms for achieving different concrete goals. This paper provides some notes on these important topics

ORLease: Optimistically Replicated Lease Using Lease Version Vector For Higher Replica Consistency in Optimistic Replication Systems

There is a tradeoff between the availability and consistency properties of any distributed replication system. Optimistic replication favors high availability over strong consistency so that the replication system can support disconnected replicas as well as high network latency between replicas. Optimistic replication improves the availability of these systems by allowing data updates to be committed at their originating replicas first before they are asynchronously replicated out and committed later at the rest of the replicas. This leads the whole system to suffer from a relaxed data consistency. This is due to the lack of any locking mechanism to synchronize access to the replicated data resources in order to mutually exclude one another. When consistency is relaxed, there is a potential of reading from stale data as well as introducing data conflicts due to the concurrent data updates that might have been introduced at different replicas. These issues could be ameliorated if the optimistic replication system is aggressively propagating the data updates at times of good network connectivity between replicas. However, aggressive propagation for data updates does not scale well in write intensive environments and leads to communication overhead in order to keep all replicas in sync. In pursuance of a solution to mitigate the relaxed consistency drawback, a new technique has been developed that improves the consistency of optimistic replication systems without sacrificing its availability and with minimal communication overhead. This new methodology is based on applying the concurrency control technique of leasing in an optimistic way. The optimistic lease technique is built on top of a replication framework that prioritizes metadata replication over data replication. The framework treats the lease requests as replication metadata updates and replicates them aggressively in order to optimistically acquire leases on replicated data resources. The technique is demonstrating a best effort semi-locking semantics that improves the overall system consistency while avoiding any locking issues that could arise in optimistic replication systems