A Layered Architecture for Erasure-Coded Consistent Distributed Storage

© 2017 Association for Computing Machinery. Motivated by emerging applications to the edge computing paradigm, we introduce a two-layer erasure-coded fault-tolerant distributed storage system offering atomic access for read and write operations. In edge computing, clients interact with an edge-layer of servers that is geographically near; the edge-layer in turn interacts with a back-end layer of servers. The edge-layer provides low latency access and temporary storage for client operations, and uses the back-end layer for persistent storage. Our algorithm, termed Layered Data Storage (LDS) algorithm, offers several features suitable for edge-computing systems, works under asynchronous message-passing environments, supports multiple readers and writers, and can tolerate f1 0). Here δ is a parameter closely related to the number of write operations that are concurrent with the read operation, and I(δ > 0) is 1 if δ > 0, and 0 if δ = 0. The cost of persistent storage in the back-end layer is Θ(1). The impact of temporary storage is minimally felt in a multiobject system running N independent instances of LDS, where only a small fraction of the objects undergo concurrent accesses at any point during the execution. For the multi-object system, we identify a condition on the rate of concurrent writes in the system such that the overall storage cost is dominated by that of persistent storage in the back-end layer, and is given by Θ(N)

CausalEC: A Causally Consistent Data Storage Algorithm based on Cross-Object Erasure Coding

Causally consistent distributed storage systems have received significant recent attention due to the potential for providing a low latency data access as compared with linearizability. Current causally consistent data stores use partial or full replication to ensure data access to clients over a distributed setting. In this paper, we develop, for the first time, an erasure coding based algorithm called CausalEC that ensures causal consistency for a collection of read-write objects stored in a distributed set of nodes over an asynchronous message passing system. CausalEC can use an arbitrary linear erasure code for data storage, and ensures liveness and storage properties prescribed by the erasure code. CausalEC retains a key benefit of previously designed replication-based algorithms - every write operation is local, that is, a server performs only local actions before returning to a client that issued a write operation. For servers that store certain objects in an uncoded manner, read operations to those objects also return locally. In general, a read operation to an object can be returned by a server on contacting a small subset of other servers so long as the underlying erasure code allows for the object to be decoded from that subset. As a byproduct, we develop EventualEC, a new eventually consistent erasure coding based data storage algorithm. A novel technical aspect of CausalEC is the use of cross-object erasure coding, where nodes encode values across multiple objects, unlike previous consistent erasure coding based solutions. CausalEC navigates the technical challenges of cross-object erasure coding, in particular, pertaining to re-encoding the objects when writes update the values and ensuring that reads are served in the transient state where the system transitions to storing the codeword symbols corresponding to the new object versions.Comment: Revised to include additional acknowledgement