Sandeep Kulkarni

Raaghav Ravishankar, Sandeep Kulkarni, Nitin H Vaidya

We focus on the problem of checkpointing (or taking a snapshot) in fully replicated eventually consistent distributed databases. In particular, we consider the problem of taking Distributed Transaction-Consistent Snapshots (DTCS). A typical example of such a system is a replicated main-memory database that provides strong eventual consistency. This problem is important and challenging for several reasons: (1) eventual consistency often creates anomalies that the users do not anticipate. Hence, frequent snapshots that can be used to ascertain desired invariants are highly beneficial in their maintenance, and (2) traditional distributed snapshot algorithms lead to significant overhead and/or inconsistencies such as storing dirty writes of incomplete transactions. A key benefit of DTCS is that it summarizes the computation by a sequence of snapshots that are strongly consistent even though the underlying computation is only weakly consistent. In essence, when anomalies arise in an eventually consistent system, DTCS enables one to concentrate solely on the snapshots surrounding the time point of the anomaly. By showing that traditional distributed snapshots lead to inconsistencies and/or excessive overhead, we define the notion of size-minimal DTCS for fully replicated databases. We present MuFASA, an algorithm for a size-minimal DTCS with minimal checkpointing overhead (only O(n) new messages and the addition of a single counter for existing messages). MuFASA also provides a significant benefit over existing checkpointing algorithms for distributed systems and replicated main-memory databases by being a fully asynchronous protocol.

Mohammad Roohitavaf, Sandeep Kulkarni

We present our framework DKVF that enables one to quickly prototype and evaluate new protocols for key-value stores and compare them with existing protocols based on selected benchmarks. Due to limitations of CAP theorem, new protocols must be developed that achieve the desired trade-off between consistency and availability for the given application at hand. Hence, both academic and industrial communities focus on developing new protocols that identify a different (and hopefully better in one or more aspect) point on this trade-off curve. While these protocols are often based on a simple intuition, evaluating them to ensure that they indeed provide increased availability, consistency, or performance is a tedious task. Our framework, DKVF, enables one to quickly prototype a new protocol as well as identify how it performs compared to existing protocols for pre-specified benchmarks. Our framework relies on YCSB (Yahoo! Cloud Servicing Benchmark) for benchmarking. We demonstrate DKVF by implementing four existing protocols --eventual consistency, COPS, GentleRain and CausalSpartan-- with it. We compare the performance of these protocols against different loading conditions. We find that the performance is similar to our implementation of these protocols from scratch. And, the comparison of these protocols is consistent with what has been reported in the literature. Moreover, implementation of these protocols was much more natural as we only needed to translate the pseudocode into Java (and add the necessary error handling). Hence, it was possible to achieve this in just 1-2 days per protocol. Finally, our framework is extensible. It is possible to replace individual components in the framework (e.g., the storage component).

Fathiyeh Faghih, Borzoo Bonakdarpour, Sebastien Tixeuil et al.

In this paper, we introduce an SMT-based method that automatically synthesizes a distributed self-stabilizing protocol from a given high-level specification and network topology. Unlike existing approaches, where synthesis algorithms require the explicit description of the set of legitimate states, our technique only needs the temporal behavior of the protocol. We extend our approach to synthesize ideal-stabilizing protocols, where every state is legitimate. We also extend our technique to synthesize monotonic-stabilizing protocols, where during recovery, each process can execute an most once one action. Our proposed methods are fully implemented and we report successful synthesis of well-known protocols such as Dijkstra's token ring, a self-stabilizing version of Raymond's mutual exclusion algorithm, ideal-stabilizing leader election and local mutual exclusion, as well as monotonic-stabilizing maximal independent set and distributed Grundy coloring.