Easy Consensus Algorithms for the Crash-Recovery Model

In the crash-recovery failure model of asynchronous distributed systems, processes can temporarily stop to execute steps and later restart their computation from a predefined local state. The crash-recovery model is much more realistic than the crash-stop failure model in which processes merely are allowed to stop executing steps. The additional complexity is reflected in the multitude of assumptions and the technical complexity of algorithms which have been developed for that model. We focus on the problem of consensus in the crash-recovery model, but instead of developing completely new algorithms from scratch, our approach aims at reusing existing crash-stop consensus algorithms in a modular way using the abstraction of failure detectors. As a result, we present three new and relatively simple consensus algorithms for the crash-recovery model for different types of assumptions

Network Synchronization in the Crash-Recovery Model

This work investigates the amount of information about failures required to simulate a synchronous distributed system by an asynchronous distributed system prone to crash-recovery failures. A failure detection sequencer SigmaCR for the crash-recovery failure model is defined, which outputs information about crashes and recoveries and about the state of the crashed or recovered processes. Using the simulation technique of a synchronizer, it is shown that in general it is impossible to implement a synchronizer in an asynchronous distributed system with an arbitrary number of concurrent crash-recovery faults. It is shown that a synchronizer is implementable given SigmaCR and an asynchronous distributed system with at least one correct process. Furthermore, it is proven that SigmaCR can be emulated in a synchronous distributed system and hence can be regarded as the weakest failure detection device suitable to implement a synchronizer in the crash-recovery failure model

Homeownership is Still Out of Reach for Millions of Households

Homeownership has long been the leading source of household wealth in the U.S. However, the most recent housing crash stripped many Americans of much of their wealth, as home values plummeted and millions of homes went into foreclosure. These losses were especially painful for homeowners of color, who lost a greater share of wealth in the crash and have rebuilt their wealth more slowly in the recovery. Now, as the housing market recovers and interest rates remain low, many Americans find themselves without the savings or access to credit necessary to be able to purchase a home. Although homeownership is not the best option for every household, many Americans who could greatly benefit from it are still excluded

An illustrative recovery approach for stateful interaction failures of orchestrated processes

During a stateful interaction, a partner service may become unavailable because of a server crash or a temporary network failure. Once the failed service becomes available again, the interaction partners do not have any knowledge about each other’s state, possibly resulting in errors or deadlocks. This paper proposes an approach to the recovery of stateful interactions based on service interaction patterns and process transformations. Our recovery approach works without a central management node and without additional communication protocols. We also minimize the changes to the description of the service supported by the recovery-enabled process. Our approach allows one partner process to be modified in order to support failures in a way that interaction with the other (unchanged) processes is still possible