Consensus in anonymous asynchronous systems with crash-recovery and omission failures

In anonymous distributed systems, processes are indistinguishable because they have no identity and execute the same algorithm. Currently, anonymous systems are receiving a lot of attention mainly because they preserve privacy, which is an important property when we want to avoid impersonation attacks. On the other hand, Consensus is a fundamental problem in distributed computing. It is well-known that Consensus cannot be deterministically solved in pure asynchronous anonymous systems if processes can crash (the so-called crash-stop failure model). This impossibility holds even if message losses never occur in transmission. Failure detectors are an elegant and powerful abstraction for achieving deterministic Consensus in asynchronous distributed systems. A failure detector is a distributed object that gives the processes information about crashed processes. Failure detectors have attracted so much attention in the crash-stop failure model because they provide a totally independent abstraction. $$\varOmega $$ Ω is the weakest failure detector to solve Consensus in classic asynchronous systems when a majority of processes never crash, and $$A\varOmega '$$ A Ω ′ is its implementable version for anonymous systems. As far as we know, there is a lack of works in the literature which tackle Consensus in anonymous asynchronous systems where crashed process can recover (the so-called crash-recovery failure model) and also assuming errors in transmission operations (the so-called omission failure model). Extending failure models in the system allows us to design more realistic systems and solve more practical security problems (i.e., fair exchange and the secure multiparty computation). We present, in this paper, an algorithm to solve Consensus using $$A\varOmega '$$ A Ω ′ in anonymous asynchronous systems under the crash-recovery and omission failure models. Another important contribution of this paper is a communication-efficient and latency-efficient implementation of $$A\varOmega '$$ A Ω ′ for these new failure models.

A Review on Fault Tolerance in Distributed Database

In this paper, we study about the different types of fault tolerance techniques which are used in various distributed database systems. The main focus of this research is about how the data are storedin the servers, fault detection techniques and the recovery techniques used. A fault can occur for many reasons. For example, system failure, resource failure, network between the server’s failure and any other reasons. These faults must be emphasis in order to make sure the system can work smoothly without any problem. A proper failure detector and a reliable fault tolerance technique can avoid loss and at once save the system from fail.

Failure Detectors of Strong S and Perfect P Classes for Time Synchronous Hierarchical Distributed Systems

Present failure detection algorithms for distributed systems are designed to work in asynchronous or partially synchronous environments on mesh (all-to-all) connected systems and maintain status of every other process. Several real-time systems are hierarchically connected and require working in strict synchronous environments. Use of existing failure detectors for such systems would generate excess computation and communication overhead. The chapter describes two suspicion-based failure detectors of Strong S and Perfect P classes for hierarchical distributed systems working in time synchronous environments. The algorithm of Strong S class is capable of detecting permanent crash failures, omission failures, link failures, and timing failures. Strong completeness and weak accuracy properties of the algorithm are evaluated. The failure detector of Perfect P class is capable of detecting crash failures, crash-recovery failures, omission failures, link failures, and timing failures. Strong completeness and strong accuracy properties of the failure detector are evaluated.

An Eventually Perfect Failure Detector for Networks of Arbitrary Topology Connected with ADD Channels Using Time-To-Live Values

We present an implementation of an eventually perfect failure detector in an arbitrarily connected, partitionable network. We assume ADD channels: for each one there exist constants [Formula: see text], [Formula: see text], not known to the processes, such that for every [Formula: see text] consecutive messages sent in one direction, at least one is delivered within time [Formula: see text]. The best previous implementation used messages of bounded size, but exponential in [Formula: see text], the number of nodes. The main contribution of this paper is a novel use of time-to-live values in the design of failure detectors, obtaining a flexible implementation that uses messages of size [Formula: see text].