HyParView: A membership protocol for reliable gossip-based broadcast

2000

Epidemic-style (gossip-based) techniques have recently emerged as a scalable class of protocols for peer-to-peer reliable multicast dissemination in large process groups. These protocols provide probabilistic guarantees on relia-bility and scalability. However, popular implementations of epidemic-style dissemination are reputed to suffer from two major drawbacks: (a) (Network Overhead) when de-ployed on a WAN-wide or VPN-wide scale they generate a large number

Cluster Computing, 2004

Gossip protocols and services provide a means by which failures can be detected in large, distributed systems in an asynchronous manner without the limits associated with reliable multicasting for group communications. Extending the gossip protocol such that a system reaches consensus on detected faults can be performed via a flat structure, or it can be hierarchically distributed across cooperating layers of nodes. In this paper, the performance of gossip services employing flat and hierarchical schemes is analyzed on an experimental testbed in terms of consensus time, resource utilization and scalability. Performance associated with a hierarchically arranged gossip scheme is analyzed with varying group sizes and is shown to scale well. Resource utilization of the gossip-style failure detection and consensus service is measured in terms of network bandwidth utilization and CPU utilization. Analytical models are developed for resource utilization and performance projections are made...

2010

Gossip protocols are known to be highly robust in scenarios with high churn, but if the data that is being gossiped becomes corrupted, a protocol's very robustness can make it hard to fix the problem. All participants need to be taken down, any disk-based data needs to be scrubbed, the cause of the corruption needs to be fixed, and only then can participants be restarted. If even a single participant is skipped in this process, say because it was temporarily unreachable, then it can contaminate the entire system all over again. We describe the design and implementation of a new middleware for gossip protocols that addresses this problem. Our middleware offers the ability to update code dynamically and provides a small resilient core that allows updating code that has failed catastrophically. Our initial PlanetLab-based deployment demonstrates that the middleware is efficient.

Bulletin of Electrical Engineering and Informatics, 2022

Resilience and fault tolerance are challenging tasks in the field of high performance computing (HPC) and extreme scale systems. Components fail more often in such systems, results in application abort. Adopting faulttolerance techniques can be consistently detect failures and continue application's execution even if the failures exist. A prominent parallel programming specification, message passing interface (MPI), as it would be used to implement failure detection and consensus algorithm in this paper. Although the MPI does not facilitate fault tolerant behavior, this work presents a fault tolerant, matrix based failure detection and consensus algorithm. The proposed algorithm uses Gossiping. To detect failures, randomised pinging will be applied during the execution of the algorithm by using piggybacked gossip messages. In order to achieve consensus on the failures in the system, failed processes' information will be sent using the same piggybacked gossip messages to all the alive processes. The algorithm was implemented in MPI framework and is completely fault tolerant. The results exhibit all the MPI process failures were detected using randomised pinging and global consensus has achieved on failed MPI process in the system.

Cluster Computing, 1999

 Three protocols for gossip-based failure detection services in large-scale heterogeneous clusters are analyzed and compared. The basic gossip protocol provides a means by which failures can be detected in large distributed systems in an asynchronous manner without the limits associated with reliable multicasting for group communications. The hierarchical protocol leverages the underlying network topology to achieve faster failure detection. In addition to studying the effectiveness and efficiency of these two agreement protocols, we propose a third protocol that extends the hierarchical approach by piggybacking gossip information on application-generated messages. The protocols are simulated and evaluated with a fault-injection model for scalable distributed systems comprised of clusters of workstations connected by high-performance networks, such as the CPlant machine at Sandia National Laboratories. The model supports permanent and transient node and link failures, with rates specified at simulation time, for processors functioning in a fail-silent fashion. Through high-fidelity, CAD-based modeling and simulation, we demonstrate the strengths and weaknesses of each approach in terms of agreement time, number of gossips, and overall scalability.

24th International Conference on Distributed Computing Systems, 2004. Proceedings., 2004

Distributed content-based publish-subscribe middleware provides the necessary decoupling, flexibility, expressiveness, and scalability required by modern distributed applications. Unfortunately, this kind of middleware usually does not provide reliability guarantees, as this problem has been thus far largely disregarded by the research community and solutions developed in other contexts are not immediately applicable.

Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001, 2001

Gossip protocols and services provide a means bywhich failures can be detected in large, distributed systemsin an asynchronous manner without the limits associatedwith reliable multicasting for group communications.Gossiping with consensus can take place throughout thesystem via a flat structure, or it can be hierarchicallydistributed across cooperating layers of nodes. In thispaper, the performance of flat and layered protocols isanalyzed on an experimental testbed in terms of consensustime and scalability. Performance associated with layeredgossip is analyzed with varying group sizes and is shownto scale well in a heterogeneous environment.

Lecture Notes in Computer Science, 1999

A reliable multicast protocol ensures that all of the intended recipients of a message m that do not fail eventually deliver m. For example, consider the reliable multicast protocol of 10], and consider a message m, sent by process p 1 , that is intended to bedelivered by p 1 , p 2 , and p 3. We impose a directed spanning tree on these processes that is rooted at the message source. For example, for m we could have the directed spanning tree p 1 ! p 2 ! p 3. The message m propagates down this spanning tree and acknowledgments of the receipt of m propagate back up the tree. A leaf process in this tree delivers m when it receives m, and a non-leaf process delivers m when it gets the acknowledgment for m from all of its children. If a non-leaf process (say, p 1) does not get an acknowledgment for m from one of its children (here, p 2), then it removes the child from the tree and \adopts" that child's children (here, p 3). The process sends m to the newly-adopted children and continues the broadcast. A similar monitoring and adoption approach is used to recover from the failure of the root of the tree. Reliable multicast protocols are intended for local area networks. Unfortunately, most implementations of reliable multicast do not scale well to large numbersofprocesses even when all are in the same local area network 3]. For example, with the protocol given above, the sender cannot deliver its own message m until it knows that all non-failed processes have already delivered m. The latency can bereduced by using a bushy directed spanning tree, but doing so increases the overhead of some processes, where by overhead we mean the numberofmessages a process sends and receives in the reliable multicast of a single m. As the number of processes increases, either the latency or the overhead at some processes increases. Hence, when a multicast is to be sent to a large numberofprocesses or processes located on a wide area network, a protocol like IP Multicast 4] that has been speci cally designed for these cases is preferable even though it is not as reliable as reliable multicast. More recently, gossip-based protocols have been developed to address scalability while still providing high reliability of message delivery. These protocols, which w ere rst developed for replicated database consistency management in the Xerox Corporate Internet 5], have been built to implement not only reliable multicast 3, 7] but also failure detection 11] and garbage collection 12]. Gossip protocols are scalable because they don't require as much synchronization as traditional reliable multicast protocols. A generic gossip protocol running at process p has a structure something

… Communications and Networks …, 2011

Ubiquitous and wirelessly connected devices are the present status quo in terms of networks around us. With the ever increase of scale, there comes also the problem of various communication failures. They are usually caused by hardware, software, or any other medium access contention. For the case of mobile networks, path uncertainty comes also into picture due to node mobility. All this leads to low quality of service and reduced user experience. The main contribution of the paper is the introduction of a novel ...

ACM SIGOPS Operating Systems Review, 2007

Gossip-based communication protocols are often touted as being robust. Not surprisingly, such a claim relies on assumptions under which gossip protocols are supposed to operate. In this paper, we discuss and in some cases expose some of these assumptions and discuss how sensitive the robustness of gossip is to these assumptions. This analysis gives rise to a collection of new research challenges.