HyParView: a membership protocol for reliable gossip-based broadcast (original) (raw)
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Gossip-based broadcast protocols
Gossip, or epidemic, protocols have emerged as a powerful strategy to implement highly scalable and resilient reliable broadcast primitives. Due to scalability reasons, each participant in a gossip protocol maintains only a partial view of the system, from which they select peers to perform gossip exchanges. On the other hand the natural redundancy of gossip protocols makes them less efficient than other approaches that rely in some sort of structured overlay network. The thesis addresses gossip protocols and the problem of building partial views to support their operation. For that purpose, the thesis presents and evaluates a new scalable membership protocol, which is called HyParView, that provides a number of properties, such as degree distribution, accuracy and clustering coefficient, that are highly useful to the construction of efficient gossip protocols. The thesis also introduce two new gossip protocols, based on HyParView, that provide high reliability with small message redundancy. One is an eager push gossip protocol while the other is a tree based gossip broadcast protocol. Simulations results show that, in comparison with other existing protocols, HyParView-based gossip protocols not only provide better reliability but also support higher percentages of node failures, and are able to recover faster from these failures.
A probabilistic characterization of a fault-tolerant gossiping algorithm
Journal of Systems Science and Complexity, 2009
Gossiping is a popular technique for probabilistic reliable multicast (or broadcast). However, it is often difficult to understand the behavior of gossiping algorithms in an analytic fashion. Indeed, existing analyses of gossip algorithms are either based on simulation or based on ideas borrowed from epidemic models while inheriting some features that do not seem to be appropriate for the setting of gossiping. On one hand, in epidemic spreading, an infected node typically intends to spread the infection an unbounded number of times (or rounds); whereas in gossiping, an infected node (i.e., a node having received the message in question) may prefer to gossip the message a bounded number of times. On the other hand, the often assumed homogeneity in epidemic spreading models (especially that every node has equal contact to everyone else in the population) has been silently inherited in the gossiping literature, meaning that an expensive membership protocol is often needed for maintaining nodes' views. Motivated by these observations, the authors present a characterization of a popular class of fault-tolerant gossip schemes (known as "push-based gossiping") based on a novel probabilistic model, while taking the afore-mentioned factors into consideration.
Handbook of Peer-to-Peer Networking, 2009
Gossip, or epidemic, protocols have emerged as a powerful strategy to implement highly scalable and resilient reliable broadcast primitives on large scale peer-to-peer networks. Epidemic protocols are scalable because they distribute the load among all nodes in the system and resilient because they have an intrinsic level of redundancy that masks node and network failures. This chapter provides an introduction to gossip-based broadcast on largescale unstructured peer-to-peer overlay networks: it surveys the main results in the field, discusses techniques to build and maintain the overlays that support efficient dissemination strategies, and provides an in-depth discussion and experimental evaluation of two concrete protocols, named HyParView and Plumtree.
There is an inherent trade-off between epidemic and deterministic tree-based broadcast primitives. Tree-based approaches have a small message complexity in steady-state but are very fragile in the presence of faults. Gossip, or epidemic, protocols have a higher message complexity but also offer much higher resilience. This paper proposes an integrated broadcast scheme that combines both approaches. We use a low cost scheme to build and maintain broadcast trees embedded on a gossip-based overlay. The protocol sends the message payload preferably via tree branches but uses the remaining links of the gossip overlay for fast recovery and expedite tree healing. Experimental evaluation presented in the paper shows that our new strategy has a low overhead and that is able to support large number of faults while maintaining a high reliability.
University of California at San Diego, La …, 1999
Rumor mongering (also known as gossip) is an epidemiological protocol that implements broadcasting with a reliability that can be very high. Rumor mongering is attractive because it is generic, scalable, adapts well to failures and recoveries, and has a reliability that gracefully degrades with the numb e r o f f a i l u r e s i n a r u n. However, rumor mongering uses random selection for communications. We study the impact of using random selection in this paper. We present a protocol that super cially resembles rumor mongering but is deterministic. We show that this new protocol has most of the same attractions as rumor mongering. The one attraction that rumor mongering has|namely graceful degradation|comes at a high cost in terms of the number of messages sent. We compare the two approaches both at an abstract level and in terms of how they perform in an Ethernet and small wide area network of Ethernets.
Efficient epidemic-style protocols for reliable and scalable multicast
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...
Corrected Gossip Algorithms for Fast Reliable Broadcast on Unreliable Systems
2017
The number of components grows ▪ More and more transistors used ▪ But also more racks, cabinets, cables, power supplies, etc. ▪ Everything at a nearly constant reliability per part ▪ Things will fail! ▪ Wang et al., 2010: "Peta-scale systems: MTBF 1.25 hours" ▪ Brightwell et al., 2011: "Next generation systems must be designed to handle failures without interrupting the workloads on the system or crippling the efficiency of the resource." Checkpoint/restart will take longer MTBF! ▪ We need to enable applications to survive failures ▪ … to reach Petascale Exascale! ▪ Like they did for decades in distributed systems!
A middleware for gossip protocols
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.
Scalable epidemic message passing interface fault tolerance
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.