Abstract
The scalability and resilience of epidemic multicast, also called probabilistic or gossip-based multicast, rests on its symmetry: Each participant node contributes the same share of bandwidth thus spreading the load and allowing for redundancy. On the other hand, the symmetry of gossiping means that it does not avoid nodes or links with less capacity. Unfortunately, one cannot naively avoid such symmetry without also endangering scalability and resilience. In this paper we point out how to break out of this dilemma, by lazily deferring message transmission according to a configurable policy. An experimental proof-of-concept illustrates the approach.

Abstract
Semantic Reliability is a novel correctness criterion for multicast protocols based on the concept of message obsolescence: A message becomes obsolete when its content or purpose is superseded by a subsequent message. By exploiting obsolescence, a reliable multicast protocol may drop irrelevant messages to find additional buffer space for new messages. This makes the multicast protocol more resilient to transient performance perturbations of group members, thus improving throughput stability. This paper describes our experience in developing a suite of semantically reliable protocols. It summarizes the motivation, definition, and algorithmic issues and presents performance figures obtained with a running implementation. The data obtained experimentally is compared with analytic and simulation models. This comparison allows us to confirm the validity of these models and the usefulness of the approach. Finally, the paper reports the application of our prototype to distributed multiplayer games.

Abstract
Data base clusters based on share-nothing replication techniques are currently widely accepted as a practical solution to scalability and availability of the data tier. A key issue when planning such systems is the ability to meet service level agreements when load spikes occur or cluster nodes fail. This translates into the ability to provision and deploy additional nodes. Many current research efforts focus on designing autonomic controllers to perform such reconfiguration, tuned to quickly react to system changes and spawn new replicas based on resource usage and performance measurements. In contrast, we are concerned about the inherent impact of deploying an additional node to an online cluster, considering both the time required to finish such an action as well as the impact on resource usage and performance of the cluster as a whole. If noticeable, such impact hinders the practicability of self-management techniques, since it adds an additional dimension that has to he accounted for. Our approach is to systematically benchmark a number of different reconfiguration scenarios to assess the cost of bringing a new replica online. We consider factors such as: workload characteristics, incremental and parallel recovery, flow control and outdatedness of the recovering replica. As a result, we show that research should be refocused from optimizing the capture and transmition of changes to applying them, which in a realistic setting dominates the cost of the recovery operation.

Abstract
Epidemic, or probabilistic, multicast protocols have emerged as a viable mechanism to circumvent the scalability problems of reliable multicast protocols. However most existing epidemic approaches use connectionless transport protocols to exchange messages and rely on the intrinsic robustness of the epidemic dissemination to mask network omissions. Unfortunately, such an approach is not network-friendly since the epidemic protocol makes no effort to reduce the load imposed on the network when the system is congested. In this paper we propose a novel epidemic protocol whose main characteristic is to be network-friendly This property is achieved by relying on connection-oriented transport connections, such as TCP/IP to support the communication among peers. Since during congestion messages accumulate in the border of the network, the protocol uses an innovative buffer management scheme, that combines different selection techniques to discard messages upon overflow. This technique improves the quality of the information delivered to the application during periods of network congestion. The protocol has been implemented and the benefits of the approach are illustrated using a combination of experimental and simulation results.

Abstract
Total order multicast greatly simplifies the implementation of fault-tolerant services using the replicated state machine approach. The additional latency of total ordering can be masked by taking advantage of spontaneous ordering observed in LANs: A tentative delivery allows the application to proceed in parallel with the ordering protocol. The effectiveness of the technique rests on the optimistic assumption that a large share of correctly ordered tentative deliveries offsets the cost of undoing the effect of mistakes. This paper proposes a simple technique which enables the usage of optimistic delivery also in WANs with much larger transmission delays where the optimistic assumption does not normally hold. Our proposal exploits local clocks and the stability of network delays to reduce the mistakes in the ordering of tentative deliveries. An experimental evaluation of a modified sequencer-based protocol is presented, illustrating the usefulness of the approach in fault-tolerant database management.

Abstract
The sheer volumes of data handled by today's Internet services demand uncompromising scalability from the persistence substrates. Such demands have been successfully addressed by highly decentralized key-value stores invariably governed by a distributed hash table. The availability of these structured overlays rests on the assumption of a moderately stable environment. However, as scale grows with unprecedented numbers of nodes the occurrence of faults and churn becomes the norm rather than the exception, precluding the adoption of rigid control over the network's organization. In this position paper we outline the major ideas of a novel architecture designed to handle today's very large scale demand and its inherent dynamism. The approach rests on the well-known reliability and scalability properties of epidemic protocols to minimize the impact of churn. We identify several challenges that such an approach implies and speculate on possible solutions to ensure data availability and adequate access performance. © 2011 IEEE.