Abstract
Several techniques for database replication using group communication have recently been proposed, namely, the Database State Machine, PostgresR, and the NODO protocol. Although all rely on a totally ordered multicast for consistency, they differ substantially on how multicast is used. This results in different performance trade-offs which are hard to compare as each protocol is presented using a different load scenario and evaluation method. In this paper we evaluate the suitability of such protocols for replication of On-Line Transaction Processing (OLTP) applications in clusters of servers and over wide area networks. This is achieved by implementing them using a common infra-structure and by using a standard workload. The results allows us to select the best protocol regarding performance and scalability in a demanding but realistic usage scenario.

Abstract
Adaptation of system parameters is acknowledged as a requirement to scalable and dependable distributed systems. Unfortunately, adaptation cannot be effective when provided solely by individual system components as the correct decision is often tied to the composition itself and the system as a whole. In fact, proper adaption is a cross-cutting issue: Diagnostic and feedback operations must target multiple components and do it at different abstraction levels. We address this problem with the SERPENTINE middleware platform. By relying on the industry standard JMX as a service interface, it can monitor and operate on a wide range of distributed middleware and application components. By building on a JMX-enabled OSGi runtime, SERPENTINE is able to control the life-cycle of components themselves. The scriptable stateless server and cascading architecture allow for increased dependability and flexibility.

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Abstract
Gossip-based protocols have been gaining an increasing interest from the research community due to the high resilience to node churn and high scalability, thus making them suitable to modern large-scale dynamic systems. Unfortunately, these properties come at the cost of redundant message transmissions to ensure bimodal delivery to all interested peers. In systems with high message throughput, those additional messages could pose a significant burden on the excess of required bandwidth. Furthermore, the overlays upon which message dissemination takes place are oblivious to the underlying network, or rely on posterior optimizations that bias the overlay to mimic the network topology. This contributes even more to the required bandwidth as 'undesirable' paths are chosen with equal probability among desired ones. In a Cloud Computing scenario, nodes tend to be aggregated in sub-nets inside a data-center or in multiple data-centers, which are connected by costlier, long-distance links. The goal of this work is, therefore, to build an overlay that approximates the structure of the physical network, while ensuring the connectivity properties desirable to ensure reliable dissemination. By having each node judiciously choose which nodes are in its dissemination list at construction time, i.e. by giving preference to local nodes, we are able to significantly reduce the number of messages traversing the long-distance links. In a later stage, this overlay shall be presented as a service upon which data dissemination and management protocols could be run. Copyright 2009 ACM.