Abstract
Database replication based on group communication systems has recently been proposed as an efficient and resilient solution for large-scale data management. However, its evaluation has been conducted either on simplistic simulation models, which fail to assess concrete implementations, or on complete system implementations which are costly to test with realistic large-scale scenarios. This paper presents a tool that combines implementations of replication and communication protocols under study with simulated network, database engine, and traffic generator models. Replication components can therefore be subjected to realistic large scale loads in a variety of scenarios, including fault-injection, while at the same time providing global observation and control. The paper shows first how the model is configured and validated to closely reproduce the behavior of a real system, and then how it is applied, allowing us to derive interesting conclusions both on replication and communication protocols and on their implementations.

Abstract
Partial replication is an alluring technique to ensure the reliability of very large and geographically distributed databases while, at the same time, offering good performance. By correctly exploiting access locality most transactions become confined to a small subset of the database replicas thus reducing processing, storage access and communication overhead associated with replication. The advantages of partial replication have however to be weighted against the added complexity that is required to manage it. In fact, if the chosen replica configuration prevents the local execution of transactions or if the overhead of consistency protocols offsets the savings of locality, potential gains cannot be realized. These issues are heavily dependent on the application used for evaluation and render simplistic benchmarks useless. In this paper, we present a detailed analysis of Partial Database State Machine (PDBSM) replication by comparing alternative partial replication protocols with full replication. This is done using a realistic scenario based on a detailed network simulator and access patterns from an industry standard database benchmark. The results obtained allow us to identify the best configuration for typical on-line transaction processing applications.

Abstract
Consensus is an abstraction of a variety of important challenges in dependable distributed systems. Thus a large body of theoretical knowledge is focused on modeling and solving consensus within different system assumptions. However, moving from theory to practice imposes compromises and design decisions that may impact the elegance, trade-offs and correctness of theoretical appealing consensus protocols. In this paper we present the implementation and detailed analysis, in a real environment with a large number of nodes, of mutable consensus, a theoretical appealing protocol able to offer a wide range of trade-offs (called mutations) between decision latency and message complexity. The analysis sheds light on the fundamental behavior of the mutations, and leads to the identification of problems related to the real environment. Such problems are addressed without ever affecting the correctness of the theoretical proposal.

Abstract
This chapter illustrates how the concepts and algorithms described earlier in this book can be used to build practical database replication systems. This is achieved first by addressing architectural challenges on how required functionality is provided by generally available software componentes and then how different components can be efficiently integrated. A second set of practical challenges arises from experience on how performance assumptions map to actual environments and real workloads. The result is a generic architecture for replicated database management systems, focusing on the interfaces between key components, and then on how different algorithmic and practical optimization options map to real world gains. This shows how consistent database replication is achievable in the current state of the art.

Abstract
Although epidemic or gossip-based multicast is a robust and scalable approach to reliable data dissemination, its inherent redundancy results in high resource consumption on both links and nodes. Tins problem is aggravated in settings that have costlier or resource constrained links as happens in Cloud Computing infrastructures composed by several interconnected data centers across the globe. The goal of this work is therefore to improve the efficiency of gossip-based reliable multicast by reducing the load imposed on those constrained links. hi detail, the proposed CLON protocol combines an overlay that gives preference to local links and a dissemination strategy that takes into account locality. Extensive experimental evaluation using a very large number of simulated nodes shows that this results in a reduction of traffic in constrained links by an order of magnitude, while at the same time preserving the resilience properties that make gossip-based protocols so attractive.

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.