Skalierbares schlüssel-basiertes Routing in verteilten Systemen ist eine Methode zur Weiterleitung von Nachrichten zu den für die Partition verantwortlichen Maschinen. Diese Technik findet Verwendung in Key-Value Speichersystemen, Content Distribution Networks oder auch beim Media Streaming. Einer der Gründe für die Verbreitung ist die Einfachheit der Routingabstraktion, bei welcher der Entwickler sich nicht um die Details des Gruppenmanagements oder Datenreplikation kümmern muss. Auf der anderen Seite sind die meisten schlüssel-basierten Routingverfahren optimistische Verfahren, bei denen der Datenzugriff keine strenge Konsistenz bietet. In dieser Arbeit präsentieren wir das System Recode mit dem schlüssel-basierten Routingabstraktion routecast, welches eine strengere Zugriffssemantik ermöglicht. Dabei garantiert routecast, dass Nachrichten eines bestimmten Schlüssels in der gleichen Reihenfolge an alle Replikate geliefert werden. Mit Hilfe dieser strengeren Garantien können auch Anwendungen wie Koordinations- oder Metadatendienste bzw. konsistente Speichersysteme das schlüssel-basierte Routing verwenden. Recode ist außerdem rekonfigurierbar bei Veränderungen der zur Verfügung stehenden Maschinen sowie bei Auslastungsänderung. Es ist ein komplett dezentralisiertes System und enthält damit keinen single-point of failure oder Systemengpass. Die drei Hauptbeiträge der Arbeit sind 1) die Abstraktion der Gruppenkommunikation unter Verwendung von Primary/Backup mit Leases für ein failover des Primary, 2) die Entwicklung und die Algorithmen der routcast-Primitive, 3) Mechanismen zur atomaren Rekonfiguration des dezentralen Schlüsselraumes. Um die Einfachheit unseres Ansatzes zu betonen, beschreiben wir außerdem drei verschiedene Anwendungen aufbauend auf Recode. Abschließend zeigen wir durch die Evaluation von Recode in einer Cluster-Umgebung die Leistungsfähigkeit. / Scalable key-based routing in distributed systems, where a mes- sage is forwarded towards a machine responsible for a partition in a large key space, has been used in many services such as key-value stores, content distribution networks and media streaming. This success can mainly be attributed to the simplicity of the route ab- straction, a developer does not need to care about the mechanisms for membership management, load balancing or data replication. A limitation, however, is that most key-based routing solutions are best-effort, which means that only eventually consistent data access is possible. This thesis presents a system (Recode) with a key-based routing primitive called routecast which provides strong delivery semantics. More specifically, routecast guarantees that a message for a key is delivered in the same total order at a set of replicas. With stronger guarantees, applications such as coordination and metadata services as used in large storage systems or consistent key-value stores can use key-based routing. Additionally, Recode aims to be both re- configurable, to handle changes to the machines running the service and updates to the workload, and fully decentralized which means there is no single point of failure or bottleneck. We make three main contributions in this thesis: 1) a group com- munication abstraction using primary/backup with leases for pri- mary fail-over, 2) the design and algorithms of the routecast-primitive and, 3) mechanisms for atomic reconfiguration of a decentralized key space. Each part of the system is broken up into modules and presented with a specification and a set of algorithms. To validate the simplicity claim, we describe how to implement three different applications on top of Recode. Finally, we evaluate Recode in a cluster environment and show that the performance is competitive.

This thesis investigates the application of autonomic management to a distributed storage system. Effects on performance and resource consumption were measured in experiments, which were carried out in a local area test-bed. The experiments were conducted with components of one specific distributed storage system, but seek to be applicable to a wide range of such systems, in particular those exposed to varying conditions. The perceived characteristics of distributed storage systems depend on their configuration parameters and on various dynamic conditions. For a given set of conditions, one specific configuration may be better than another with respect to measures such as resource consumption and performance. Here, configuration parameter values were set dynamically and the results compared with a static configuration. It was hypothesised that under non-changing conditions this would allow the system to converge on a configuration that was more suitable than any that could be set a priori. Furthermore, the system could react to a change in conditions by adopting a more appropriate configuration. Autonomic management was applied to the peer-to-peer (P2P) and data retrieval components of ASA, a distributed storage system. The effects were measured experimentally for various workload and churn patterns. The management policies and mechanisms were implemented using a generic autonomic management framework developed during this work. The motivation for both groups of experiments was to test management policies with the objective to avoid unsatisfactory situations with respect to resource consumption and performance. Such unsatisfactory situations occur when either the P2P layer or the data retrieval mechanism is configured statically. In a statically configured P2P system two unsatisfactory situations can be identified. The first arises when the frequency with which P2P node states are verified is low and membership churn is high. The P2P node state becomes inaccurate due to a high membership churn, leading to errors during the routing process and a reduction in performance. In this situation it is desirable to increase the frequency to increase P2P state accuracy. The converse situation arises when the frequency is high and churn is low. In this situation network resources are used unnecessarily, which may also reduce performance, making it desirable to decrease the frequency. In ASA’s data retrieval mechanism similar unsatisfactory situations can be identified with respect to the degree of concurrency (DOC). The DOC controls the eagerness with which multiple redundant replicas are retrieved. An unsatisfactory situation arises when the DOC is low and there is a large variation in the times taken to retrieve replicas. In this situation it is desirable to increase the DOC, because by retrieving more replicas in parallel a result can be returned to the user sooner. The converse situation arises when the DOC is high, there is little variation in retrieval time and there is a network bottleneck close to the requesting client. In this situation it is desirable to decrease the DOC, since the low variation removes any benefit in parallel retrieval, and the bottleneck means that decreasing parallelism reduces both bandwidth consumption and elapsed time for the user. The experimental evaluations of autonomic management show promising results, and suggest several future research topics. These include optimisations of the managed mechanisms, alternative management policies, different evaluation methods, and the application of developed management mechanisms to other facets of a distributed storage system. The findings of this thesis could be exploited in building other distributed storage systems that focus on harnessing storage on user workstations, since these are particularly likely to be exposed to varying, unpredictable conditions.