This paper presents a new persistent data management layer designed to simplify cluster-based Internet service construction. This self-managing layer, called a distributed data structure (DDS), presents a conventional single-site data structure interface to service authors, but partitions and replicates the data across a cluster. We have designed and implemented a distributed hash table DDS that has properties necessary for Internet services (incremental scaling of throughput and data capacity, fault tolerance and high availability, high concurrency, consistency, and durability). The hash table uses two-phase commits to present a coherent view of its data across all cluster nodes, allowing any node to service any task. We show that the distributed hash table simplies Internet service construction by decoupling service-specic logic from the complexities of persistent, consistent state management, and by allowing services to inherit the necessary service properties from the DDS rather ...

We propose a new paradigm for building scalable distributed systems. Our approach does not require dealing with message-passing protocols—a major complication in existing distributed systems. Instead, developers just design and manipulate data structures within our service called Sinfonia. Sinfonia keeps data for applications on a set of memory nodes, each exporting a linear address space. At the core of Sinfonia is a novel minitransaction primitive that enables efficient and consistent access to data, while hiding the complexities that arise from concurrency and failures. Using Sinfonia, we implemented two very different and complex applications in a few months: a cluster file system and a group communication service. Our implementations perform well and scale to hundreds of machines.

modifications in distributed system technology, middleware developers strive to support applications that meet the technical challenges of ubiquitous computing. 24 Computer

We describe the design and implementation of Walter, a key-value store that supports transactions and replicates data across distant sites. A key feature behind Walter is a new property called Parallel Snapshot Isolation (PSI). PSI allows Walter to replicate data asynchronously, while providing strong guarantees within each site. PSI precludes write-write conflicts, so that developers need not worry about conflict-resolution logic. To prevent write-write conflicts and implement PSI, Walter uses two new and simple techniques: preferred sites and counting sets. We use Walter to build a social networking application and port a Twitter-like application.

Building scalable geo-replicated storage backends for web applications by