The language Java is enjoying a rapid rise in popularity as an application programming language. For many applications an effective provision of database facilities is required. Here we report on a particular approach to providing such facilities, called "orthogonal persistence". Persistence allows data to have lifetimes that vary from transient to (the best approximation we can achieve to) indefinite. It is orthogonal persistence if the available lifetimes are the same for all kinds of data. We aim to show that the programmer productivity gains and possible performance gains make orthogonal persistence a valuable augmentation of Java.

Despite the importance of storage in enterprise computer systems, there are few adequate tools to design and configure a storage system to meet application data requirements efficiently. Storage system design involves choosing the disk arrays to use, setting the configuration options on those arrays, and determining an efficient mapping of application data onto the configured system. This is a complex process because of the multitude of disk array configuration options, and the need to take into account both capacity and potentially contending I/O performance demands when placing the data. Thus, both existing tools and administrators using rules of thumb often generate designs that are of poor quality.This article presents the Disk Array Designer (DAD), which is a tool that can be used both to guide administrators in their design decisions and to automate the design process. DAD uses a generalized best-fit bin packing heuristic with randomization and backtracking to search efficiently through the huge number of possible design choices. It makes decisions using device models that estimate storage system performance. We evaluate DAD's designs based on traces from a variety of database, filesystem, and e-mail workloads. We show that DAD can handle the difficult task of configuring midrange and high-end disk arrays, even with complex real-world workloads. We also show that DAD quickly generates near-optimal storage system designs, improving in both speed and quality over previous tools.

A Federated Array of Bricks is a scalable distributed storage system composed from inexpensive storage bricks. It achieves high reliability with low cost by using erasure coding across the bricks to maintain data reliability in the face of brick failures. Erasure coding generates n encoded blocks from m data blocks (n > m) and permits the data blocks to be reconstructed from any m of these encoded blocks. We present a new fully decentralized erasurecoding algorithm for an asynchronous distributed system. Our algorithm provides fully linearizable read-write access to erasure-coded data and supports concurrent I/O controllers that may crash and recover. Our algorithm relies on a novel quorum construction where any two quorums intersect in m processes.

In this paper, we introduce SoCaM, a framework for supporting case management in social networking environments. SoCaM makes case entities (cases, processes, artifacts, etc.) first class, active elements in the social network and connects them to people. It enables social, collaborative and flexible definition, adaptation and enactment of case processes among people. It also offers mechanisms for capturing and formalizing feedback, from interactions in the social network, into the case, process and artifact definitions. We report on the implementation and a case management scenario for sales processes in the enterprise.

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