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.

Abstract
The Database Management System ( DBMS) used to be a commodity software component, with well known standard interfaces and semantics. However, the performance and reliability expectations being placed on DBMSs have increased the demand for a variety add-ons, that augment the functionality of the database in a wide range of deployment scenarios, offering support for features such as clustering, replication, and self-management, among others. A well known software engineering approach to systems with such requirements is reflection. Unfortunately, standard reflective interfaces in DBMSs are very limited. Some of these limitations may be circumvented by implementing reflective features as a wrapper to the DBMS server. Unfortunately, these solutions comes at the expense of a large development effort and significant performance penalty.

Abstract
Reliable multicast protocols can strongly simplify the design of distributed applications. However it is hard to sustain a high multicast throughput when groups are large and heterogeneous. In an attempt to overcome this limitation, previous work has focused on weakening reliability properties. In this paper we introduce a novel reliability model that exploits semantic knowledge to decide in which specific conditions messages can be purged without compromising application correctness. This model is based on the concept of message obsolescence: A message becomes obsolete when its content or purpose is overwritten by a subsequent message. We show that message obsolescence can be expressed in a generic way and can be used to configure the system to achieve higher multicast throughput.

Abstract

Abstract
Modern I/O applications that run on HPC infrastructures are increasingly becoming read and metadata intensive. However, having multiple applications submitting large amounts of metadata operations can easily saturate the shared parallel file system's metadata resources, leading to overall performance degradation and I/O unfairness. We present PADLL, an application and file system agnostic storage middleware that enables QoS control of data and metadata workflows in HPC storage systems. It adopts ideas from Software-Defined Storage, building data plane stages that mediate and rate limit POSIX requests submitted to the shared file system, and a control plane that holistically coordinates how all I/O workflows are handled. We demonstrate its performance and feasibility under multiple QoS policies using synthetic benchmarks, real-world applications, and traces collected from a production file system. Results show that PADLL can enforce complex storage QoS policies over concurrent metadata-aggressive jobs, ensuring fairness and prioritization.

Abstract