Massive-scale distributed computing is a challenge at our doorstep. The current exponential growth of data calls for massive-scale capabilities of storage and processing. This is being acknowledged by several major Internet players embracing the cloud computing model and offering first generation distributed tuple stores. Having all started from similar requirements, these systems ended up providing a similar service: A simple tuple store interface, that allows applications to insert, query, and remove individual elements. Further- more, while availability is commonly assumed to be sustained by the massive scale itself, data consistency and freshness is usually severely hindered. By doing so, these services focus on a specific narrow trade-off between consistency, availability, performance, scale, and migration cost, that is much less attractive to common business needs. In this paper we introduce DataDroplets, a novel tuple store that shifts the current trade-off towards the needs of common business users, pro- viding additional consistency guarantees and higher level data process- ing primitives smoothing the migration path for existing applications. We present a detailed comparison between DataDroplets and existing systems regarding their data model, architecture and trade-offs. Prelim- inary results of the system's performance under a realistic workload are also presented.

Publish/subscribe mechanisms for scalable event dissemination are a core component of many distributed systems ranging from EAI middleware to news dissemination in the Internet. Hence, a lot of research has been done on overlay networks for efficient decentralized topic-based routing. Specifically, in gossip-based dissemination, approximating nodes with shared interests in the overlay makes dissemination more efficient. Unfortunately, this usually requires fully disclosing interests to nearby nodes and impacts reliability due to clustering.
In this paper we address this by starting with multiple overlays, one for each topic subscribed, that then separately self-organize to share a large number of physical connections, thereby leading to reduced message traffic and maintenance overhead. This is achieved without a node ever disclosing an interest to another node that doesn’t share it and without impacting the robustness of the overlay. Besides presenting the overlay maintenance protocol, we evaluate it using simulation in order to validate our results.

In this paper we present a computer assisted proof of the correctness of a partial derivative automata construction from a regular expression within the Coq proof assistant. This proof is part of a formalization of Kleene algebra and regular languages in Coq towards their usage in program certification.

Many emerging online data analysis applications require applying continuous query operations such as correlation, aggregation, and filtering to data streams in real time. Distributed stream processing systems allow in-network stream processing to achieve better scalability and quality-of-service (QoS) provision. In this paper, we present Synergy, a novel distributed stream processing middleware that provides automatic sharing-aware component composition capability. Synergy enables efficient reuse of both result streams and processing components, while composing distributed stream processing applications with QoS demands. It provides a set of fully distributed algorithms to discover and evaluate the reusability of available result streams and processing components when instantiating new stream applications. Specifically, Synergy performs QoS impact projection to examine whether the shared processing can cause QoS violations on currently running applications. The QoS impact projection algorithm can handle different types of streams including both regular traffic and bursty traffic. If no existing processing components can be reused, Synergy dynamically deploys new components at strategic locations to satisfy new application requests. We have implemented a prototype of the Synergy middleware and evaluated its performance on both PlanetLab and simulation testbeds. The experimental results show that Synergy can achieve much better resource utilization and QoS provisioning than previously proposed schemes, by judiciously sharing streams and components during application composition.

The process of creating the architecture of a software system results in a documentation, which is recognized as a key artifact for stakeholder communication, early analysis of the system, support for quality attributes and trouble -free maintenance. The problem of software architecture documentation remains to a large extent unsolved; however the past few years, significant advances have been made in the field from research academic and industrial centers. This paper introduces an approach for recording the results that have been achieved hitherto in the field of documenting software architectures, by formatting them in the shape of patterns. We aim at assembling knowledge and experience in the field from industry and academia, with respect to the few issues that the community has reached consensus. Furthermore, by codifying this knowledge and experience in the form of patterns, we hope for a wider dissemination of architectural documentation concepts and practices to them community and thus a further advance of the field.

In [4], Blok and Pigozzi have shown that a deterministic finite au- tomaton can be naturally viewed as a logical matrix. Following this idea, we use a generalisation of the matrix concept to deal with other kind of automata in the same algebraic perspective. We survey some classical concepts of automata theory using tools from algebraic logic. The novelty of this approach is the understand- ing of the classical automata theory within the standard abstract algebraic logic theory.