Hypersonic: Model Analysis and Checking in the Cloud

Context: Modeling tools are traditionally delivered as monolithic desktop applications, optionally extended by plug-ins or special purpose central servers. This delivery model suffers from several drawbacks, ranging from poor scalability to diffcult maintenance and the proliferation of \shelfware”. Objective: In this paper we investigate the conceptual and technical feasibility of a new software architecture for modeling tools, where certain advanced features are factored out of the client and moved towards the Cloud. With this approach we plan to address the above mentioned drawbacks of existing modeling tools.Method: We base our approach on RESTful Web services. Using features implemented in the existing Model Analysis and Checking (MACH) tool, we create a RESTful Web service API offering model analysis facilities. We refer to it as the Hypersonic API. We provide a proof of concept implementation for the Hypersonic API using model clone detection as our example case. We also implement a sample Web application as a client for these Web services. Results: Our initial experiments with Hypersonic demonstrate the viability of our approach. By applying standards such as REST and JSON in combination with Prolog as an implementation language, we are able to transform MACH from a command line tool into the first Web-based model clone detection service with remarkably little effort.<br/

A Practical Study of Self-Stabilization for Prefix-Tree Based Overlay Networks

Service discovery is crucial in the development of fully decentralized computational grids. Among the significant amount of work produced by the convergence of peer-to-peer (P2P) systems and grids, a new kind of overlay networks, based on prefix trees, has emerged. In particular, the Distributed Lexicographic Placement Table (DLPT) approach is a decentralized and dynamic service discovery service. Fault-tolerance within the DLPT approach is achieved through best-effort policies relying on formal self-stabilization results. Self-stabilization means that the tree can become transiently inconsistent, but is guaranteed to autonomously converge to a correct topology after arbitrary crashes, in a finite time. However, during convergence, the tree may not be able to process queries correctly. In this paper, we present some simulation results having several objectives. First, we investigate the interest of self-stabilization for such architectures. Second, we explore, still based on simulation, a simple Time-To-Live policy to avoid useless processing during convergence time

A Practical Study of Self-Stabilization for Prefix-Tree Based Overlay Networks

Service discovery is crucial in the development of fully decentralized computational grids. Among the significant amount of work produced by the convergence of peer-to-peer (P2P) systems and grids, a new kind of overlay networks, based on prefix trees, has emerged. In particular, the Distributed Lexicographic Placement Table (DLPT) approach is a decentralized and dynamic service discovery service. Fault-tolerance within the DLPT approach is achieved through best-effort policies relying on formal self-stabilization results. Self-stabilization means that the tree can become transiently inconsistent, but is guaranteed to autonomously converge to a correct topology after arbitrary crashes, in a finite time. However, during convergence, the tree may not be able to process queries correctly. In this paper, we present some simulation results having several objectives. First, we investigate the interest of self-stabilization for such architectures. Second, we explore, still based on simulation, a simple Time-To-Live policy to avoid useless processing during convergence time