Using real options to select stable Middleware-induced software architectures

The requirements that force decisions towards building distributed system architectures are usually of a non-functional nature. Scalability, openness, heterogeneity, and fault-tolerance are examples of such non-functional requirements. The current trend is to build distributed systems with middleware, which provide the application developer with primitives for managing the complexity of distribution, system resources, and for realising many of the non-functional requirements. As non-functional requirements evolve, the `coupling' between the middleware and architecture becomes the focal point for understanding the stability of the distributed software system architecture in the face of change. It is hypothesised that the choice of a stable distributed software architecture depends on the choice of the underlying middleware and its flexibility in responding to future changes in non-functional requirements. Drawing on a case study that adequately represents a medium-size component-based distributed architecture, it is reported how a likely future change in scalability could impact the architectural structure of two versions, each induced with a distinct middleware: one with CORBA and the other with J2EE. An option-based model is derived to value the flexibility of the induced-architectures and to guide the selection. The hypothesis is verified to be true for the given change. The paper concludes with some observations that could stimulate future research in the area of relating requirements to software architectures

Implementing Session Centered Calculi

Recently, specific attention has been devoted to the development of service oriented process calculi. Besides the foundational aspects, it is also interesting to have prototype implementations for them in order to assess usability and to minimize the gap between theory and practice. Typically, these implementations are done in Java taking advantage of its mechanisms supporting network applications. However, most of the recurrent features of service oriented applications are re-implemented from scratch. In this paper we show how to implement a service oriented calculus, CaSPiS (Calculus of Services with Pipelines and Sessions) using the Java framework IMC, where recurrent mechanisms for network applications are already provided. By using the session oriented and pattern matching communication mechanisms provided by IMC, it is relatively simple to implement in Java all CaSPiS abstractions and thus to easily write the implementation in Java of a CaSPiS process

Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed

Generic Distribution Support for Programming Systems

This dissertation provides constructive proof, through the implementation of a middleware, that distribution transparency is practical, generic, and extensible. Fault tolerant distributed services can be developed by using the failure detection abilities of the middleware. By generic we mean that the middleware can be used for many different programming languages and paradigms. Distribution for each kind of language entity is done in terms of consistency protocols, which guarantee that the semantics of the entities are preserved in a distributed setting. The middleware allows new consistency protocols to be added easily. The efficiency of the middleware and the ease of integration are shown by coupling the middleware to a programming system, which encompasses the object oriented, the functional, and the concurrent-declarative programming paradigms. Our measurements show that the distribution middleware is competitive with the most popular distributed programming systems (JavaRMI, .NET, IBM CORBA)

1st INCF Workshop on Sustainability of Neuroscience Databases

The goal of the workshop was to discuss issues related to the sustainability of neuroscience databases, identify problems and propose solutions, and formulate recommendations to the INCF. The report summarizes the discussions of invited participants from the neuroinformatics community as well as from other disciplines where sustainability issues have already been approached. The recommendations for the INCF involve rating, ranking, and supporting database sustainability