Interoperable Systems: an introduction

This short chapter introduces interoperable systems and attempts to distinguish the principal research strands in this area. It is not intended as a review. Significant review material is integrated with each of the succeeding chapters. It is rather intended to whet the appetite for what follows and to provide some initial conceptual orientation. This book concerns the architecture, modelling and management of interoperable computing systems. Our collective research agenda addresses all aspects of interoperable systems development, including the business and industry requirements and environments for distributed information services

Multimedia big data computing for in-depth event analysis

While the most part of ”big data” systems target text-based analytics, multimedia data, which makes up about 2/3 of internet traffic, provide unprecedented opportunities for understanding and responding to real world situations and challenges. Multimedia Big Data Computing is the new topic that focus on all aspects of distributed computing systems that enable massive scale image and video analytics. During the course of this paper we describe BPEM (Big Picture Event Monitor), a Multimedia Big Data Computing framework that operates over streams of digital photos generated by online communities, and enables monitoring the relationship between real world events and social media user reaction in real-time. As a case example, the paper examines publicly available social media data that relate to the Mobile World Congress 2014 that has been harvested and analyzed using the described system.Peer ReviewedPostprint (author's final draft

DistriX : an implementation of UNIX on transputers

Bibliography: pages 104-110.Two technologies, distributed operating systems and UNIX are very relevant in computing today. Many distributed systems have been produced and many are under development. To a large extent, distributed systems are considered to be the only way to solve the computing needs of the future. UNIX, on the other hand, is becoming widely recognized as the industry standard for operating systems. The transputer, unlike. UNIX and distributed systems is a relatively new innovation. The transputer is a concurrent processing machine based on mathematical principles. Increasingly, the transputer is being used to solve a wide range of problems of a parallel nature. This thesis combines these three aspects in creating a distributed implementation of UNIX on a network of transputers. The design is based on the satellite model. In this model a central controlling processor is surrounded by worker processors, called satellites, in a master/ slave relationship

How robust are distributed systems

A distributed system is made up of large numbers of components operating asynchronously from one another and hence with imcomplete and inaccurate views of one another's state. Load fluctuations are common as new tasks arrive and active tasks terminate. Jointly, these aspects make it nearly impossible to arrive at detailed predictions for a system's behavior. It is important to the successful use of distributed systems in situations in which humans cannot provide the sorts of predictable realtime responsiveness of a computer, that the system be robust. The technology of today can too easily be affected by worn programs or by seemingly trivial mechanisms that, for example, can trigger stock market disasters. Inventors of a technology have an obligation to overcome flaws that can exact a human cost. A set of principles for guiding solutions to distributed computing problems is presented

Distributed Operating Systems

Distributed operating systems have many aspects in common with centralized ones, but they also differ in certain ways. This paper is intended as an introduction to distributed operating systems, and especially to current university research about them. After a discussion of what constitutes a distributed operating system and how it is distinguished from a computer network, various key design issues are discussed. Then several examples of current research projects are examined in some detail, namely, the Cambridge Distributed Computing System, Amoeba, V, and Eden. © 1985, ACM. All rights reserved

Next Generation Middleware Technology for Mobile Computing

Current advances in portable devices, wireless technologies, and distributed systems have created a mobile computing environment that is characterized by a large scale of dynamism. Diversities in network connectivity, platform capability, and resource availability can significantly affect the application performance. Traditional middleware systems are not prepared to offer proper support for addressing the dynamic aspects of mobile systems. Modern distributed applications need a middleware that is capable of adapting to environment changes and that supports the required level of quality of service. This paper represents the experience of several research projects related to next generation middleware systems. We first indicate the major challenges in mobile computing systems and try to identify the main requirements for mobile middleware systems. The different categories of mobile middleware technologies are reviewed and their strength and weakness are analyzed

Hierarchical Parallelisation of Functional Renormalisation Group Calculations -- hp-fRG

The functional renormalisation group (fRG) has evolved into a versatile tool in condensed matter theory for studying important aspects of correlated electron systems. Practical applications of the method often involve a high numerical effort, motivating the question in how far High Performance Computing (HPC) can leverage the approach. In this work we report on a multi-level parallelisation of the underlying computational machinery and show that this can speed up the code by several orders of magnitude. This in turn can extend the applicability of the method to otherwise inaccessible cases. We exploit three levels of parallelisation: Distributed computing by means of Message Passing (MPI), shared-memory computing using OpenMP, and vectorisation by means of SIMD units (single-instruction-multiple-data). Results are provided for two distinct High Performance Computing (HPC) platforms, namely the IBM-based BlueGene/Q system JUQUEEN and an Intel Sandy-Bridge-based development cluster. We discuss how certain issues and obstacles were overcome in the course of adapting the code. Most importantly, we conclude that this vast improvement can actually be accomplished by introducing only moderate changes to the code, such that this strategy may serve as a guideline for other researcher to likewise improve the efficiency of their codes