Architecture independent environment for developing engineering software on MIMD computers

Engineers are constantly faced with solving problems of increasing complexity and detail. Multiple Instruction stream Multiple Data stream (MIMD) computers have been developed to overcome the performance limitations of serial computers. The hardware architectures of MIMD computers vary considerably and are much more sophisticated than serial computers. Developing large scale software for a variety of MIMD computers is difficult and expensive. There is a need to provide tools that facilitate programming these machines. First, the issues that must be considered to develop those tools are examined. The two main areas of concern were architecture independence and data management. Architecture independent software facilitates software portability and improves the longevity and utility of the software product. It provides some form of insurance for the investment of time and effort that goes into developing the software. The management of data is a crucial aspect of solving large engineering problems. It must be considered in light of the new hardware organizations that are available. Second, the functional design and implementation of a software environment that facilitates developing architecture independent software for large engineering applications are described. The topics of discussion include: a description of the model that supports the development of architecture independent software; identifying and exploiting concurrency within the application program; data coherence; engineering data base and memory management

Proceedings of the ECSCW'95 Workshop on the Role of Version Control in CSCW Applications

The workshop entitled "The Role of Version Control in Computer Supported Cooperative Work Applications" was held on September 10, 1995 in Stockholm, Sweden in conjunction with the ECSCW'95 conference. Version control, the ability to manage relationships between successive instances of artifacts, organize those instances into meaningful structures, and support navigation and other operations on those structures, is an important problem in CSCW applications. It has long been recognized as a critical issue for inherently cooperative tasks such as software engineering, technical documentation, and authoring. The primary challenge for versioning in these areas is to support opportunistic, open-ended design processes requiring the preservation of historical perspectives in the design process, the reuse of previous designs, and the exploitation of alternative designs. The primary goal of this workshop was to bring together a diverse group of individuals interested in examining the role of versioning in Computer Supported Cooperative Work. Participation was encouraged from members of the research community currently investigating the versioning process in CSCW as well as application designers and developers who are familiar with the real-world requirements for versioning in CSCW. Both groups were represented at the workshop resulting in an exchange of ideas and information that helped to familiarize developers with the most recent research results in the area, and to provide researchers with an updated view of the needs and challenges faced by application developers. In preparing for this workshop, the organizers were able to build upon the results of their previous one entitled "The Workshop on Versioning in Hypertext" held in conjunction with the ECHT'94 conference. The following section of this report contains a summary in which the workshop organizers report the major results of the workshop. The summary is followed by a section that contains the position papers that were accepted to the workshop. The position papers provide more detailed information describing recent research efforts of the workshop participants as well as current challenges that are being encountered in the development of CSCW applications. A list of workshop participants is provided at the end of the report. The organizers would like to thank all of the participants for their contributions which were, of course, vital to the success of the workshop. We would also like to thank the ECSCW'95 conference organizers for providing a forum in which this workshop was possible

Accessing RDF(S) data resources in service-based Grid infrastructures

We describe the results of the RDF(S) activity within the Open Grid Forum (http://www.ogf.org) (OGF) Database Access and Integration Services (DAIS) Working Group (http://forge.gridforum.org/projects/dais-wg) whose objective is to develop standard service-based grid access mechanisms for data expressed in RDF and RDF Schema. We produce two specifications, focused on the provision of SPARQL querying capabilities for accessing RDF data and a set of RDF Schema ontology handling primitives for creating, retrieving, updating, and deleting RDF data. In this paper we present a set of use cases that justify this work and an overview of these specifications, which will enter in editorial process at OGF25. We conclude by outlining the future work that will be made in the context of this standardization process

Living City, A Collaborative Browser-Based Massively Multiplayer Online Game

This work presents the design and implementation of our Browser-based Massively Multiplayer Online Game, Living City, a simulation game fully developed at the University of Messina. Living City is a persistent and real-time digital world, running in the Web browser environment and accessible from users without any client-side installation. Today Massively Multiplayer Online Games attract the attention of Computer Scientists both for their architectural peculiarity and the close interconnection with the social network phenomenon. We will cover these two aspects paying particular attention to some aspects of the project: game balancing (e.g. algorithms behind time and money balancing); business logic (e.g., handling concurrency, cheating avoidance and availability) and, finally, social and psychological aspects involved in the collaboration of players, analyzing their activities and interconnections

Quality measures for ETL processes: from goals to implementation

Extraction transformation loading (ETL) processes play an increasingly important role for the support of modern business operations. These business processes are centred around artifacts with high variability and diverse lifecycles, which correspond to key business entities. The apparent complexity of these activities has been examined through the prism of business process management, mainly focusing on functional requirements and performance optimization. However, the quality dimension has not yet been thoroughly investigated, and there is a need for a more human-centric approach to bring them closer to business-users requirements. In this paper, we take a first step towards this direction by defining a sound model for ETL process quality characteristics and quantitative measures for each characteristic, based on existing literature. Our model shows dependencies among quality characteristics and can provide the basis for subsequent analysis using goal modeling techniques. We showcase the use of goal modeling for ETL process design through a use case, where we employ the use of a goal model that includes quantitative components (i.e., indicators) for evaluation and analysis of alternative design decisions.Peer ReviewedPostprint (author's final draft

Optimistic replication

Data replication is a key technology in distributed data sharing systems, enabling higher availability and performance. This paper surveys optimistic replication algorithms that allow replica contents to diverge in the short term, in order to support concurrent work practices and to tolerate failures in low-quality communication links. The importance of such techniques is increasing as collaboration through wide-area and mobile networks becomes popular. Optimistic replication techniques are different from traditional “pessimistic ” ones. Instead of synchronous replica coordination, an optimistic algorithm propagates changes in the background, discovers conflicts after they happen and reaches agreement on the final contents incrementally. We explore the solution space for optimistic replication algorithms. This paper identifies key challenges facing optimistic replication systems — ordering operations, detecting and resolving conflicts, propagating changes efficiently, and bounding replica divergence — and provides a comprehensive survey of techniques developed for addressing these challenges

Data management in cloud environments: NoSQL and NewSQL data stores

: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the large number and diversity of existing NoSQL and NewSQL solutions, it is difficult to comprehend the domain and even more challenging to choose an appropriate solution for a specific task. Therefore, this paper reviews NoSQL and NewSQL solutions with the objective of: (1) providing a perspective in the field, (2) providing guidance to practitioners and researchers to choose the appropriate data store, and (3) identifying challenges and opportunities in the field. Specifically, the most prominent solutions are compared focusing on data models, querying, scaling, and security related capabilities. Features driving the ability to scale read requests and write requests, or scaling data storage are investigated, in particular partitioning, replication, consistency, and concurrency control. Furthermore, use cases and scenarios in which NoSQL and NewSQL data stores have been used are discussed and the suitability of various solutions for different sets of applications is examined. Consequently, this study has identified challenges in the field, including the immense diversity and inconsistency of terminologies, limited documentation, sparse comparison and benchmarking criteria, and nonexistence of standardized query languages

Analysis domain model for shared virtual environments

The field of shared virtual environments, which also encompasses online games and social 3D environments, has a system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model

High Performance Computing using Infiniband-based clusters

L'abstract è presente nell'allegato / the abstract is in the attachmen

A Game-Theoretic Approach for Runtime Capacity Allocation in MapReduce

Nowadays many companies have available large amounts of raw, unstructured data. Among Big Data enabling technologies, a central place is held by the MapReduce framework and, in particular, by its open source implementation, Apache Hadoop. For cost effectiveness considerations, a common approach entails sharing server clusters among multiple users. The underlying infrastructure should provide every user with a fair share of computational resources, ensuring that Service Level Agreements (SLAs) are met and avoiding wastes. In this paper we consider two mathematical programming problems that model the optimal allocation of computational resources in a Hadoop 2.x cluster with the aim to develop new capacity allocation techniques that guarantee better performance in shared data centers. Our goal is to get a substantial reduction of power consumption while respecting the deadlines stated in the SLAs and avoiding penalties associated with job rejections. The core of this approach is a distributed algorithm for runtime capacity allocation, based on Game Theory models and techniques, that mimics the MapReduce dynamics by means of interacting players, namely the central Resource Manager and Class Managers