Distributed Environment

Multimedia data is generally stored in compressed form in order to efficiently utilize the available storage facilities. Access to archives is dependent on our ability to browse compressed multimedia information-retrieval and tracking from coded video databases. In this paper, a novel visual search engine for video retrieval and tracking from compressed multimedia databases is proposed. The goal of the project is the implementation of a visual browser that operates in a distributed environment where users initiate video searches and retrieve relevant video information simultaneously from multiple video archives. Being presented with a query in the form of template images of objects, the system operates on the compressed video to find the images or video sequences where those objects are present and their positions in the image. Upon user's request, the system will decompress and display only the video sequences of interest.

Previous research [1, 2] has indicated that pair programming is better than individual programming when the pairs are physically colocated. However, important questions arise: How effective is pair programming if the pairs are not physically next to each other? What if the programmers are geographically distributed? An experiment was conducted to compare the different working arrangements of student teams developing object-oriented software. The teams were both colocated and in distributed environments; ...

In this article, we present MADIK, a Multi-Agent Digital Investigation ToolKit to help experts during the forensic examination process. MADIK uses a four layer multi-agent architecture, as a metaphor to the organizational hierarchy levels: strategic, tactical, operational and specialist. The proposed architecture and tool was developed under a blackboard approach, implemented with Java Agent DEvelopment Framework - JADE, using Java Expert System Shell - JESS as an inference engine. We have done some experiments with MADIK using real data, on stand alone and distributed environments with encouraging results.

Global companies that experimented extensive waterfall phased plans are trying to improve their existing processes to expedite team engagement. SCRUM has become an acceptable path to follow for those companies because it comprises project management as part of its practices. SCRUM has been used with the objective of simplifying project control through simple processes, easy to update documentation and higher team iteration over exhaustive documentation. Instead of investing team effort on producing static documentation, SCRUM proposes to focus on team continuous improvement aiming to add value to business processes. The purpose of this industry report is to describe two projects that experimented SCRUM practices within a globally distributed company. This company has development centers across North America, South America and Asia. This report covers challenges faced by the project teams, strengths and practical recommendations of using SCRUM in a globally distributed environment.

The Extreme Programming software development methodology relies heavily on the co- location of the team members. Outsourcing and teleworking is becoming more common nowa- days, meaning that XP practitioners need to adapt their daily XP practices for a distributed setting. In most cases the distributed teams use (existing) tools that is a direct translation of a practice without thinking about

Abstract. Data management solutions in distributed environments have been continuously evolving during the last years to answer users ’ needs and face new technology challenges. To help matters, ontologies have been used as a support for the techniques of managing data. For instance, ontologies may be used to describe the semantics of data at different sources, helping to overcome problems of semantic interoperability and data heterogeneity, and thus assisting schema integration and query answering over the distributed data sources. The goal of this paper is to highlight the use of ontologies in order to enhance data management issues in distributed environments. To this end, we describe a set of ongoing works which have been developed in our research.

The first wave of agent implementation toolkits focussed mostly on providing APIs for agent com- munication. We believe that new toolkits should focus on the public dissemination of complete agent architectures that provide significant value over building software agents from scratch. DECAF (Distributed, Environment Centered Agent Framework) is a software toolkit for the rapid design, development, and execution of ''intelligent''

Page 1. Evolutionary Migration of Legacy Systems to an Object-Based Distributed EnvironmentMiguel A. Serrano * , Carlos Montes de Oca¦, Doris L. Carver * * Department of Computer Science Louisiana State University Baton Rouge, Louisiana, 70803. ...

This article reports on a two-year ethnographic study of learners participating in multi-site, graduate-level education classes. Classes sometimes met face-to-face in the same physical location; at other times part of the class met physically elsewhere. Yet all were linked through the virtual space. Ethnographic analysis of four data types explored how the instructor and students were able to interact through videoconferencing technologies. Most of the interaction occurred between the local and distance learners by way of cultural guides, local students assigned to host a distance learner through Google Video chat. The distance learners were able to receive real-time attention from the instructor and were able to share differing perspectives that contributed to increased satisfaction in the course. These interactions allowed for a dynamic collaborative effort among a diverse set of actors in the field of education.

This paper describes the architecture for the distributed CAPS system (DCAPS). The system accomplishes distributed software prototyping with legacy module reuse. Prototype System Description Language (PSL), the prototyping language, is used to describe real-time software in the DCAPS system. PSDL specifies not only real-time constraints, but also the connection and interaction among software components. Automatic generation of software wrappers and glue is applied for the normalization of data transfer between legacy systems. Implementation of the DCAPS communication layer is based on the JavaSpacesTM library. DCAPS supports collaborative prototype design in a distributed environment

The performance of a distributed system is affected by the various functions of its components. The interaction between components such as network nodes, computer systems and system programs is examined with special interest accorded to its effect on system reliability. At affordable time and space costs, the analytic hierarchy process (AHP) is used to determine how the reliability of a distributed system may be controlled by appropriately assigning weights to its components. Illustrative case studies, that display the system structure, the assignment of weights and the AHP handling are presented.

Grid computing infrastructures are inherently dynamic and unpredictable environments shared by many users. Grid schedulers aim to make efficient use of grid resources while providing the best possible performance to the grid applications and satisfying the associated performance and policy constraints. Additionally, in commercial grid settings, where the grid resource brokering becomes an increasingly important part of grid scheduling, it is necessary to minimise the cost of application execution on the behalf of the grid users, while ensuring that the applications meet their QoS constraints. Efficient resource allocation could in turn also allow the resource broker to maximise its profit by minimising the number of resources procured. Scheduling in such a large-scale, dynamic and distributed environment is a complex undertaking. In this paper, we propose an approach to grid scheduling which abstracts over the details of individual applications, focusing instead on the global cost optimisation problem and the scheduling of the entire grid workload. Our model places particular emphasis on the stochastic and unpredictable nature of the grid, leading to a more accurate reflection of the state of the grid and hence more efficient and accurate scheduling decisions