94,613 research outputs found

    Systematic composition of distributed objects: Processes and sessions

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    We consider a system with the infrastructure for the creation and interconnection of large numbers of distributed persistent objects. This system is exemplified by the Internet: potentially, every appliance and document on the Internet has both persistent state and the ability to interact with large numbers of other appliances and documents on the Internet. This paper elucidates the characteristics of such a system, and proposes the compositional requirements of its corresponding infrastructure. We explore the problems of specifying, composing, reasoning about and implementing applications in such a system. A specific concern of our research is developing the infrastructure to support structuring distributed applications by using sequential, choice and parallel composition, in the anarchic environment where application compositions may be unforeseeable and interactions may be unknown prior to actually occurring. The structuring concepts discussed are relevant to a wide range of distributed applications; our implementation is illustrated with collaborative Java processes interacting over the Internet, but the methodology provided can be applied independent of specific platforms

    Genetic Programming for Smart Phone Personalisation

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    Personalisation in smart phones requires adaptability to dynamic context based on user mobility, application usage and sensor inputs. Current personalisation approaches, which rely on static logic that is developed a priori, do not provide sufficient adaptability to dynamic and unexpected context. This paper proposes genetic programming (GP), which can evolve program logic in realtime, as an online learning method to deal with the highly dynamic context in smart phone personalisation. We introduce the concept of collaborative smart phone personalisation through the GP Island Model, in order to exploit shared context among co-located phone users and reduce convergence time. We implement these concepts on real smartphones to demonstrate the capability of personalisation through GP and to explore the benefits of the Island Model. Our empirical evaluations on two example applications confirm that the Island Model can reduce convergence time by up to two-thirds over standalone GP personalisation.Comment: 43 pages, 11 figure

    About Parallel Programming: Paradigms, Parallel Execution and Collaborative Systems

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    In the last years, there were made efforts for delineation of a stabile and unitary frame, where the problems of logical parallel processing must find solutions at least at the level of imperative languages. The results obtained by now are not at the level of the made efforts. This paper wants to be a little contribution at these efforts. We propose an overview in parallel programming, parallel execution and collaborative systems.Parallel Programming, Parallel Execution, Collaborative systems, Collaborative parallel execution

    On sharing and synchronizing groupware calendars under android platform

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    (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Sharing a calendar of tasks and events is a cornerstone in collaborative group work. Indeed, the individual work of the members of the group as well as the group work as a whole need the calendar to guide their activity and to meet the deadlines, milestones, deliverables of a project, etc. Additionally the members of the group should be able to work both offline and online, which arises when members of the group use smartphones and can eventually run out of Internet connection from time to time, or simply want to develop some activities locally. In the former case, they should have access to the calendar locally, while in the later case they should access the calendar online, shared by all members of the group. In both cases they should be able to see eventually the same information, namely the local calendars of the members should be synchronized with the group calendar. For the case of smartphones under Android system, one solution could be using the Google calendar, however, that is not easily tailorable to collaborative group work. In this paper we present an analysis, design and implementation of group work calendar that meets several requirements such as 1) sharing among all of members of the group, 2) synchronization among local calendars of members and global group calendar, 3) conflict resolution through a voting system, 4) awareness of changes in the entries (tasks, members, events, etc.) of the calendar and 5) all these requirements under proper privacy, confidentiality and security mechanisms. Moreover, we extend the sharing of calendars among different groups, a situation which often arises in enterprises when different groups need to be aware of other projects' development, or, when some members participate in more than one project at the same time.Peer ReviewedPostprint (author's final draft

    A parallel grid-based implementation for real time processing of event log data in collaborative applications

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    Collaborative applications usually register user interaction in the form of semi-structured plain text event log data. Extracting and structuring of data is a prerequisite for later key processes such as the analysis of interactions, assessment of group activity, or the provision of awareness and feedback. Yet, in real situations of online collaborative activity, the processing of log data is usually done offline since structuring event log data is, in general, a computationally costly process and the amount of log data tends to be very large. Techniques to speed and scale up the structuring and processing of log data with minimal impact on the performance of the collaborative application are thus desirable to be able to process log data in real time. In this paper, we present a parallel grid-based implementation for processing in real time the event log data generated in collaborative applications. Our results show the feasibility of using grid middleware to speed and scale up the process of structuring and processing semi-structured event log data. The Grid prototype follows the Master-Worker (MW) paradigm. It is implemented using the Globus Toolkit (GT) and is tested on the Planetlab platform
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