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    Real-time agreement and fulfilment of SLAs in Cloud Computing environments

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    A Cloud Computing system must readjust its resources by taking into account the demand for its services. This raises the need for designing protocols that provide the individual components of the Cloud architecture with the ability to self-adapt and to reach agreements in order to deal with changes in the services demand. Furthermore, if the Cloud provider has signed a Service Level Agreement (SLA) with the clients of the services that it offers, the appropriate agreement mechanism has to ensure the provision of the service contracted within a specified time. This paper introduces real-time mechanisms for the agreement and fulfilment of SLAs in Cloud Computing environments. On the one hand, it presents a negotiation protocol inspired by the standard WSAgreement used in web services to manage the interactions between the client and the Cloud provider to agree the terms of the SLA of a service. On the other hand, it proposes the application of a real-time argumentation framework for redistributing resources and ensuring the fulfilment of these SLAs during peaks in the service demand.This work is supported by the Spanish government Grants CONSOLIDER-INGENIO 2010 CSD2007-00022, TIN2011-27652-C03-01, TIN2012-36586-C03-01 and TIN2012-36586-C03-03.De La Prieta, F.; Heras Barberá, SM.; Palanca Cámara, J.; Rodríguez, S.; Bajo, J.; Julian Inglada, VJ. (2014). Real-time agreement and fulfilment of SLAs in Cloud Computing environments. 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    A précis of philosophy of computing and information technology

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    The authors recently finished a comprehensive chapter on “Philosophy of Computing and Information Technology” for the forthcoming (fall 2009) Philosophy of Technology and Engineering Sciences (Ed.: A. Meijers), Volume IX in the Elsevier series Handbook of the Philosophy of Science (Eds.: D. Gabbay, P. Thagard and J. Woods). The purpose of the chapter is to review and discuss the main developments, concepts, topics, and contributors in the intersection between philosophy and computing, as well as provide some suggestions on how to structure the many subcategories within what is loosely referred to as philosophy of computing. In this short synopsis, we will give an outline of the kinds of issues raised in this chapter

    Route Planning in Transportation Networks

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    We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while others can deal efficiently with real-time traffic. Journey planning on public transportation systems, although conceptually similar, is a significantly harder problem due to its inherent time-dependent and multicriteria nature. Although exact algorithms are fast enough for interactive queries on metropolitan transit systems, dealing with continent-sized instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation (buses, trains) with unrestricted modes (walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4, previously published by Microsoft Research. This work was mostly done while the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at Microsoft Research Silicon Valle

    On the mechanical effects of poroelastic crystal mush in classical magma chamber models

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    Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Solid Earth 123(11), (2018): 9376-9406. doi: 10.1029/2018JB015985.Improved constraints on the mechanical behavior of magma chambers is essential for understanding volcanic processes; however, the role of crystal mush on the mechanical evolution of magma chambers has not yet been systematically studied. Existing magma chamber models typically consider magma chambers to be isolated melt bodies surrounded by elastic crust. In this study, we develop a physical model to account for the presence and properties of crystal mush in magma chambers and investigate its impact on the mechanical processes during and after injection of new magma. Our model assumes the magma chamber to be a spherical body consisting of a liquid core of fluid magma within a shell of crystal mush that behaves primarily as a poroelastic material. We investigate the characteristics of time‐dependent evolution in the magma chamber, both during and after the injection, and find that quantities such as overpressure and tensile stress continue to evolve after the injection has stopped, a feature that is absent in elastic (mushless) models. The time scales relevant to the postinjection evolution vary from hours to thousands of years, depending on the micromechanical properties of the mush, the viscosity of magma, and chamber size. We compare our poroelastic results to the behavior of a magma chamber with an effectively viscoelastic shell and find that only the poroelastic model displays a time scale dependence on the size of the chamber for any fixed mush volume fraction. This study demonstrates that crystal mush can significantly influence the mechanical behaviors of crustal magmatic reservoirs.We thank James Rice, Tushar Mittal, Chris Huber and Helge Gonnerman for useful discussions in the early stages of this work. S. Adam Soule was supported by National Science Foundation Grant OCE‐1333492. Meghan Jones was supported by the U.S. Department of Defense through the National Defense Science and Engineering Graduate Fellowship (NDSEG) Program. The numerical codes used for computing the results in the work can be found at https://github.com/YangVol/MushyChamber.2019-03-3
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