2,399 research outputs found
Multi-criteria and satisfaction oriented scheduling for hybrid distributed computing infrastructures
International audienceAssembling and simultaneously using different types of distributed computing infrastructures (DCI) like Grids and Clouds is an increasingly common situation. Because infrastructures are characterized by different attributes such as price, performance, trust, greenness, the task scheduling problem becomes more complex and challenging. In this paper we present the design for a fault-tolerant and trust-aware scheduler, which allows to execute Bag-of-Tasks applications on elastic and hybrid DCI, following user-defined scheduling strategies. Our approach, named Promethee scheduler, combines a pull-based scheduler with multi-criteria Promethee decision making algorithm. Because multi-criteria scheduling leads to the multiplication of the possible scheduling strategies, we propose SOFT, a methodology that allows to find the optimal scheduling strategies given a set of application requirements. The validation of this method is performed with a simulator that fully implements the Promethee scheduler and recreates an hybrid DCI environment including Internet Desktop Grid, Cloud and Best Effort Grid based on real failure traces. A set of experiments shows that the Promethee scheduler is able to maximize user satisfaction expressed accordingly to three distinct criteria: price, expected completion time and trust, while maximizing the infrastructure useful employment from the resources owner point of view. Finally, we present an optimization which bounds the computation time of the Promethee algorithm, making realistic the possible integration of the scheduler to a wide range of resource management software
Delivering services by building and running virtual organisations
Non peer reviewedPostprin
Domain-independent exception handling services that increase robustness in open multi-agent systems
Title from cover. "May 2000."Includes bibliographical references (p. 17-23).Mark Klein and Chrysanthos Dellarocas
Secure Cloud-Edge Deployments, with Trust
Assessing the security level of IoT applications to be deployed to
heterogeneous Cloud-Edge infrastructures operated by different providers is a
non-trivial task. In this article, we present a methodology that permits to
express security requirements for IoT applications, as well as infrastructure
security capabilities, in a simple and declarative manner, and to automatically
obtain an explainable assessment of the security level of the possible
application deployments. The methodology also considers the impact of trust
relations among different stakeholders using or managing Cloud-Edge
infrastructures. A lifelike example is used to showcase the prototyped
implementation of the methodology
A Gaussian approximation of the distributed computing process
The authors propose a refinement of the stochastic model describing the dynamics of the Desktop Grid (DG) project with many hosts and many workunits to be performed, originally proposed by Morozov et al. in 2017. The target performance measure is the mean duration of the runtime of the project. To this end, the authors derive an asymptotic expression for the amount of the accumulated work to be done by means of limit theorems for superposed on-off sources that lead to a Gaussian approximation. In more detail, depending on the distribution of active and idle periods, Brownian or fractional Brownian processes are obtained. The authors present the analytic results related to the hitting time of the considered processes (including the case in which the overall amount of work is only known in a probabilistic way), and highlight how the runtime tail distribution could be estimated by simulation. Taking advantage of the properties of Gaussian processes and the Conditional Monte-Carlo (CMC) approach, the authors present a theoretical framework for evaluating the runtime tail distribution
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
Data Grids have been adopted as the platform for scientific communities that
need to share, access, transport, process and manage large data collections
distributed worldwide. They combine high-end computing technologies with
high-performance networking and wide-area storage management techniques. In
this paper, we discuss the key concepts behind Data Grids and compare them with
other data sharing and distribution paradigms such as content delivery
networks, peer-to-peer networks and distributed databases. We then provide
comprehensive taxonomies that cover various aspects of architecture, data
transportation, data replication and resource allocation and scheduling.
Finally, we map the proposed taxonomy to various Data Grid systems not only to
validate the taxonomy but also to identify areas for future exploration.
Through this taxonomy, we aim to categorise existing systems to better
understand their goals and their methodology. This would help evaluate their
applicability for solving similar problems. This taxonomy also provides a "gap
analysis" of this area through which researchers can potentially identify new
issues for investigation. Finally, we hope that the proposed taxonomy and
mapping also helps to provide an easy way for new practitioners to understand
this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
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