7,530 research outputs found
Towards trusted volunteer grid environments
Intensive experiences show and confirm that grid environments can be
considered as the most promising way to solve several kinds of problems
relating either to cooperative work especially where involved collaborators are
dispersed geographically or to some very greedy applications which require
enough power of computing or/and storage. Such environments can be classified
into two categories; first, dedicated grids where the federated computers are
solely devoted to a specific work through its end. Second, Volunteer grids
where federated computers are not completely devoted to a specific work but
instead they can be randomly and intermittently used, at the same time, for any
other purpose or they can be connected or disconnected at will by their owners
without any prior notification. Each category of grids includes surely several
advantages and disadvantages; nevertheless, we think that volunteer grids are
very promising and more convenient especially to build a general multipurpose
distributed scalable environment. Unfortunately, the big challenge of such
environments is, however, security and trust. Indeed, owing to the fact that
every federated computer in such an environment can randomly be used at the
same time by several users or can be disconnected suddenly, several security
problems will automatically arise. In this paper, we propose a novel solution
based on identity federation, agent technology and the dynamic enforcement of
access control policies that lead to the design and implementation of trusted
volunteer grid environments.Comment: 9 Pages, IJCNC Journal 201
Investigating grid computing technologies for use with commercial simulation packages
As simulation experimentation in industry become more computationally demanding, grid computing can be seen as a promising technology that has the potential to bind together the computational resources needed to quickly execute such simulations. To investigate how this might be possible, this paper reviews the grid technologies that can be used together with commercial-off-the-shelf simulation packages (CSPs) used in industry. The paper identifies two specific forms of grid computing (Public Resource Computing and Enterprise-wide Desktop Grid Computing) and the middleware associated with them (BOINC and Condor) as being suitable for grid-enabling existing CSPs. It further proposes three different CSP-grid integration approaches and identifies one of them to be the most appropriate. It is hoped that this research will encourage simulation practitioners to consider grid computing as a technologically viable means of executing CSP-based experiments faster
Personal Volunteer Computing
We propose personal volunteer computing, a novel paradigm to encourage
technical solutions that leverage personal devices, such as smartphones and
laptops, for personal applications that require significant computations, such
as animation rendering and image processing. The paradigm requires no
investment in additional hardware, relying instead on devices that are already
owned by users and their community, and favours simple tools that can be
implemented part-time by a single developer. We show that samples of personal
devices of today are competitive with a top-of-the-line laptop from two years
ago. We also propose new directions to extend the paradigm
MOON: MapReduce On Opportunistic eNvironments
Abstract—MapReduce offers a flexible programming model for processing and generating large data sets on dedicated resources, where only a small fraction of such resources are every unavailable at any given time. In contrast, when MapReduce is run on volunteer computing systems, which opportunistically harness idle desktop computers via frameworks like Condor, it results in poor performance due to the volatility of the resources, in particular, the high rate of node unavailability. Specifically, the data and task replication scheme adopted by existing MapReduce implementations is woefully inadequate for resources with high unavailability. To address this, we propose MOON, short for MapReduce On Opportunistic eNvironments. MOON extends Hadoop, an open-source implementation of MapReduce, with adaptive task and data scheduling algorithms in order to offer reliable MapReduce services on a hybrid resource architecture, where volunteer computing systems are supplemented by a small set of dedicated nodes. The adaptive task and data scheduling algorithms in MOON distinguish between (1) different types of MapReduce data and (2) different types of node outages in order to strategically place tasks and data on both volatile and dedicated nodes. Our tests demonstrate that MOON can deliver a 3-fold performance improvement to Hadoop in volatile, volunteer computing environments
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Leveraging simulation practice in industry through use of desktop grid middleware
This chapter focuses on the collaborative use of computing resources to support decision making in industry. Through the use of middleware for desktop grid computing, the idle CPU cycles available on existing computing resources can be harvested and used for speeding-up the execution of applications that have “non-trivial” processing requirements. This chapter focuses on the desktop grid middleware BOINC and Condor, and discusses the integration of commercial simulation software together with free-to-download grid middleware so as to offer competitive advantage to organizations that opt for this technology. It is expected that the low-intervention integration approach presented in this chapter (meaning no changes to source code required) will appeal to both simulation practitioners (as simulations can be executed faster, which in turn would mean that more replications and optimization is possible in the same amount of time) and the management (as it can potentially increase the return on investment on existing resources)
Pando: Personal Volunteer Computing in Browsers
The large penetration and continued growth in ownership of personal
electronic devices represents a freely available and largely untapped source of
computing power. To leverage those, we present Pando, a new volunteer computing
tool based on a declarative concurrent programming model and implemented using
JavaScript, WebRTC, and WebSockets. This tool enables a dynamically varying
number of failure-prone personal devices contributed by volunteers to
parallelize the application of a function on a stream of values, by using the
devices' browsers. We show that Pando can provide throughput improvements
compared to a single personal device, on a variety of compute-bound
applications including animation rendering and image processing. We also show
the flexibility of our approach by deploying Pando on personal devices
connected over a local network, on Grid5000, a French-wide computing grid in a
virtual private network, and seven PlanetLab nodes distributed in a wide area
network over Europe.Comment: 14 pages, 12 figures, 2 table
Grid-enabling FIRST: Speeding up simulation applications using WinGrid
The vision of grid computing is to make computational power, storage capacity, data and applications available to users as readily as electricity and other utilities. Grid infrastructures and applications have traditionally been geared towards dedicated, centralized, high performance clusters running on UNIX flavour operating systems (commonly referred to as cluster-based grid computing). This can be contrasted with desktop-based grid computing which refers to the aggregation of non-dedicated, de-centralized, commodity PCs connected through a network and running (mostly) the Microsoft Windowstrade operating system. Large scale adoption of such Windowstrade-based grid infrastructure may be facilitated via grid-enabling existing Windows applications. This paper presents the WinGridtrade approach to grid enabling existing Windowstrade based commercial-off-the-shelf (COTS) simulation packages (CSPs). Through the use of a case study developed in conjunction with Ford Motor Company, the paper demonstrates how experimentation with the CSP Witnesstrade and FIRST can achieve a linear speedup when WinGridtrade is used to harness idle PC computing resources. This, combined with the lessons learned from the case study, has encouraged us to develop the Web service extensions to WinGridtrade. It is hoped that this would facilitate wider acceptance of WinGridtrade among enterprises having stringent security policies in place
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