Showing papers on "Cloud computing published in 2006"

The Computational and Storage Potential of Volunteer Computing

Abstract: "Volunteer computing" uses Internet-connected computers, volunteered by their owners, as a source of computing power and storage. This paper studies the potential capacity of volunteer computing. We analyzed measurements of over 330,000 hosts participating in a volunteer computing project. These measurements include processing power, memory, disk space, network throughput, host availability, userspecified limits on resource usage, and host churn. We show that volunteer computing can support applications that are significantly more data-intensive, or have larger memory and storage requirements, than those in current projects.

Marketplace for cloud services resources

Abstract: The claimed subject matter provides systems and/or methods that facilitate dynamically allocating resources (e.g., hardware, software, . . . ) supported by a third party service provider. The third party service provider can support any number of services that can be concurrently requested by several clients without user perception of degraded computing performance as compared to conventional systems/techniques due to improved connectivity and mitigated latencies. An interface component can receive a request from a client device. Further, a dynamic allocation component can apportion resources (e.g., hardware resources) supported by the third party service provider to process and respond to the request based at least in part upon subscription data. Moreover, a user state evaluator can determine a state associated with a user and/or the client device; the state can be utilized by the dynamic allocation component to tailor resource allocation.

Hardware architecture for cloud services

Abstract: The claimed subject matter provides systems and/or methods that facilitate dynamically allocating resources (e.g., hardware, software, . . . ) supported by a third party service provider. The third party service provider can support any number of services that can be concurrently requested by several clients without user perception of degraded computing performance as compared to conventional systems/techniques due to improved connectivity and mitigated latencies. An interface component can receive a request from a client device. Further, a dynamic allocation component can apportion resources (e.g., hardware resources) supported by the third party service provider to process and respond to the request based at least in part upon subscription data. Moreover, a user state evaluator can determine a state associated with a user and/or the client device; the state can be utilized by the dynamic allocation component to tailor resource allocation.

Data security in an off-premise environment

Abstract: A system that enables a cloud-based data repository to function as a secure ‘drop-box’ for data that corresponds to a user is provided. The ‘drop box’ can be facilitated through the use of cryptographic keying technologies. For instance, data that is ‘dropped’ by or on behalf of a particular user can be encrypted using a public key that corresponds to a user-specific private key. Thus, although the data resides within the large pool of ‘cloud-based’ data, it is protected since it can only be decrypted by using the private key, which is kept secret. The innovation can further facilitate user-centric secure storage by partitioning the cloud-based repository into multiple partitions, each of which corresponds to specific indexing criteria.

Remote management of resource license

Abstract: A user-centric or identity-centric resource licensing system that manages access to ‘cloud-based’ resources (e.g., applications and services) is provided. A ‘cloud’ refers to a collection of resources (e.g., hardware and/or software) provided and maintained by an off-site or off-premise party (e.g., third party), wherein the collection of resources can be accessed by an identified user via a network. In accordance with the user-centric licensing model, the resource license (and subscription) rights can migrate with a user without regard to physical location, device used, or other contextual factors (e.g., activity engaged). Effectively, the rights are mapped (and tracked) as a function of a user identity, which can be a core identity or an identity based upon activity engaged, role, capacity, etc.

Resource standardization in an off-premise environment

Abstract: A computing paradigm where information can be aggregated from multiple services/programs within a ‘cloud-based’ environment is provided. Thus, the system can provide a uniform interface that can combine computational tasks across the multiple services/programs. Thus, the innovation takes advantage of the computing device being a ‘thin client’ which affords greater user comfort to a user without sacrificing data processing capabilities. Accordingly, the mechanisms are disclosed that standardize and/or normalize data across the resources within the cloud.

Off-premise encryption of data storage

Abstract: A system that enables a cloud-based data repository to function as a secure ‘drop-box’ for data that corresponds to a user is provided. The ‘drop box’ can be facilitated through the use of cryptographic keying technologies. For instance, data that is ‘dropped’ by or on behalf of a particular user can be encrypted using a public key that corresponds to a user-specific private key. Thus, although the data resides within the large pool of ‘cloud-based’ data, it is protected since it can only be decrypted by using the private key, which is kept secret. The innovation can further facilitate user-centric secure storage by partitioning the cloud-based repository into multiple partitions, each of which corresponds to specific indexing criteria.

Objective Assessment of the Information Content of Visible and Infrared Radiance Measurements for Cloud Microphysical Property Retrievals over the Global Oceans. Part I: Liquid Clouds

Abstract: The importance of accurately representing the role of clouds in climate change studies has become increasingly apparent in recent years, leading to a substantial increase in the number of satellite sensors and associated algorithms that are devoted to measuring the global distribution of cloud properties. The physics governing the radiative transfer through clouds is well understood, but the impact of uncertainties in algorithm assumptions and the true information content of the measurements in the inverse retrieval problem are generally not as clear, making it difficult to determine the best product to adopt for any particular application. This paper applies information theory to objectively analyze the problem of liquid cloud retrievals from an observing system modeled after the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument currently operating on the Aqua and Terra platforms. It is found that four diagnostics—the retrieval error covariance, the information content, the number of degrees of freedom for signal, and the effective rank of the problem—provide a rigorous test of an observing system. Based on these diagnostics, the combination of the 0.64- and 1.64-m channels during the daytime and the 3.75- and 11.0-m channels at night provides the most information for retrieving the properties of the wide variety of liquid clouds modeled. With an eye toward developing a coherent representation of the global distribution of cloud microphysical and radiative properties, these four channels may be integrated into a suitable multichannel inversion methodology such as the optimal estimation or Bayesian techniques to provide a common framework for cloud retrievals under varying conditions. The expected resolution of the observing system for such liquid cloud microphysical property retrievals over a wide variety of liquid cloud is also explored.

Cloud-based access control list

Abstract: A system that can assist users to manage a personal active directory for all of their information maintained within a cloud-based environment is provided. The identity of a client that accesses data is monitored and recorded in a log. In turn, this information can be made available to the owner of the information in order to develop a desired access control list (ACL). Additionally, the system can employ a heuristic component that can automatically establish the ACL on the owner's behalf. As well, the system can track how information is being accessed (or attempted to be accessed) by other people therefore, giving the owner of the information the opportunity to restrict or allow access based upon any number of recorded factors (e.g., identity, context).

Method and system of social networking through a cloud

Abstract: A method of social networking is disclosed. The method displays a user name on a web page. Further, the method receives an input that selects the user name. The method displays a display cloud, for the user name that is selected, that illustrates at least a subset of a personal cloud of the user associated with the user name. Furthermore, multi-level tagging for content can be used in order to generate tag clouds.

Secure service computation

Abstract: Systems and methods for managing cloud service applications are provided In particular, a security component can regulate such applications to prevent undesirable behavior In one instance, applications can be restricted to use of designated network resources to thereby contain application activities Additionally or alternatively, the applications can be monitored and prohibited from executing malicious code such as that associated with a virus, worm and/or Trojan horse, among other things

CompuP2P: An Architecture for Internet Computing Using Peer-to-Peer Networks

Abstract: Internet computing is emerging as an important new distributed computing paradigm in which resource intensive computing is integrated over Internet-scale networks. Over these large networks, different users and organizations share their computing resources, and computations take place in a distributed fashion. In such an environment, a framework is needed in which the resource providers are given incentives to share their resources. CompuP2P is a lightweight architecture for enabling Internet computing. It uses peer-to-peer networks for sharing of computing resources. CompuP2P create dynamic markets of network accessible computing resources, such as processing power, memory storage, disk space, etc., in a completely distributed, scalable, and fault-tolerant manner. This paper discusses the system architecture, functionality, and applications of the proposed CompuP2P architecture. We have implemented a Java-based prototype, and our results show that the system is light-weight and can provide almost a perfect speedup for applications that contain several independent compute-intensive tasks

Introduction to MODIS Cloud Products

Abstract: The Earth’s radiative energy balance and hydrological cycle are fundamentally coupled with the distribution and properties of clouds. Therefore, the ability to remotely infer cloud properties and their variation in space and time is crucial for establishing climatologies as a reference for validation of present-day climate models and in assessing future climate change. Remote cloud observations also provide data sets useful for testing and improving cloud model physics, and for assimilation into numerical weather prediction models.

Rich index to cloud-based resources

Abstract: The innovation enables generation of an index of cloud-based resources (e.g., data, services, applications). The index can be used to retrieve a subset of the cloud-based resources by analyzing a user-generated or standing query. ‘Identity’ and contextual factors can be incorporated to enable rich indexing as well as subsequent retrieval of meaningful resources. The cloud-based resources can be indexed and/or searched in accordance with diverse criteria including, but not limited to, type, size, data created, date modified, author core identity, object size, etc. As well, the innovation can provide for dynamically indexing and/or searching resources in accordance with current contextual factors including, but not limited to, author current acting capacity (e.g., current identity), current engaged activity of a user, location, time, date, etc. All of these criteria can facilitate indexing and categorizing of the resources for later retrieval and rendering via a rich index view.

The effects of climate change on the long-term conservation of Fagus grandifolia var. mexicana, an important species of the Cloud Forest in Eastern Mexico

Abstract: We examined the effects of climate change on the future conservation and distribution patterns of the cloud forests in eastern Mexico, by using as a species model to Fagus grandifolia Ehr. var. mexicana (Martinez) Little which is mainly located in this vegetation type, at the Sierra Madre Oriental. This species was selected because it is restricted to the cloud forest, where it is a dominant element and has not been considered for protection in any national or international law. It is probably threatened due to the fact that it plays an important social role as a source of food and furnishing. We used a floristic database and a bioclimatic modeling approach including 19 climatic parameters, in order to obtain the current potential distribution pattern of the species. Currently, its potential distribution pattern shows that it is distributed in six different Mexican Priority Regions for Conservation. In addition, we also selected a future climate scenario, on the basis of some climate changes predictions already proposed. The scenario proposed is characterized by +2 °C and −20% rainfall in the region. Under this predicted climatic condition, we found a drastic distribution contraction of the species, in which most of the remaining populations will inhabit restricted areas located outside the boundaries of the surrounding reserves. Consequently, our results highlight the importance of considering the effects of possible future climate changes on the selection of conservation areas and the urgency to conserve some remaining patches of existing cloud forests. Accordingly, we believe that our bioclimatic modeling approach represents a useful tool to undertake decisions concerning the definition of protected areas, once the current potential distribution pattern of some selected species is known.

Real-time realistic illumination and shading of stratiform clouds

Abstract: Realistic rendering of clouds involves solving the complex interaction of light within the cloud and with its environment. Interactive methods achieve efficient cloud rendering by ignoring several lighting effects. However, these effects are visually important, and removing them strongly reduces realism. We present a novel approach for capturing the important effects of multiple anisotropic Mie scattering within cloud layers (i.e., stratiform clouds), and the inter-reflections between the ground and the cloud base under sun and sky illumination. Our model maps well to graphics hardware, enabling the real-time rendering of animated cloud skies over landscapes.

Combined observational and modeling based study of the aerosol indirect effect

Abstract: The indirect effect of aerosols via liquid clouds is investigated by comparing aerosol and cloud characteristics from the Global Climate Model CAM-Oslo to those observed by the MODIS instrument onboard the TERRA and AQUA satellites http://modis.gsfc.nasa.gov). The comparison is carried out for 15 selected regions ranging from remote and clean to densely populated and polluted. For each region, the regression coefficient and correlation coefficient for the following parameters are calculated: Aerosol Optical Depth vs. Liquid Cloud Optical Thickness, Aerosol Optical Depth vs. Liquid Cloud Droplet Effective Radius and Aerosol Optical Depth vs. Cloud Liquid Water Path. Modeled and observed correlation coefficients and regression coefficients are then compared for a 3-year period starting in January 2001. Additionally, global maps for a number of aerosol and cloud parameters crucial for the understanding of the aerosol indirect effect are compared for the same period of time. Significant differences are found between MODIS and CAM-Oslo both in the regional and global comparison. However, both the model and the observations show a positive correlation between Aerosol Optical Depth and Cloud Optical Depth in practically all regions and for all seasons, in agreement with the current understanding of aerosol-cloud interactions. The correlation between Aerosol Optical Depth and Liquid Cloud Droplet Effective Radius is variable both in the model and the observations. However, the model reports the expected negative correlation more often than the MODIS data. Aerosol Optical Depth is overall positively correlated to Cloud Liquid Water Path both in the model and the observations, with a few regional exceptions.

Neural network application for cloud detection in SPOT VEGETATION images

Abstract: SPOT VEGETATION is a recent sensor at 1 km resolution for land surface studies. Cloud detection based on this sensor is complicated by the absence of a thermal band. An artificial neural network was thus trained for the cloud detection on atmospherically corrected S1 daily data and on top of the atmosphere reflectance P data, from the SPOT VEGETATION system. It consists of a multi‐layer perceptron with one hidden sigmoid layer, trained with the Levenberg–Marquardt back‐propagation algorithm and generalized by the Bayesian regularization. Two neural networks allowed optimal cloud detections to be obtained. The first used all four bands of S1 data with 13 hidden nodes, and the second employed all four bands of P data with 11 hidden nodes. The multiple‐layer perceptrons lead to a cloud detection accuracy of 98.0% and 97.6% for S1 and P data, respectively, when trained to map three predefined values that classify cloud, water and land. The network was further evaluated using three SPOT VEGETATION images taken...

Cloud base heights retrieved during night‐time conditions with MODIS data

Abstract: The capability to retrieve cloud base heights was developed under the US National Polar‐orbiting Operational Environmental Satellite System (NPOESS) programme as one of 27 data products to be created from data collected by the Visible Infrared Imager Radiometer Suite (VIIRS). First launch of the VIIRS sensor, which is the high‐resolution Earth imager of the NPOESS programme, comes on National Aeronautics & Space Administration's (NASA) NPOESS Preparatory Project (NPP). In preparation for this launch, extensive testing of the VIIRS cloud algorithms was completed to verify that product performance will satisfy system requirements before the cloud algorithms were hosted in the NPOESS ground processing centre. The approach taken to retrieve cloud base height converts cloud optical properties into a geometric thickness which is then subtracted from the cloud top height. Performance of the cloud base height algorithms has been verified recently using MODIS data, together with temporarily and spatial coincident ...

The Heidelberg iterative cloud retrieval utilities (HICRU) and its application to GOME data

Abstract: Information about clouds, in particular the accurate identification of cloud free pixels, is crucial for the retrieval of tropospheric vertical column densities from space. The Heidelberg Iterative Cloud Retrieval Utilities (HICRU) retrieve effective cloud fraction using spectra of two instruments designed for trace gas retrievals from space: The Global Ozone Monitoring Experiment (GOME) on the European Remote Sensing Satellite (ERS-2) and the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) on ENVISAT. HICRU applies the widely used threshold method to the so-called Polarization Monitoring Devices (PMDs) with higher spatial resolution compared to the channels used for trace gas retrievals. Cloud retrieval and in particular the identification of cloud free pixels is improved by HICRU through a sophisticated, iterative retrieval of the thresholds which takes their dependency on different instrumental and geometrical parameters into account. The lower thresholds, which represent the surface albedo and strongly affect the results of the algorithm, are retrieved accurately through a four stage classification scheme using image sequence analysis. The design and the results of the algorithm applied to GOME data are described and compared to several other cloud algorithms for GOME. The differences to other cloud algorithms are discussed with respect to the particular characteristics of the algorithms.

Redar: A Remote Desktop Architecture for the Distributed Virtual Personal Computing

Abstract: Some popular computing technologies, such as ubiquitous computing, grid computing and thin-client computing, bring people to a much more distributed and pervasive computing environment. Based on these innovative technologies, a distributed virtual personal computing (DVPC) paradigm is coming into being. One of the fundamental challenges in the DVPC design is the virtually integrated but physically distributed desktop system. We proposed Redar, a remote desktop architecture for the DVPC. Redar integrates various user interfaces from diverse service nodes into one virtual desktop, and present the virtual desktop to the ultra-thin user client. The user interfaces currently supported by Redar include the application GUIs as well as the mobile storage interfaces. The key components in Redar are the GUI merger, the virtual desktop manager, the ultra-thin-client and the transport protocols. We have implemented Redar in a DVPC prototype system. According to our evaluation, Redar shows perfect display latency, storage I/O, overhead, scalability and robustness.

Geomatics and Information Science of Wuhan University

Abstract: The veracity of land evaluation is tightly related to the reasonable weights of land estimate factors.By mapping qualitative linguistic words into a fine-changeable cloud drops and translating the uncertain factor conditions into quantitative values with the uncertain illation based on the cloud model,and then,integrating correlation analysis,a new way of figuring out the weight of land estimate factors is proposed.It may solve the limitations of the conventional ways.

Developing large-scale forcing data for single-column and cloud-resolving models from the Mixed-Phase Arctic Cloud Experiment

Abstract: [1] This study represents an effort to develop Single-Column Model (SCM) and Cloud-Resolving Model large-scale forcing data from a sounding array in the high latitudes. An objective variational analysis approach is used to process data collected from the Atmospheric Radiation Measurement Program (ARM) Mixed-Phase Arctic Cloud Experiment (M-PACE), which was conducted over the North Slope of Alaska in October 2004. In this method the observed surface and top of atmosphere measurements are used as constraints to adjust the sounding data from M-PACE in order to conserve column-integrated mass, heat, moisture, and momentum. Several important technical and scientific issues related to the data analysis are discussed. It is shown that the analyzed data reasonably describe the dynamic and thermodynamic features of the Arctic cloud systems observed during M-PACE. Uncertainties in the analyzed forcing fields are roughly estimated by examining the sensitivity of those fields to uncertainties in the upper-air data and surface constraints that are used in the analysis. Impacts of the uncertainties in the analyzed forcing data on SCM simulations are discussed. Results from the SCM tests indicate that the bulk features of the observed Arctic cloud systems can be captured qualitatively well using the forcing data derived in thismore » study, and major model errors can be detected despite the uncertainties that exist in the forcing data as illustrated by the sensitivity tests. Lastly, the possibility of using the European Center for Medium-Range Weather Forecasts analysis data to derive the large-scale forcing over the Arctic region is explored.« less

Location management of off-premise resources

Abstract: The innovation enables generation of an index of cloud-based resources (e.g., data, services, applications). The index can be used to retrieve a subset of the cloud-based resources by analyzing a user-generated or standing query. ‘Identity’ and contextual factors can be incorporated to enable rich indexing as well as subsequent retrieval of meaningful resources. The cloud-based resources can be indexed and/or searched in accordance with diverse criteria including, but not limited to, type, size, data created, date modified, author core identity, object size, etc. As well, the innovation can provide for dynamically indexing and/or searching resources in accordance with current contextual factors including, but not limited to, author current acting capacity (e.g., current identity), current engaged activity of a user, location, time, date, etc. All of these criteria can facilitate indexing and categorizing of the resources for later retrieval and rendering via a rich index view.

Seeing the Difference in IP Traffic: Wireless Versus Wireline

Abstract: With the explosive growth of the Internet over the last 10 years, a lot of work has been dedicated to understanding the underlying mechanisms of wired IP traffic Recently, the rapid deployment of large-scale wireless infrastructures in various environments and the interesting mixture of traffic carried coupled with the large diversity of devices accessing the medium (Cell-phones, Laptops, PDAs) have triggered the attention and curiosity of the research community This paper analyzes in depth the properties of several large traces of packet data collected between the wireless access point and the IP cloud from an operational wireless service provider We determine unambiguously the influence of network variables such as the arrival patterns of packet and flows, flow durations and flow interactions, on the aggregate statistics of TCP traffic In doing so, we highlight the main differences and similarities between wireless and wired IP traffic, and between the two directions (from wireless devices to IP cloud and vice-versa), and show how they can be distinguished The resulting insights provide a foundation for models of such traffic, necessary for improved resource allocation schemes as well as for the effectiveness of future services and applications

Impact of conditional sampling and instrumental limitations on the statistics of cloud properties derived from cloud radar and lidar at SIRTA

Abstract: [1] Clouds represent the largest uncertainty in future climate projections. As a result, unbiased long-term vertically-resolved cloud observations must be collected and analyzed in order to produce regional cloud climatologies. In the present study, we use model outputs to evaluate the impact of conditional temporal sampling and instrumental effects on the 2-year statistics of frequency of cloud occurrence and cloud fraction. We then quantify the radiative significance of the ice clouds undetected by cloud radars. We find that in order to evaluate the representation of all types of clouds in operational models both a cloud radar and a lidar must be used. The cloud radar alone can do a reasonable job at describing cloud properties up to 8–9 km, however the lidar is mandatory to detect most of the high-altitude clouds above 9 km. The sampling should be regular but not necessarily continuous, and should not be driven by meteorological conditions. This result applies to all sites having a lidar without a radome. It is finally suggested that a cloud radar of around −60 dBZ sensitivity at 1 km range would be required to detect almost all radiatively-significant ice clouds.

Bridging the e-gaps: towards post-ubiquitous computing

Abstract: We have been working on research and development of advanced network and applications called "flexible computing". We are now in the next stage of this research, strongly pressing forward the concept of flexible computing, namely, "symbiotic computing", towards next generation computing model based on co-existence of real space and digital space. In this paper, we explain basic concepts, architecture and enabling technologies of symbiotic computing that we are aiming to develop.

Erasure Resilient Codes in Peer-To-Peer Storage Cloud

Abstract: In this paper, we investigate the use of erasure resilient code (ERC) in a peer-to-peer storage cloud. We compare the random linear code (RLC, network coding) and the Reed-Solomon (RS) code, and study the proper ERC parameters in term of data reliability, computational efficiency and security concerns. We conclude that the use of ERC in P2P storage may greatly improve data reliability and reduce backup server cost. Because of the lack of efficient homomorphic hashing, RLC can not be implemented efficiently and yet be effective against the malicious attack. As a result, we believe that the RS code is most suited for use in the P2P storage cloud.

A Bootstrap Technique for Testing the Relationship between Local-Scale Radar Observations of Cloud Occurrence and Large-Scale Atmospheric Fields

Abstract: A classification scheme is created to map the synoptic-scale (large scale) atmospheric state to distributions of local-scale cloud properties. This mapping is accomplished by a neural network that classifies 17 months of synoptic-scale initial conditions from the rapid update cycle forecast model into 25 different states. The corresponding data from a vertically pointing millimeter-wavelength cloud radar (from the Atmospheric Radiation Measurement Program Southern Great Plains site at Lamont, Oklahoma) are sorted into these 25 states, producing vertical profiles of cloud occurrence. The temporal stability and distinctiveness of these 25 profiles are analyzed using a bootstrap resampling technique. A stable-state-based mapping from synoptic-scale model fields to local-scale cloud properties could be useful in three ways. First, such a mapping may improve the understanding of differences in cloud properties between output from global climate models and observations by providing a physical context. ...

Access to a computing environment by computing devices

Abstract: A method for managing access to a computing environment by a computing device includes providing at least one credential that identifies both the computing device and a user of the computing device, storing data at the computing environment relating to the computing device and the user in association with the credential, and selectively granting an access request received from the computing device using the credential in accordance with the data stored at the computing environment.