Search results for "cloud computing."
showing 10 items of 325 documents
Run-time scalable NoC for FPGA based virtualized IPs
2017
The integration of virtualized FPGA-based hardware accelerators in a cloud computing is progressing from time to time. As the FPGA has limited resources, the dynamic partial reconfiguration capability of the FPGA is considered to share resources among different virtualized IPs during runtime. On the other hand, the NoC is a promising solution for communication among virtualized FPGA-based IPs. However, not all the virtualized regions of the FPGA will be active all the time. When there is no demand for virtualized IPs, the virtualized regions are loaded with blank bitstreams to save power. However, keeping active the idle components of the NoC connecting with the idle virtualized regions is …
Convolutional Neural Networks for Cloud Screening: Transfer Learning from Landsat-8 to Proba-V
2018
Cloud detection is a key issue for exploiting the information from Earth observation satellites multispectral sensors. For Proba-V, cloud detection is challenging due to the limited number of spectral bands. Advanced machine learning methods, such as convolutional neural networks (CNN), have shown to work well on this problem provided enough labeled data. However, simultaneous collocated information about the presence of clouds is usually not available or requires a great amount of manual labor. In this work, we propose to learn from the available Landsat −8 cloud masks datasets and transfer this learning to solve the Proba-V cloud detection problem. CNN are trained with Landsat images adap…
Transferring deep learning models for cloud detection between Landsat-8 and Proba-V
2020
Abstract Accurate cloud detection algorithms are mandatory to analyze the large streams of data coming from the different optical Earth observation satellites. Deep learning (DL) based cloud detection schemes provide very accurate cloud detection models. However, training these models for a given sensor requires large datasets of manually labeled samples, which are very costly or even impossible to create when the satellite has not been launched yet. In this work, we present an approach that exploits manually labeled datasets from one satellite to train deep learning models for cloud detection that can be applied (or transferred) to other satellites. We take into account the physical proper…
On the Dependence of Cirrus Parametrizations on the Cloud Origin
2019
<p>Particle size distributions (PSDs) for cirrus clouds are important for both climate models as well as many remote sensing retrieval methods. Therefore, PSD parametrizations are required. This study presents parametrizations of Arctic cirrus PSDs. The dataset used for this purpose originates from balloon-borne measurements carried out during winter above Kiruna (Sweden), i.e. north of the Arctic circle. The observations are sorted into two types of cirrus cloud origin, either in-situ or liquid. The cloud origin describes the formation pathway of the ice particles. At temperatures below −38 °C, ice particles form in-situ from solution or ice nuclea…
A Cloud masking algorithm for the XBAER aerosol retrieval using MERIS data
2017
Abstract To determine aerosol optical thickness, AOT, and other geophysical parameters describing conditions in the atmosphere and at the earth's surface by inversion of remote sensing measurements from space based instrumentation, it is necessary to separate ground scenes into cloud free and cloudy or cloud contaminated. Identifying the presence of cloud in a ground scene and establishing an accurate and adequate cloud mask is a challenging task. In this study, measurements by the European Space Agency (ESA) MEdium Resolution Imaging Spectrometer (MERIS) have been used to develop a cloud identification and cloud mask algorithm for preprocessing prior to application of the new algorithm cal…
Wireless NoC for Inter-FPGA Communication: Theoretical Case for Future Datacenters
2020
Integration of FPGAs in datacenters might have different motivations from acceleration to energy efficiency, but the goal of better performance tops all. FPGAs are being utilized in a variety of ways today, tightly coupled with heterogenous computing resources, and as a standalone network of homogenous resources. Open source software stacks, propriety tool chain, and programming languages with advanced methodologies are hitting hard on the programmability wall of the FPGAs. The deployment of FPGAs in datacenters will neither be sustainable nor economical, without realizing the multi-tenancy in multiple FPGAs. Inter-FPGA communication among multiple FPGAs remained relatively less addressed p…
Energy Efficient Optimization for Computation Offloading in Fog Computing System
2017
In this paper, we investigate the energy efficient computation offloading scheme in a multi-user fog computing system. We consider the users need to make the decision on whether to offload the tasks to the fog node nearby, based on the energy consumption and delay constraint. In particular, we utilize queuing theory to bring a thorough study on the energy consumption and execution delay of the offloading process. Two queuing models are applied respectively to model the execution processes at the mobile device (MD) and fog node. Based on the theoretical analysis, an energy efficient optimization problem is formulated with the objective to minimize the energy consumption subjects to execution…
Broker and Federation Based Cloud Networking Architecture for IaaS and NaaS QoS Guarantee
2016
International audience; Today, the Cloud networking aspect is a critical factor for adopting the Cloud computing approach. The main drawback of Cloud networking consists in the lack of Quality of Service (QoS) guarantee and management in conformance with a corresponding Service Level Agreement (SLA). This paper presents a framework for resource allocation according to an end-to-end SLA established between a Cloud Service User (CSU) and several Cloud Service Providers (CSPs) in a Cloud networking environment. We focus on QoS parameters for Network as a Service (NaaS) and Infrastructure as a Service (IaaS) services. In addition, we propose algorithms for the best CSPs selection to allocate Vi…
A Patient-Centric Attribute Based Access Control Scheme for Secure Sharing of Personal Health Records Using Cloud Computing
2016
Personal health records (PHR) are an emerging health information exchange model, which facilitates PHR owners to efficiently share their private health data among a variety of users including healthcare professionals as well as family and friends. PHRs are usually outsourced and stored in third-party cloud platforms which relieves PHR owners from the burden of managing their PHR data while achieving better availability of health data. However, outsourcing private health data raises significant privacy concerns because there is a higher risk of leaking health information to unauthorized parties. To ensure PHR owners' control of their outsourced PHR data, attribute based encryption (ABE) mech…
A Distributed Multi-Authority Attribute Based Encryption Scheme for Secure Sharing of Personal Health Records
2017
Personal health records (PHR) are an emerging health information exchange model, which facilitates PHR owners to efficiently manage their health data. Typically, PHRs are outsourced and stored in third-party cloud platforms. Although, outsourcing private health data to third-party platforms is an appealing solution for PHR owners, it may lead to significant privacy concerns, because there is a higher risk of leaking private data to unauthorized parties. As a way of ensuring PHR owners' control of their outsourced PHR data, attribute based encryption (ABE) mechanisms have been considered due to the fact that such schemes facilitate a mechanism of sharing encrypted data among a set of intende…