Search results for "cloud computing."
showing 10 items of 325 documents
Pattern Recognition Scheme for Large-Scale Cloud Detection over Landmarks
2020
Landmark recognition and matching is a critical step in many Image Navigation and Registration (INR) models for geostationary satellite services, as well as to maintain the geometric quality assessment (GQA) in the instrument data processing chain of Earth observation satellites. Matching the landmark accurately is of paramount relevance, and the process can be strongly impacted by the cloud contamination of a given landmark. This paper introduces a complete pattern recognition methodology able to detect the presence of clouds over landmarks using Meteosat Second Generation (MSG) data. The methodology is based on the ensemble combination of dedicated support vector machines (SVMs) dependent…
A Deep Network Approach to Multitemporal Cloud Detection
2018
We present a deep learning model with temporal memory to detect clouds in image time series acquired by the Seviri imager mounted on the Meteosat Second Generation (MSG) satellite. The model provides pixel-level cloud maps with related confidence and propagates information in time via a recurrent neural network structure. With a single model, we are able to outline clouds along all year and during day and night with high accuracy.
Cloud detection machine learning algorithms for PROBA-V
2020
This paper presents the development and implementation of a cloud detection algorithm for Proba-V. Accurate and automatic detection of clouds in satellite scenes is a key issue for a wide range of remote sensing applications. With no accurate cloud masking, undetected clouds are one of the most significant sources of error in both sea and land cover biophysical parameter retrieval. The objective of the algorithms presented in this paper is to detect clouds accurately providing a cloud flag per pixel. For this purpose, the method exploits the information of Proba-V using statistical machine learning techniques to identify the clouds present in Proba-V products. The effectiveness of the propo…
A Comprehensive Utility Function for Resource Allocation in Mobile Edge Computing
2020
In mobile edge computing (MEC), one of the important challenges is how much resources of which mobile edge server (MES) should be allocated to which user equipment (UE). The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only. This paper presents a novel comprehensive utility function for resource allocation in MEC. The utility function considers the heterogeneous nature of applications that a UE offloads to MES. The proposed utility function considers all important parameters, including CPU, RAM, hard disk space, required time, and distance, to calculate a more realis…
A Proposed Access Control-Based Privacy Preservation Model to Share Healthcare Data in Cloud
2020
Healthcare data in cloud computing facilitates the treatment of patients efficiently by sharing information about personal health data between the healthcare providers for medical consultation. Furthermore, retaining the confidentiality of data and patients' identity is a another challenging task. This paper presents the concept of an access control-based (AC) privacy preservation model for the mutual authentication of users and data owners in the proposed digital system. The proposed model offers a high-security guarantee and high efficiency. The proposed digital system consists of four different entities, user, data owner, cloud server, and key generation center (KGC). This approach makes…
Assessing Cloud Infrastructure Costs in Communications-Intensive Applications
2012
By deploying cloud infrastructure services, companies strive at achieving faster time to market, improved scalability, lower up-front costs, and lower IT management overhead, among other benefits. However, in longer term, the use of cloud infrastructure may incur significant costs; furthermore, these costs depend both on the required infrastructure resources and on the mode of infrastructure deployment. Therefore, the choice of a particular deployment mode should be justified with a systematic analysis of the associated costs. In this paper, a model for assessing the costs of alternative cloud infrastructure deployment scenarios is introduced. This model decomposes the infrastructure costs …
Intelligent Cloud Storage Management for Layered Tiers
2018
Today, the cloud offers a large array of possibilities for storage, with this flexibility comes also complexity. This complexity stems from the variety of storage mediums, such as, blob storage or NoSQL tables, and also from the different cost tiers within these systems. A strategic thinking to navigate this complex cloud storage landscape is important, not only for cost saving but also for prioritizing information, this prioritization has wider implications in other domains such as the Big Data realm, especially for governance and efficiency. In this paper we propose a strategy centered around probabilistic graphical model (PGM), this heuristic oriented management and organizational strate…
Cloud Computing Vulnerabilities Analysis
2019
Nowadays cloud computing technologies are the most widely used tools due to their great flexibility and also to their lower maintenance costs. Many vendors of cloud computing have appeared on the market for each type of cloud. These solutions still pose certain vulnerabilities and work to improve the security of cloud computing technologies. We analyze the main cloud computing solutions, analyze the vulnerabilities identified for these solutions, and also calculate the impact of these vulnerabilities based on the NVD scores. We average the scores for each solution for each cloud computing model. This way, we can see the impact of the vulnerabilities identified so far for each cloud computin…
Activation radius of aerosol particles in cloud events - ground based and aircraft field measurements
1997
Accelerating bioinformatics applications via emerging parallel computing systems [Guest editorial]
2015
The papers in this issue focus on advanced parallel computing systems for bioinformatics applications. This papers provide a forum to publish recent advances in the improvement of handling bioinformatics problems on emerging parallel computing systems. These systems can be characterized by exploiting different types of parallelism, including fine-grained versus coarse-grained and thread-level parallelism versus datalevel parallelism versus request-level parallelism. Hence, parallel computing systems based on multi- and many-core CPUs, many-core GPUs, vector processors, or FPGAs offer the promise to massively accelerate many bioinformatics algorithms and applications, ranging from computeint…