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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Harmonization And Fusion of Global Scale Data
摘要： Remote sensing data provides scientists with synoptic coverage of the Earth's surface, allowing us to understand its system dynamics in a way that would be impossible with more direct observation. As more satellites have been deployed in recent years, imagery has become more readily available and diverse, encompassing a wider range of spatial, temporal, and spectral resolutions than ever before. While these data better inform our understanding of the Earth, anyone hoping to leverage this information is hampered by the large size and complexity of these datasets, a lack of easily accessible computing resources, and the broad expertise required to correctly interpret the imagery. To fully leverage the information in these disparate datasets, data fusion methods must be implemented that abstract access to them. Large scale fusion of geospatial data, using physically based and statistical methods, can be accomplished to create a living model of the earth. This presentation will discuss the Descartes Labs approach to data fusion and normalization as well as our effort to leverage these capabilities toward a synoptic earth model. Topics will include the current status of the physical normalization algorithms deployed into the Descartes Labs Platform as well as efforts to harmonize and abstract access to multi-vendor constellations.
关键词： cloud computing,data fusion,data normalization,surface reflectance
更新于2025-09-10 09:29:36
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Surface Deformation Mapping of Italy Through the P-Sbas Dinsar Processing of Sentinel-L Data in a Cloud Computing Environment
摘要： In this work we implement a completely automatic interferometric processing chain, based on the well-known advanced DInSAR algorithm referred to as Parallel Small BAseline Subset (P-SBAS), for the generation of Sentinel-1 (S-1) Interferometric Wide Swath (IWS) deformation mean velocity maps and time-series of very wide areas, implemented within the Amazon Web Services (AWS) Elastic Cloud Compute environment. Our processing chain consists of the initial data query to the S-1 archive that we created on the AWS S3 storage, then the data transfer to the AWS computing nodes, the data processing and, finally, the transfer of the obtained interferometric results back to the original S3 storage. In order to demonstrate the capability of the implemented Cloud-based processing chain to deal with massive amount of data, we focus our analysis on the whole Italian territory by processing all the available data acquired both from ascending and descending orbits within the October 2014 – March 2017 time interval. As final result we combine the retrieved LOS displacements in order to compute the mean velocity maps and time-series of the vertical and East-West surface deformation components.
关键词： P-SBAS,Sentinel-1,Cloud Computing,DInSAR,deformation time-series
更新于2025-09-10 09:29:36
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Quantum information exchange protocol associated with the quantum cloud
摘要： Quantum cryptography discusses the security of quantum information. Cloud computing has emerged as a computational paradigm and an alternative to the conventional computing. Cloud security is associated with cloud computing. In this paper, we define the new concept about quantum cloud and discuss the security of quantum information exchange in quantum internet. A tripartite simultaneous quantum information exchange protocol associated with the quantum cloud based on entanglement swapping and Bell states is proposed. The proposed secure quantum information exchange protocol can resist intercept-and-resend attack, intercept-and-measure attack, intercept-and-entangle auxiliary attack and denial-of-service attack. It can also be generalised to N-party case that is feasible and efficient.
关键词： intercept-and-resend attack,cloud computing,quantum information exchange,intercept-and-measure attack,intercept-and-entangle auxiliary attack,denial-of-service attack,quantum cloud
更新于2025-09-09 09:28:46
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[Advances in Intelligent Systems and Computing] Image Processing and Communications Challenges 10 Volume 892 (10th International Conference, IP&C’2018 Bydgoszcz, Poland, November 2018, Proceedings) || Interference-Aware Virtual Machine Placement: A Survey
摘要： In order to maintain energy e?ciency and optimize resource utilization in cloud datacenters, cloud providers adopt virtualization technologies as well as server consolidation. Virtualization is the means used to achieve multi-tenant environments by creating many virtual machines (VMs) on the same physical machine (PM) in a way that they share same physical resources (e.g. CPU, disk, memory, network I/O, etc.). Server consolidation consists of placing as much as possible VMs on as less as possible PMs, in the aim of maximizing idle servers and then minimize the energy consumption. However, this vision of server consolidation is not as simple as it seems to be. Hence, it is crucial to be aware of its emerging concerns, such as severe performance degradation problem when placing particular VMs on the same PM. Furthermore, the Virtual Machine Placement (VMP) is one of the most challenging problems in cloud environments management and it’s been studied from various perspectives. In this paper, we are going to propose a VMP taxonomy in order to understand the various aspects that researchers consider while de?ning their VMP approaches. We will also survey the most relevant interference-aware virtual machine placement literature and then we shall give a comparative study between them.
关键词： Server Consolidation,Energy Efficiency,Interference-aware,Cloud Computing,Virtual Machine Placement
更新于2025-09-09 09:28:46
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[IEEE 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Krakow, Poland (2018.10.16-2018.10.18)] 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Vision-Based Product Tracking Method for Cyber-Physical Production Systems in Industry 4.0
摘要： A competitive company should possess the ability to rapidly adopt to changes and the new era of the fourth industrial revolution (Industry 4.0) puts forward an incredible reshaping of the entire manufacturing sector. The primary goal of Industry 4.0 should be to transform the massive production lines from a system-based scheme to a product-based one, while individuals and cyber-physical systems (CPSs) should interact with each other and with objects. This advantage can be achieved in a smart factory, so as to allow product tracking all the way through manufacturing by interacting with any other factory component via cloud computing. Towards this end, in this paper we propose a vision-oriented method, which utilizes detection and tracking along with a cloud-based platform to facilitate product tracking and interaction. The proposed method make use of a panoramic camera composing a CPS, which a part of a cyber-physical production system (CPPS). We study and evaluate the proposed CPS in a computer integrated manufacturing (CIM) scenario.
关键词： Computer Integrated Manufacturing,Cyber-Physical Systems,Product Tracking,Cloud Computing,Industry 4.0
更新于2025-09-09 09:28:46
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[IEEE 2018 26th International Conference on Geoinformatics - Kunming, China (2018.6.28-2018.6.30)] 2018 26th International Conference on Geoinformatics - SPARK Processing of Computing-Intensive Classification of Remote Sensing Images: The Case on K-Means Clustering Algorithm
摘要： High performance processing of remote sensing images is an important topic in remote sensing applications. One typical type of remote sensing processing is the iterative computing algorithms such as image classification algorithms, which are often computing-intensive and time-consuming. Recent advancement of cloud computing technologies such as APACHE SPARK has shown great promise for improving the computing performance. This paper presents a MapReduce based approach for parallelizing classification algorithms of remote sensing images on the cloud computing platform. The iterative processing is transformed into iterative Map and Reduce tasks that can be executed in parallel. The K-Means clustering algorithm is experimented with the SPARK cluster deployed on the OpenStack cloud computing platform to illustrate the applicability and effectiveness of the approach.
关键词： cloud computing,classification,distributed computing,remote sensing images
更新于2025-09-04 15:30:14
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[Advances in Intelligent Systems and Computing] Image Processing and Communications Challenges 10 Volume 892 (10th International Conference, IP&C’2018 Bydgoszcz, Poland, November 2018, Proceedings) || Ten Years of Image Processing and Communications
摘要： Image processing and communications have become emerging domains for researchers and societies all over the world. Both are widely implemented and become reality in everyday matters. In this article authors present an overview of the trends and reflect on aspects discussed during the Image Processing and Communications Conferences taking place in Bydgoszcz, Poland during last 10 years. The paper aims to reflect on this great event and its scientific contents.
关键词： Cloud computing,Biometrics,Applications,Image quality,Video processing,Pattern recognition,Network,Image processing,Cyber security
更新于2025-09-04 15:30:14