相关论文: Towards an IO intensive Grid application instrumen…
Cloud Geographic Information Systems (GIS) has emerged as a tool for analysis, processing and transmission of geospatial data. The Fog computing is a paradigm where Fog devices help to increase throughput and reduce latency at the edge of…
We present our experiences using cloud computing to support data-intensive analytics on satellite imagery for commercial applications. Drawing from our background in high-performance computing, we draw parallels between the early days of…
This paper investigates new efficient transmission architectures for multi-satellite massive multiple-input multiple-output (MIMO). We study the weighted sum-rate maximization problem in a multi-satellite system where multiple satellites…
Virtualization technology allows currently any application run any application complex and expensive computational (the scientific applications are a good example) on heterogeneous distributed systems, which make regular use of Grid and…
Ever-increasing amounts of data and requirements to process them in real time lead to more and more analytics platforms and software systems being designed according to the concept of stream processing. A common area of application is the…
In this paper we discuss ways to reduce the execution time of a software Global Navigation Satellite System (GNSS) receiver that is meant for offline operation in a cloud environment. Client devices record satellite signals they receive,…
Sending massive Earth observation data produced by low Earth orbit (LEO) satellites back to the ground for processing consumes a large amount of on-orbit bandwidth and exacerbates the space-to-ground link bottleneck. Most prior work has…
In this paper, we propose a methodology for partitioning and mapping computational intensive applications in reconfigurable hardware blocks of different granularity. A generic hybrid reconfigurable architecture is considered so as the…
Grids enable the aggregation, virtualization and sharing of massive heterogeneous and geographically dispersed resources, using files, applications and storage devices, to solve computation and data intensive problems, across institutions…
Major advances in telecommunications and the Internet of Things have given rise to numerous smart city scenarios in which smart services are provided. What was once a dream for the future has now become reality. However, the need to provide…
A large volume of remote sensing (RS) data has been generated with the deployment of satellite technologies. The data facilitates research in ecological monitoring, land management and desertification, etc. The characteristics of RS data…
Regarding to the smart city infrastructures, there is a demand for big data processing and its further usage. This data can be gained by various means. There are many IoT devices in the city, which can communicate and share the information…
Modern intelligent urban mobility applications are underpinned by large-scale, multivariate, spatiotemporal data streams. Working with this data presents unique challenges of data management, processing and presentation that is often…
An emerging class of data-intensive applications involve the geographically dispersed extraction of complex scientific information from very large collections of measured or computed data. Such applications arise, for example, in…
This chapter summarizes the results obtained from a test bed, which is composed of a microgrid and a wireless network, both relying on real and practical premises. This test bed aims to evaluate application protocols considered in the…
The amount of remote sensing data available to applications is constantly growing due to the rise of very-high-resolution sensors and short repeat cycle satellites. Consequently, tackling computational complexity in Earth Observation…
This work describes Live Monitor, the monitoring subsystem of SDDS - an automated system for space experiment data processing, storage, and distribution created at SINP MSU. Live Monitor allows operators and developers of satellite data…
The field of remote sensing is nowadays faced with huge amounts of data. While this offers a variety of exciting research opportunities, it also yields significant challenges regarding both computation time and space requirements. In…
The problem of data synchronization arises in networked applications that require some measure of consistency. Indeed data synchronization approaches have demonstrated a significant potential for improving performance in various…
A grid computing system is designed for solving complicated scientific and commercial problems effectively,whereas mobile computing is a traditional distributed system having computing capability with mobility and adopting wireless…