Related papers: A Communication Efficient and Scalable Distributed…
In this paper, we propose scalable distributed beamforming schemes over low Earth orbit (LEO) satellite networks that rely solely on statistical channel state information for downlink orthogonal frequency division multiplexing systems. We…
An All-to-All Comparison problem is where every element of a data set is compared with every other element. This is analogous to projective planes and affine planes where every pair of points share a common line. For large data sets, the…
Modern scientific repositories are growing rapidly in size. Scientists are increasingly interested in viewing the latest data as part of query results. Current scientific middleware cache systems, however, assume repositories are static.…
The next-generation astronomy archives will cover most of the universe at fine resolution in many wavelengths. One of the first of these projects, the Sloan Digital Sky Survey (SDSS) will create a 5-wavelength catalog over 10,000 square…
Machine Learning has proven useful in the recent years as a way to achieve failure prediction for industrial systems. However, the high computational resources necessary to run learning algorithms are an obstacle to its widespread…
Geo-distributed data analytics are increasingly common to derive useful information in large organisations. Naive extension of existing cluster-scale data analytics systems to the scale of geo-distributed data centers faces unique…
The large size of DNNs poses a significant challenge for deployment on devices with limited resources, such as mobile, edge, and IoT platforms. To address this issue, a distributed inference framework can be utilized. In this framework, a…
This work presents novel distributed data collection systems and storage algorithms for collaborative learning wireless sensor networks (WSNs). In a large WSN, consider $n$ collaborative sensor devices distributed randomly to acquire…
We consider replication-based distributed storage systems in which each node stores the same quantum of data and each data bit stored has the same replication factor across the nodes. Such systems are referred to as balanced distributed…
In this paper we study inexact dumped Newton method implemented in a distributed environment. We start with an original DiSCO algorithm [Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss, Yuchen Zhang and…
Data analysis in space sciences has been performed exclusively visually for years, despite the fact that the largest amount of data belongs to non-visible portions of the electromagnetic spectrum. This, on the one hand, limits the study of…
Network slicing has been considered as one of the key enablers for 5G to support diversified services and application scenarios. This paper studies the distributed network slicing utilizing both the spectrum resource offered by…
We review some of the scientific opportunities and technical challenges posed by the exploration of the large digital sky surveys, in the context of a Virtual Observatory (VO). The VO paradigm will profoundly change the way observational…
Modern cloud databases present scaling as a binary decision: scale-out by adding nodes or scale-up by increasing per-node resources. This one-dimensional view is limiting because database performance, cost, and coordination overhead emerge…
Coded distributed computing can alleviate the communication load by leveraging the redundant storage and computation resources with coding techniques in distributed computing. In this paper, we study a MapReduce-type distributed computing…
Dome A, Antarctica has been thought to be one of the best astronomical sites on the earth since decades ago. From it was first visited by astronomers in 2008, dozens of facilities for astronomical observation and site testing were deployed.…
In this paper, we propose an approach to the distributed storage and fusion of data for collective perception in resource-limited robot swarms. We demonstrate our approach in a distributed semantic classification scenario. We consider a…
Earth Observation (EO) has traditionally involved the transmission of a large volume of raw data to map the Earth surface. This results in congestion to the satellite network and delays in the availability of the results, invalidating the…
The German-Russian Astroparticle Data Life Cycle Initiative is an international project launched in 2018. The Initiative aims to develop technologies that provide a unified approach to data management, as well as to demonstrate their…
Commercial cloud platforms are a powerful technology for astronomical research. Despite the benefits of cloud computing -- such as on-demand scalability and reduction of systems management overhead -- confusion over how to manage costs…