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Forwarding data by name has been assumed to be a necessary aspect of an information-centric redesign of the current Internet architecture that makes content access, dissemination, and storage more efficient. The Named Data Networking (NDN)…
High-Content Digital Microscopy enhances user comfort, data storage and analysis throughput, paving the way to new researches and medical diagnostics. A digital microscopy platform aims at capturing an image of a cover slip, at storing…
We consider load balancing in large-scale heterogeneous server systems in the presence of data locality that imposes constraints on which tasks can be assigned to which servers. The constraints are naturally captured by a bipartite graph…
Given a real-world dataset, data condensation (DC) aims to synthesize a small synthetic dataset that captures the knowledge of a natural dataset while being usable for training models with comparable accuracy. Recent works propose to…
Security analysts need to classify, search and correlate numerous images. Automatic classification tools improve the efficiency of such tasks. However, no open-source and turnkey library was found able to reach this goal. The present paper…
Due to its longevity and enormous information density, DNA is an attractive medium for archival storage. In this work, we study the fundamental limits and tradeoffs of DNA-based storage systems under a simple model, motivated by current…
Free content websites that provide free books, music, games, movies, etc., have existed on the Internet for many years. While it is a common belief that such websites might be different from premium websites providing the same content…
In modern large-scale distributed systems, analytics jobs submitted by various users often share similar work, for example scanning and processing the same subset of data. Instead of optimizing jobs independently, which may result in…
The exponential growth of data necessitates distributed storage models, such as peer-to-peer systems and data federations. While distributed storage can reduce costs and increase reliability, the heterogeneity in storage capacity, I/O…
The past decade highlighted the usefulness of social network simulations that run on k-regular, n-size, connected graphs. These can be seen as small-scale models of human social networks of large societies. By narrowing down onto k-regular…
In this paper we explore visually the structure of the collection of a digital research data archive in terms of metadata for deposited datasets. We look into the distribution of datasets over different scientific fields; the role of main…
Replicating or caching popular content in memories distributed across the network is a technique to reduce peak network loads. Conventionally, the performance gain of caching was thought to result from making part of the requested data…
The problem of fast items retrieval from a fixed collection is often encountered in most computer science areas, from operating system components to databases and user interfaces. We present an approach based on hash tables that focuses on…
In cloud storage systems, hot data is usually replicated over multiple nodes in order to accommodate simultaneous access by multiple users as well as increase the fault tolerance of the system. Recent cloud storage research has proposed…
Caching has been successfully applied in wired networks, in the context of Content Distribution Networks (CDNs), and is quickly gaining ground for wireless systems. Storing popular content at the edge of the network (e.g. at small cells) is…
A Content Distribution Network (CDN) can be defined as an overlay system that replicates copies of contents at multiple points of a network, close to the final users, with the objective of improving data access. CDN technology is widely…
Obtaining semantic labels on a large scale radiology image database (215,786 key images from 61,845 unique patients) is a prerequisite yet bottleneck to train highly effective deep convolutional neural network (CNN) models for image…
Journalistic fact-checking, as well as social or economic research, require analyzing high-quality statistics datasets (SDs, in short). However, retrieving SD corpora at scale may be hard, inefficient, or impossible, depending on how they…
Performance and reliability of content access in mobile networks is conditioned by the number and location of content replicas deployed at the network nodes. Facility location theory has been the traditional, centralized approach to study…
Segmentation of ultra-high resolution images is increasingly demanded, yet poses significant challenges for algorithm efficiency, in particular considering the (GPU) memory limits. Current approaches either downsample an ultra-high…