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Distributed Hash Tables (DHTs) are pivotal in numerous high-impact key-value applications built on distributed networked systems, offering a decentralized architecture that avoids single points of failure and improves data availability.…
Cost-effective and scalable video analytics are essential for precision livestock monitoring, where high-resolution footage and near-real-time monitoring needs from commercial farms generates substantial computational workloads. This paper…
Non-relational databases are the common means of data storage in the Cloud, and optimizing the data access is of paramount importance into determining the overall Cloud system performance. In this paper, we present GAIA, a novel model for…
Scheduling virtual machines (VMs) on hosts in cloud data centers dictates efficiency and is an NP-hard problem with incomplete information. Prior work improved VM scheduling with predicted VM lifetimes. Our work further improves…
Incorporating AI technologies into digital infrastructure offers transformative potential for energy management, particularly in enhancing energy efficiency and supporting net-zero objectives. However, the complexity of IoT-generated…
Database systems are becoming increasingly multi-engine. In particular, a main-memory database engine may coexist with a traditional storage-centric engine in a system to support various applications. It is desirable to allow applications…
In the interdisciplinary field of microscopy research, managing and integrating large volumes of data stored across disparate platforms remains a major challenge. Data types such as bioimages, experimental records, and spectral information…
Reliable access to food is a basic requirement in any sustainable society. However, achieving food security for all is still a challenge, especially for poor populations in urban environments. The project Feed4Food aims to use a federation…
In the last two decades, unsupervised latent variable models---blind source separation (BSS) especially---have enjoyed a strong reputation for the interpretable features they produce. Seldom do these models combine the rich diversity of…
In recent IoT (Internet of Things) and Web 2.0 technologies, a critical problem arises with respect to storing and processing the large amount of collected data. In this paper we develop and evaluate distributed infrastructures for storing…
In this paper we propose a data dissemination platform that supports data security and different privacy levels even when the platform and the data are hosted by untrusted infrastructures. The proposed system aims at enabling an application…
Mobile crowdsensing (MCS) is a new paradigm of sensing by taking advantage of the rich embedded sensors of mobile user devices. However, the traditional server-client MCS architecture often suffers from the high operational cost on the…
The dense concentration of low-altitude, slow-speed, and small-size targets in the complex low-altitude environment poses significant security challenges, including failures in continuous wide-area sensing and ambiguous target intent, which…
A new class of Wireless Sensor Network has emerged whereby multiple nodes transmit data simultaneously, exploiting constructive interference to enable data collection frameworks with low energy usage and latency. This paper presents STAIR…
MLModelCI provides multimedia researchers and developers with a one-stop platform for efficient machine learning (ML) services. The system leverages DevOps techniques to optimize, test, and manage models. It also containerizes and deploys…
Small-scale clouds (SCs) often suffer from resource under-provisioning during peak demand, leading to inability to satisfy service level agreements (SLAs) and consequent loss of customers. One approach to address this problem is for a set…
We describe a new end-to-end experimental data streaming framework designed from the ground up to support new types of applications -- AI training, extremely high-rate X-ray time-of-flight analysis, crystal structure determination with…
Financial exchanges are migrating to the cloud, but the best-effort nature of the public cloud is at odds with the stringent latency requirements of exchanges. We present Jasper, a system for meeting the networking requirements of financial…
When we consider the application layer of networked infrastructures, data and control flow are important concerns in distributed systems integration. Modularity is a fundamental principle in software design, in particular for distributed…
Currently, one of the hottest topics in the Internet of Things (IoT) research domain regards the issue to overcome the heterogeneity of proprietary technologies and systems so as to enable the integration of applications and devices…