Articles tagged with Cloud Computing
Researchers from MIT have developed a more user-friendly and efficient method to identify potential system failures in cloud computing algorithms. The 'MetaEase' technique analyzes an algorithm's source code directly to uncover hidden blind spots that might cause unexpected failures, reducing the risk of costly network outages.
Microsoft received the 2026 INFORMS Franz Edelman Award for its innovative use of generative AI and advanced analytics in cloud supply chain optimization. The Intelligent Fulfillment Service (IFS) has halved cycle times, generating significant annual savings while mitigating tariff impacts.
A new database, led by Harvard computer scientist Salil Vadhan, enables companies to adopt differential privacy framework, providing real-world applications for protected data. The Differential Privacy Deployments Registry aims to promote widespread adoption and refinement of the technology.
Researchers have developed a passive, solar-powered orbital data center that can scale AI computing and reduce environmental impact. The system leverages decades of research on 'tethers' and could host thousands of computing nodes to replicate terrestrial data centers.
The MLEDGE project has successfully combined federated learning with cloud and edge computing to develop more secure, efficient, and personalized AI solutions. The project's applications include real-time COVID risk maps and energy consumption optimization in industry.
The UC3M's new supercomputer is a state-of-the-art facility designed to support research and development projects requiring high-performance computing. The system features over 11,500 CPU cores and 42 GPUs, enabling the processing of large volumes of data and complex numerical simulations.
The Stowers Institute has appointed its first AI Fellow, Sumner Magruder, to harness the potential of artificial intelligence in biological research. He will collaborate with researchers to design new algorithms and unlock insights from large datasets.
The team aims to deliver AI power directly to devices, improving resilience and speed in constrained environments. By processing data step-by-step across a network of devices, they can create a safe and adaptable system that can withstand attacks and extreme conditions.
The Hong Kong Polytechnic University has secured funding from the Research Grants Council to develop a cost-effective and sustainable collaborative Generative AI (Co-GenAI) model. The project aims to democratize AI development by reducing centralized computational demand and enabling broader participation in GenAI research and deployment.
Computer scientist An Wang receives a $1M NSF CAREER grant to leverage cloud computing resources for efficient machine learning model training. Environmental engineer Bridget Hegarty receives a grant to develop safe and effective biocontrol for water systems using bacteriophages.
Purdue researchers create a new method to notify CPUs without polling, reducing interrupt overhead and improving efficiency. This discovery impacts cloud systems and large data centers, driving smooth operations throughout networks.
Hebrew University alumni Assaf Rappaport, Ami Lotbek, and Yinon Costica have achieved the largest exit in Israel's history with the acquisition of WIZ by Google. The trio is proud graduates of the university, with Lotbek also holding a master's degree from the School of Engineering and Computer Science.
The Open Brain Institute launches a groundbreaking platform to simulate and study digital brains, empowering researchers to explore brain complexity and diseases. With its virtual neuroscience laboratories, the OBI enables global collaboration and access to cutting-edge virtual labs.
Researchers have developed a high-speed, energy-efficient electro-optic switch with low crosstalk and broad bandwidth. The switch uses a scalable process and consists of four Mach-Zehnder interferometer structures formed by silicon nitride waveguides.
Researchers discovered a key security weakness in AMD computer processors due to 'BadRAM', rogue memory modules providing false information to the processor. This allows attackers to bypass CPU memory protections and access sensitive data or cause disruptions in shared cloud environments.
A team of scientists and experts led by PNNL has developed a cloud computing approach to democratize access to emerging resources. They demonstrated that cloud computing can provide an agile complement to high-performance computing facilities, enabling complex chemistry workflows to be completed in days instead of months. The initiativ...
The U.S. Department of Energy has selected Kate Petersen Mace as the project director for the High Performance Data Facility (HPDF), a first-of-its-kind project providing resources for data-intensive science. Mace will lead the team in developing transformational capabilities to serve the DOE community.
A new study by Penn State researchers found that US firms using cloud computing services are more likely to export goods and services, especially those located outside large cities. The study suggests that accessing cloud services may help level the playing field for non-urban firms and promote their expansion into international markets.
Researchers developed a real-time stream-based data compression technology that automatically detects frequently occurring data patterns and compresses them to minimize data volume. This innovation enables high-speed, compact data compression modules in hardware without additional processors or memory.
The Chameleon testbed has secured $12 million in funding to expand its services in computer science research. With this new funding, the platform will continue to innovate and support its growing community, enabling groundbreaking discoveries in CS systems research.
Konstantinos Mamouras, assistant professor of computer science at Rice University, has been awarded a $547,555 NSF CAREER Award to decentralize IoT applications and relieve network congestion. He aims to introduce novel programming techniques that enable efficient and reliable IoT development.
A new study published in Physical Review Letters has developed a method for secure quantum computing, enabling users to access remote quantum computers while maintaining data authenticity and security. This breakthrough promises to unlock the transformative potential of cloud-based quantum computing.
Researchers have developed a scalable, fully-coupled annealing processor that outperforms simulating a fully coupled Ising system on a PC by 2,306 times. The processor incorporates 4096 spins and uses parallelized capabilities for accelerated problem-solving.
The Internet-of-Batteries (IoB) system utilizes IoT principles to gather data from EV batteries, analyzing health and performance, identifying faults, and optimizing usage. Machine learning approaches enhance decision-making for improved battery performance, increased range, and reduced costs.
The partnership aims to leverage AI and cloud computing to accelerate scientific discovery in chemistry and materials science, two key fields for global energy challenges. PNNL researchers are testing Microsoft's Azure Quantum Elements platform to identify promising new materials for energy applications.
A research team at City University of Hong Kong has developed a novel performance evaluation method called Information Exchange Surrogate Approximation (IESA) to calculate blocking probabilities in queueing systems with overflow. IESA provides ways to allocate limited resources better, enhancing resource allocation and capacity plannin...
The High Performance Data Facility Hub will provide researchers with unprecedented data management resources, accelerating scientific discovery through seamless access to large and complex datasets. The hub will be led by Jefferson Lab and partner with Lawrence Berkeley National Laboratory.
Researchers are working on EdgeRIC: Real-time radio access network intelligent control, aiming to enhance wireless communication and machine learning. The project involves developing intelligent systems that can adapt to changing conditions, prioritizing users and acquiring lower latency for applications.
Serverless computing is a paradigm shift in cloud computing where cloud providers take over responsibility for complete server management. Two key principles define it: 'NoOps' and 'utilisation-based billing'. Research team from University of Würzburg explores the history, status and potential of serverless computing.
The University of Missouri is using a $1 million grant to develop an Industry 4.0 lab, providing engineering students with hands-on learning experiences in the latest industrial revolution's technology-centered job market. The lab will integrate skills at a higher level and keep students at the state-of-the-art level for industry.
A study published in Telecommunications Policy found that cloud adoption enables innovation in rural businesses, increasing new-to-market innovation by 6% compared to non-cloud firms. The research highlights the importance of broadband access in enabling rural entrepreneurship and supporting vibrant economies.
A deep learning-based framework called EMGSense enables accurate wearable EMG device usage through AI self-training techniques. It achieves average accuracy of 91.9% in gesture recognition and 81.2% in activity recognition, outperforming state-of-the-art approaches.
Researchers developed MoBIE, a user-friendly tool for sharing and exploring large image data sets. The tool allows for visualization and analysis of huge amounts of data from hundreds of sources, making it easier for researchers to analyze and interpret microscopy data worldwide.
Engineers at Tokyo Institute of Technology have developed a technique to support the classification performance of neural networks operating on sensor time series by feeding recorded signals into elementary non-linear dynamical systems. This approach increases the classification performance by augmenting the data through additional tim...
Researchers have identified a tailor-made pocket feature in the spike glycoproteins of deadly coronaviruses, including SARS-CoV-2, MERS, and Omicron. This finding could lead to the development of a pan-coronavirus treatment that exploits this pocket feature to stop virus infectivity.
Researchers propose a new solution called labeled von Neumann architecture (LvNA) to tackle challenges in cloud computing. LvNA incorporates label-powered control mechanisms to differentiate, isolate, and prioritize user-defined application requests, mitigating resource contentions and guaranteeing performance.
Researchers found that cloud tenants are vulnerable to receiving sensitive customer data when IP addresses are leased and released back to the public. To mitigate this risk, companies and cloud-service providers must implement practices such as preventing IP address reuse.
Researchers at North Carolina State University identified a vulnerability in homomorphic encryption that allows data to be stolen during the encryption process. This discovery highlights the need for protection against side-channel attacks, which can compromise even next-generation encryption technologies.
Research reveals SARS-CoV-2 can have multiple variants in one person, with some hiding in specific cells like kidneys or spleens. This can make complete virus clearance more difficult, as the body struggles to defend against dominant strains.
Cidon's new software framework, XRP, aims to speed up cloud computing by offloading storage functions to the operating system. The project expects to more than halve computation and energy needed for common storage operations on fast storage devices.
The MDI Biological Laboratory has been awarded a grant to promote cloud computing among researchers in Maine, aiming to level the playing field by providing access to sophisticated computing resources. The program will provide training on Google Cloud Platform and assist institutions in implementing cloud computing services.
The RT-CIRAM system analyzes public-domain data to determine the best times to avoid crowds and minimize COVID-19 infection risk. The mobile phone app provides personalized recommendations based on user input and factors like vaccination rates and cultural norms.
Rice University computer scientists have discovered an inexpensive way to implement rigorous personal data privacy in large databases for machine learning. Using locality sensitive hashing, their RACE method creates small summaries of enormous databases while scaling for high-dimensional data.
Researchers developed SeKVM, a system that guarantees the security of virtual machines in the cloud through mathematical proof. This breakthrough enables companies and users to trust their data and computation in cloud computing providers like Amazon.
Researchers are studying the integration of smart vehicles with smart cities, exploring computing paradigms such as vehicular cloud computing and vehicular fog computing. The goal is to create efficient, safe, and economical transportation systems that can adapt to real-time applications.
A UMass Amherst-led team will develop a self-powered, decentralized network of computing hardware and solar batteries to reduce carbon emissions. The team plans to virtualize energy systems and engineer digital carbon-capping policies to track applications' use of traditional grid-based carbon emissions.
A new software tool called HangFix can detect and fix hang bugs in production cloud systems, resolving issues in seconds. Researchers tested the tool against 42 real-world bugs and found it successfully fixed 40 of them instantly.
A computer science researcher has developed an algorithm called Orchestra that reduces spikes in resource demands in cloud computing, allowing companies to maintain smooth operations despite increased work-from-home usage. The solution uses lightweight monitoring and performance-based models to adjust cloud resources in real-time.
Researchers from Los Alamos National Laboratory have developed a new technique that separates industrial noise from natural seismic signals using cloud computing. The approach allows for large-scale seismic analysis ten times faster than traditional methods and has the potential to transform the field of seismology.
Researchers used computational simulation methods and cloud computing to discover how nicotine receptors respond to nicotine, reducing time to results from months to days. This accelerated discovery could lead to more effective smoking cessation aids, addressing a major public health concern.
Jia Rao's research aims to overcome bottlenecks in high-speed networks and virtualized networks by developing stress-testing approaches, pipelining processes, and scheduling algorithms. The goal is to improve efficiency in commodity operating systems, allowing users to capitalize on the speed of high-performance networks.
Mendel Rosenblum's work on virtual machines transformed datacenters and enabled modern cloud computing. His contributions led to the development of Amazon Web Services, Microsoft Azure, and Google Cloud.
Jia Rao, a UTA researcher, is working on redesigning abstractions in virtualized systems to improve efficiency. Current virtualization systems face issues with performance, cost-effectiveness, and predictability due to semantic gaps between levels of abstraction.
The NSF-funded E-CAS project will investigate the viability of commercial clouds for leading-edge research computing, with Amazon Web Services and Google Cloud Platform as initial providers. The project aims to accelerate scientific discoveries by leveraging cloud computing capabilities.
Researchers at the University of Arizona are developing fog computing to address high-speed data demands in applications like telemedicine and smart transportation. By moving data processing closer to users, fog computing reduces latency and enables real-time decision-making.
Researchers analyzed mountain glaciers using satellite imagery and found that 4.4% of the glacier surface is covered in debris, with uneven distribution towards poles and steep mountain regions. The study provides a basis for future modeling of debris impact on ice and can inform monitoring efforts to mitigate effects on water resources.
The study proposes a three-tier architecture based on an ant colony algorithm to improve Cloud performance, reducing response time and cost.
A new technology, Sprocket, enables fast video processing by breaking down files into small pieces and processing them on thousands of servers. This reduces processing time to seconds, making it ideal for image searches within videos.
Researchers at University at Buffalo School of Management developed a new algorithm to establish pricing and allocate resources for cloud computing. The study provides practical formulas that companies can use to determine necessary resources and set charges for their customers.
The UTSA Open Cloud Institute is supporting collaborative R&D partnerships and creating educational opportunities through a $200,000 grant program. The institute is also launching a graduate-level certificate program in cloud computing to incorporate cloud expertise into engineering, computer science, and cybersecurity degrees.