Articles tagged with Computer Networking
Researchers at Rice University are developing novel computational approaches to track environmental microbiome dynamics over time, across species and after perturbations. The team will use biofilm-based 'species abundance networks' on scaffolds to observe how they form their own genome-exchange networks.
Lehigh University researcher Roberto Palmieri aims to make RDMA technology even faster by revisiting a long-held theory. His goal is to enable all machines to interact with local memory, reducing latency and improving performance.
Researchers aim to detect malware in IoT networked devices using a principled approach. They plan to develop resource-aware distributed malware detection and reliable feature extraction methods.
A study published in Proceedings of the National Academy of Sciences refutes the concept that a person's position within a network is crucial for information spread. Even with minimal advertising, the influence of individuals across the network becomes more equalized.
Researchers have improved Wi-Fi network operation and performance for the 5G/6G ecosystem by applying machine learning techniques. A new algorithm, ε-sticky, is proposed to reduce service disruptions and network instability, benefiting both stations that have found a suitable access point and those that haven't.
A new NIST formula could significantly improve Wi-Fi and cellular system performance in unlicensed bands by selecting optimal frequency channels. The formula uses machine learning to maximize data rates and reduce interference, with computer simulations showing it can outperform exhaustive trial-and-error methods.
Researchers at University of Waterloo have developed a novel approach called FLAIR, which optimizes data storage systems by utilizing all servers within a network. This leads to improved storage efficiency and output speed, resulting in faster data retrieval times up to 97%.
A team of researchers has developed a novel attack detection scheme that captures vulnerable communication links, allowing systems to react optimally even under attack. The approach uses an adaptive observer to detect the onset of attacks and learns how they disrupt the system, enabling it to perform better under duress.
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.
New research reveals that laptops and desktops are susceptible to hacking through common plug-in devices like chargers and docking stations. Attackers can compromise an unattended machine in seconds, taking complete control of the target computer.
A recent UCLA study found that artificial intelligence, specifically deep learning computer networks, have severe limitations in distinguishing objects. The researchers demonstrated that these machines can be easily fooled, and their method of identifying objects using computer vision differs substantially from human vision.
A tiny camera lens invented by ANU researchers may enable fast and reliable transfer of quantum information between quantum computers and an optical fibre network. The device uses a metasurface that controls light with functionalities outperforming traditional systems.
Akatosh, a new security analysis tool, provides deeper context to existing IT infrastructure, automating the process of sorting through intrusion detection system (IDS) alerts. This reduces the time and cost required to identify the source of a security incident and neutralize threats.
A new AI-based framework has been developed to create realistic textures in virtual worlds, addressing the challenge of designing complex and believable textures. The tool uses generative adversarial networks (GANs) to train computers to expand small textures into larger ones, resulting in efficient and realistic designs.
Researchers at Google DeepMind created a machine-learning system called Generative Query Network (GQN) that learns 3-D scene composition from limited 2-D images. The GQN can generate predicted images of unseen scenes from different viewpoints, allowing for autonomous learning without human supervision.
Researchers at Binghamton University are developing a micro-device using bio-photovoltaic technology to create self-sustaining wireless sensor networks. The project aims to harness energy from biological photosynthesis to improve wireless sensing and communication, with potential applications in various industries.
Professor Atiquzzaman, an international expert in satellite communications, receives the prestigious award for his research achievements in next-generation computer networks and wireless mobile networks.
A team of researchers from Cranfield University and Chinese institutions developed a framework combining cyber, physical, and social systems to integrate vehicle connectivity and automation attributes. They proposed the use of parallel learning theory to analyze information regarding vehicle, human driver, and driving actions in parallel.
Researchers at Georgia Institute of Technology develop 'Refinable Attack INvestigation' (RAIN) software to automate cyber attack investigation. The system provides a detailed record of intrusions, even if attackers covered their tracks, allowing investigators to quickly identify the extent and impact of network or computer system attacks.
Researchers at MIT and Cisco Systems have developed a new approach to network monitoring called Marple, which allows routers to report on their own state without relying on external servers. By using a programming language and simple circuit design, Marple enables precise traffic analysis while reducing the need for additional hardware.
Researchers at UTA have developed a mathematical solution to optimize computing and network resource allocation in data centers, ensuring better user experiences. The new grant will allow for the development of a user-context-aware joint computing-and-networking resource allocation framework.
A nationwide team of security experts, led by Clemson University's Hongxin Hu, is developing a new operating system to fundamentally change how large computer and network systems are built, making data more secure. The S2OS system could be transformative for cloud computing, protecting users' data from cyber threats.
A study at Aalto University aims to reduce societal polarization by connecting people with opposing views on Twitter. The algorithm suggests bridges between users of opposing sides, such as Hillary Clinton and Donald Trump, to provide recommendations about who to retweet.
Researchers propose a wireless monitoring system for detecting concrete damage using Electromechanical Impedance sensing approach. The proposed WiAMS system utilizes a credit card-sized Raspberry Pi single-board computer, enabling remote data transfer and processing.
Researchers created a computer defense system that senses possible malicious probes and redirects them to a virtual decoy network. This shadow network is isolated and can mimic the structure of an actual network to fool hackers.
Researchers develop new parallel-computing method using nanofabricated channels explored by protein filaments propelled by molecular motors, solving combinatorial problems in a dramatic improvement over conventional computers. The approach is fully scalable with existing technologies and uses orders of magnitude less energy.
A new antivirus add-on can scan across computer networks and trap malicious activity missed by system firewalls, offering improved protection against malware. The system adds little computing overhead and can block malware before it causes harm or spreads to other machines.
The RIT team's Meshed Tree Protocol aims to eliminate loops in network switching operations, reducing convergence time and improving cybersecurity. The protocol features four levels of security with different authentication and encryption methods.
A team of researchers at the University of Texas at Arlington has developed a genetic computer network model that can predict the onset of mental illnesses such as bipolar disorder and schizophrenia. The model uses single nucleotide polymorphism networks to analyze a patient's genetic pattern and apply personalized therapy.
Researchers at Washington State University have developed a wireless network on a computer chip that can reduce energy consumption in data farms. The technology allows for wireless links between cores, resulting in less energy loss and higher data transfer speed.
A UMD-led public computational biology web service, MolecularEvolution.org, has gained popularity by giving back to its users. The Lattice Project, built on the Berkeley Open Infrastructure for Network Computing, offers a service called GARLI, designed to reconstruct and predict genetic relationships between biological samples.
Researchers from Virginia Tech have developed a new security approach that detects stealthy malware in advance. By analyzing causal relations among computer network events, the system can effectively isolate infected hosts and prevent attacks.
Researchers found keywords in word networks that facilitate quick recognition of similar words, opening up potential applications for language disorders and learning. Removing keywords from memory could disrupt language processing.
Researchers have developed a new technique for addressing vertex-connectivity problems, which could lead to communications protocols that coax as much bandwidth as possible from networks. The approach is based on decomposing the network into connected dominating sets, allowing for faster information flow and increased robustness.
Researchers use existing IT infrastructure to monitor office occupancy and adjust temperature controls, reducing energy waste. The approach involves analyzing network addresses and device activity to estimate user locations, enabling more efficient heating and cooling systems.
Engineers at UC Berkeley created the first user-interactive sensor network on flexible plastic, responding to touch with instant light emission. The new e-skin technology has potential applications in robots, wallpapers, dashboard displays, and health monitors.
Danfeng Yao received a $450,000 grant from the Office of Naval Research (ONR) to develop quantitative anomaly detection methods for Department of Defense systems. The project aims to detect anomalies in computer programs, systems, and networks, enabling early detection and prevention of cyber attacks.
Marwan Krunz, a professor at the University of Arizona, has been named a distinguished lecturer by the Institute of Electrical and Electronics Engineers (IEEE) for his research on optimal resource allocation and adaptive control. He will share his expertise on dynamic spectrum access models to overcome wireless spectrum shortages.
The new dedicated network, Science DMZ, will enable WSU researchers to transmit and receive large amounts of data quickly, across the campus or around the world. This upgrade will greatly speed up their ability to work, moving research forward with faster downloads and improved collaboration.
Francois Baccelli, renowned French mathematician and engineer, joins The University of Texas at Austin as the first Simons Chair in Mathematics and Electrical and Computer Engineering. He brings a $1.5 million grant to establish a new Center in Information and Network Science.
Researchers at Kansas State University are developing a self-adapting computer network that can detect and defend itself against cyber attacks. The 'moving-target defense' system randomly changes its configuration to make it difficult for hackers to identify vulnerabilities.
A new data transmission approach developed by researchers at North Carolina State University can increase the amount of data transmitted in multi-hop wireless networks by 20-80%. The centrality-based power control algorithm optimizes system efficiency by determining when to use powerful transmissions and when to use less powerful ones.
Researchers at the University of Minnesota discovered that cell phone networks leak user locations, allowing hackers to track their movements. The team used inexpensive phones and open source software to demonstrate the vulnerability on the GSM network.
MIT researchers have developed a new security scheme that can automatically create connections between wireless devices and defend against man-in-the-middle (MITM) attacks. The scheme uses novel techniques to detect and prevent MITM attacks, making it stronger than previous solutions.
Researchers from North Carolina State University have developed a model that can find optimal fiber optic network connections significantly faster and more efficiently. The model breaks down the complex problem into smaller units, allowing for faster design and re-design cycles.
Researchers have developed a computer algorithm to identify and block distributed denial-of-service (DDoS) attacks on mobile ad hoc networks in under 22 seconds. The technique can halt 80% of attack traffic and provide a model framework for building better security systems.
Researchers at Carnegie Mellon University have discovered a biologically-inspired method to organize wireless sensor networks and distributed computing applications. Inspired by the fruit fly's nervous system, a new algorithm has been developed that can efficiently deploy sensors without advance knowledge of their connections.
A national pilot program utilizing a Carnegie Mellon-developed algorithm is matching living kidney donors with medically compatible transplant candidates. The initial run of the computer matching process successfully matched seven people in need of a kidney transplant with suitable donors, expanding kidney paired-donation transplants.
The WPI Center for Wireless Information Network Studies is conducting a groundbreaking study to develop standards for body area networks, which support various medical applications and can be used in health care, athletics, and other fields. The research aims to spur the growth of this technology and improve healthcare.
A researcher at Virginia Tech is developing a unified mathematical framework to study the spread of pandemics, malware, and power grid failures. The framework aims to improve robustness in healthcare, computer networking, and power grid controls, addressing concerns for workers and policy planners.
Researchers developed an algorithm to target local scanning worms, which can evade worm defenses. The algorithm estimates susceptible host population size and quarantines the worm if scans exceed a threshold value.
Researchers found that slime mold can self-organize into a nearly identical network to Tokyo's rail system, suggesting improved technological systems. The model captures the basic dynamics of network adaptability through interaction of local rules.
A new study reveals a more extensive valley network on Mars, indicating the presence of an ancient ocean. The findings suggest that rainfall and precipitation played a major role in shaping the Martian landscape.
A new computer security approach, called 'swarm intelligence,' uses digital ants to search for threats in large networks, adapting to changes and attracting human operators to investigate. This method promises to transform cyber security by rapidly responding to emerging threats and improving overall defense.
PortLand is a fault-tolerant, layer 2 data center network fabric capable of scaling to 100,000 nodes and beyond. It provides baseline support for virtual machines and migration while reducing administrative overhead, and leverages multipath routing and improved fault tolerance.
Researchers at UC San Diego are building low-cost, low-power modems for short-range underwater networking, enabling higher sampling rates and more frequent data collection. The project aims to create a network of underwater sensors that can provide real-time environmental data, revolutionizing the way we understand our natural world.
Researchers at University of California, Davis have developed a 2-pronged approach to ward off self-propagating infectious programs known as worms. The strategy enables computers to share information about anomalous activity and use an algorithm to weigh the cost of infection against the benefit of staying online.
Researchers at UC San Diego have proposed a new topology for Ethernet data center connectivity, enabling scalable interconnection bandwidth and reducing costs. The approach requires no modifications to end-host network interface, operating system, or applications, and is fully backward compatible with Ethernet, IP, and TCP.
The NIST model assigns a probable risk of attack to guide IT managers in securing their networks by analyzing all possible paths that system attackers could penetrate through. This allows decision makers to make wise decisions and investments to protect their network from data breaches.
A study published in PLOS ONE demonstrates that the spontaneous activity of small neuronal networks in the cortex consists of highly structured patterns rather than random noise. These patterns are shaped by network connectivity and can be used to inform researchers about the underlying anatomy.