A groundbreaking algorithm that significantly reduces communication time and message size in distributed machine learning, ensuring fast and reliable model convergence.

Brief description not available

Innovative methods and devices for improving error correction and reducing repair bandwidth in distributed systems using enhanced Reed-Solomon codes.

This technology enhances indoor pedestrian localization accuracy using LTE signals by mitigating multipath errors through synthetic aperture navigation.

An innovative approach to indoor localization using LTE signals and IMU data, enhancing accuracy and reliability for navigation.

An innovative approach to vehicle localization and mapping using lidar and cellular LTE data, enhancing accuracy without relying on GNSS signals.

This technology offers a novel approach to navigation by using LTE signals, providing a viable alternative to traditional GPS systems.

The DDFB laser introduces a novel feedback mechanism for enhanced frequency selectivity and stability in laser oscillation.

This technology introduces a revolutionary receiver architecture capable of demodulating high-order QAM signals without the need for high-speed analog-to-digital converters (ADCs), significantly enhancing communication speed and efficiency.

This technology introduces an advanced scheduling strategy for optimizing multi-model AI workloads on heterogeneous chiplet-based multi-chip modules (MCMs), aiming at maximizing performance efficiency.

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This technology revolutionizes health monitoring by integrating smart textiles with body area networks for real-time biometric data collection.

Metadata is used to summarize basic information about data that can make tracking and working with specific data easier. Today’s communication systems, like WhatsApp, iMessage, and Signal, use end-to-end encryption to protect message contents. Such communication systems do not hide metadata, which is the data providing information about one or more aspects of such contents, like messages. Such metadata includes information about who communicates with whom, when, and how much, and is generally visible to systems and network observers. As a result, cyber risk associated with metadata leakage and traffic analysis remains a significant attack vector in such modern communication systems. Previous attempts to address this risk have been generally seen as not secure or prohibitively expensive, for example, by imposing inflexible bandwidth restrictions and cumbersome synchronous schedules globally, which cripples performance. Moreover, prior approaches relied on distributed trust for security, which is largely incompatible with conventional organizations hosting or using such apps.

Many people have learned to appreciate the advent of GPS based navigational applications in our daily lives through the use of street level navigation, and many more loathe the same applications when using them to navigate established public transportation systems. Many of these travelers become confused and frustrated when attempting to understand and act on the directions given to them by such existing applications that primarily focus on large-scale street navigation, especially if the user has a visual or cognitive impairment. Several existing applications will not even attempt to aid someone in the navigation of say, a metro, train or bus station, and instead simply inform the user of the label of the route that the application intends the user to take. Without any small-scale directions many people find themselves struggling to figure out what platform or boarding zone they need to use to get on their preferred method of transportation, as well as how to get to these platforms and boarding zones in the first place. These transit hubs, plazas, malls, and the like have long been a pain in the side of developers and users alike when it comes to navigation. Innovation has long been overdue in this space concerning small scale transit plaza navigation, with major players holding large market shares in navigation not even attempting to address this longstanding problem. The only existing application to offer indoor navigation offers very limited as well as inconsistent functionality including only two-dimensional indoor mapping, due to manually uploaded floor plans that are only available in the first place from partnering locations. This has continued to be an issue due to a lack of adoption by existing locations, as each location is required to draw out their floor plan on an antiquated image file and submit it for approval. Solving this problem would ease a large amount of stress for those navigating in areas they are not familiar with, as well as saving time that could possibly make the difference between a missed train and a nearly missed train.

It is well known that the communication capacity of wireless networks is limited by interference. Depending on the strength of the interference, there are three conventional approaches to this problem. If the interference is very strong, then the receiver can decode the interfering signal and subtract from the desired signal using successive interference cancelation. If the interference signal is very weak compared to the desired signal, it can be treated as noise. The third and most common possibility is when the interference is comparable with the desired signal. In this case the interference can be avoided by orthogonalizing it with the desired signal using techniques such as time division multiple access (TDMA) or frequency division multiple access (FDMA). In addition to interference, wireless networks also experience channel fading. Conventional approaches to wireless networking attempt to combat fading. Depending on the coherence time of the fading, various approaches have been used. For example, fast fading may be mitigated by the use of diversity techniques, interleaving, and error-correcting codes. Certain diversity techniques, such as the use of multiple antennas, has been shown to help combat fading as well as increase multiplexing gain and system capacity. Multiuser diversity scheme is a technique to increase the capacity of wireless networks using multiple antennas at the base station. In this approach the base station selects a mobile device that has the best channel condition, maximizing the signal-to-noise ratio (SNR). According to some implementations of this approach, K random beams are constructed and information is transmitted to the users with the highest signal-to-noise plus interference ratio (SINR). Searching for the best SINR in the network, however, requires feedback from the mobile devices that scales linearly with the number of users. These implementations also use beamforming, which is complex to implement. In addition, the cooperation requirement is substantial.

         Recent mass evacuation events, including the 2018 Camp Fire and 2023 Maui Fire, have demonstrated shortcomings in our communication abilities during natural disasters and emergencies. Individuals fleeing dangerous areas were unable to obtain fast or accurate information pertaining to open evacuation routes and faced traffic gridlocks, while nearby communities were unprepared for the emergent situation and influx of persons. Climate change is increasing the frequency, areas subject to, and risk-level associated with natural hazards, making effective communication channels that can operate when mobile network-based systems and electric distribution systems are compromised crucial.         To address this need UC Berkeley researchers have developed a mobile network-free communication system that can function during natural disasters and be adapted to most communication devices (mobile phones and laptops). The self-organized, mesh-based and low-power network is embedded into common infrastructure monitoring device nodes (e.g., pre-existing WSN, LoRa, and other LPWAN devices) for effective local communication. Local communication contains dedicated Emergency Messaging and “walkie-talkie” functions, while higher level connectivity through robust gateway architecture and data transmission units allows for real-time internet access, communication with nearby communities, and even global connectivity. The system can provide GPS-free position information using trilateration, which can help identify the location of nodes monitoring important environmental conditions or allowing users to navigate.

A major aim of the field of cryptography is to design cryptosystems that is both provably secure and practical. Symmetric-key (private-key) methods have traditionally been viewed as practical in terms of typically a smaller key size, which means less storage requirements, and also faster processing. This, however, opens the protocols up to certain vulnerabilities, such as brute-force attacks. To reduce risk, the cryptographic keys are made longer, which in turn adds overhead burden and makes the scheme less practical. One-time pad (OTP) is a symmetric-type encryption technique that cannot be cracked, but requires the use of a single-use pre-shared key that is larger than or equal to the size of the message being sent. In this technique, a plaintext is paired with a random secret key (also referred to as OTP). Asymmetric-type (public-key, asymptotic) frameworks use pairs of keys consisting of a public and private key, and these models depend heavily on the privacy of the non-public key. Asymmetric-based protocols are generally much slower than symmetric approaches in practice. Hypertext Transfer Protocol Secure (HTTPS) protocol which is the backbone of internet security uses the Transport Layer Security (TLS) protocol stack in Transmission Control Protocol / Internet Protocol (TCP/IP) for secure and private data transfer. TLS is a protocol suite that uses a myriad of other protocols to guarantee security. Many of these subprotocols consume a lot of CPU power and are complex processes which are not optimized for big data applications. TLS uses public-key cryptography paradigms to exchange the keys between the communicating parties through the TLS handshake protocol. Unfortunately, traditional cryptographic algorithms and protocols (including schemes above and incorporating TLS, RSA, and AES) are not well suited in big data applications, as they need to perform a significant number of computations in practice. In turn, cloud providers face increasing CPU processing times and power usage to appropriately maintain services. In the modern computing era with quantum architecture and increased access to network and cloud resources, the speed and integrity of such outmoded cryptographic models will be put to the test.

Since the advent of asynchronous packet-based networks in communication and information technology, the topic of clock synchronization has received significant attention due to the temporal requirements of packet-based networks for the exchange of information. In more recent years, as distributed packet-based networks have evolved in terms of size, complexity, and, above all, application scope, there has been a growing need for new clock synchronization schemes with tractable design conditions to meet the demands of these evolving networks. Distributed applications such as robotic swarms, automated manufacturing, and distributed optimization rely on precise time synchronization among distributed agents for their operation. For example, in the case of distributed control and estimation over networks, the uncertainties of packet-based network communication require timestamping of sensor and actuator messages in order to synchronize the information to the evolution of the dynamical system being controlled or estimated. Such a scenario is impossible without the existence of a common timescale among the non-collocated agents in the system. In fact, the lack of a shared timescale among the networked agents can result in performance degradation that can destabilize the system. Moreover, one cannot always assume that consensus on time is a given, especially when the network associated to the distributed system is subject to perturbations such as noise, delay, or jitter. Hence, it is essential that these networked systems utilize clock synchronization schemes that establish and maintain a common timescale for their algorithms. With the arrival of more centralized protocols came motivated leader-less, consensus-based approaches by leveraging the seminal results on networked consensus in (e.g., Cao et al. 2008). More recent approaches (Garone et al. 2015, Kikuya et al. 2017) employ average consensus to give asymptotic results on clock synchronization under asynchronous and asymmetric communication topology. Unfortunately, a high number of iterations of the algorithm is often required before the desired synchronization accuracy is achieved. Furthermore, the constraint on asymmetric communication precludes any results guaranteeing stability or robustness. Lastly, these approaches suffer from over-complexity in term of both computation and memory allocation. Moreover, both synchronous and asynchronous scenarios require a large number of iterations before synchronization is achieved. Finally, the algorithm subjects the clocks to significant non-smooth adjustments in clock rate and offset that may prove undesirable in certain application settings.

A major aim of the field of cryptography is to design cryptosystems that is both provably secure and practical. Symmetric-key (private-key) methods have traditionally been viewed as practical in terms of typically a smaller key size, which means less storage requirements, and also faster processing. This, however, opens the protocols up to certain vulnerabilities, such as brute-force attacks. To reduce risk, the cryptographic keys are made longer, which in turn adds overhead burden and makes the scheme less practical. One-time pad (OTP) is a symmetric-type encryption technique that cannot be cracked, but requires the use of a single-use pre-shared key that is larger than or equal to the size of the message being sent. In this technique, a plaintext is paired with a random secret key (also referred to as OTP). Asymmetric-type (public-key, asymptotic) frameworks use pairs of keys consisting of a public and private key, and these models depend heavily on the privacy of the non-public key. Asymmetric-based protocols are generally much slower than symmetric approaches in practice. Hypertext Transfer Protocol Secure (HTTPS) protocol which is the backbone of internet security uses the Transport Layer Security (TLS) protocol stack in Transmission Control Protocol / Internet Protocol (TCP/IP) for secure and private data transfer. TLS is a protocol suite that uses a myriad of other protocols to guarantee security. Many of these subprotocols consume a lot of CPU power and are complex processes which are not optimized for big data applications. TLS uses public-key cryptography paradigms to exchange the keys between the communicating parties through the TLS handshake protocol. Unfortunately, traditional cryptographic algorithms and protocols (including schemes above and incorporating TLS, RSA, and AES) are not well suited in big data applications, as they need to perform a significant number of computations in practice. In turn, cloud providers face increasing CPU processing times and power usage to appropriately maintain services. In the modern computing era with quantum architecture and increased access to network and cloud resources, the speed and integrity of such outmoded cryptographic models will be put to the test.

A major aim of the field of cryptography is to design cryptosystems that is both provably secure and practical. Symmetric-key (private-key) methods have traditionally been viewed as practical in terms of typically a smaller key size, which means less storage requirements, and also faster processing. This, however, opens the protocols up to certain vulnerabilities, such as brute-force attacks. To reduce risk, the cryptographic keys are made longer, which in turn adds overhead burden and makes the scheme less practical. One-time pad (OTP) is a symmetric-type encryption technique that cannot be cracked, but requires the use of a single-use pre-shared key that is larger than or equal to the size of the message being sent. In this technique, a plaintext is paired with a random secret key (also referred to as OTP). Asymmetric-type (public-key, asymptotic) frameworks use pairs of keys consisting of a public and private key, and these models depend heavily on the privacy of the non-public key. Asymmetric-based protocols are generally much slower than symmetric approaches in practice. Hypertext Transfer Protocol Secure (HTTPS) protocol which is the backbone of internet security uses the Transport Layer Security (TLS) protocol stack in Transmission Control Protocol / Internet Protocol (TCP/IP) for secure and private data transfer. TLS is a protocol suite that uses a myriad of other protocols to guarantee security. Many of these subprotocols consume a lot of CPU power and are complex processes which are not optimized for big data applications. TLS uses public-key cryptography paradigms to exchange the keys between the communicating parties through the TLS handshake protocol. Unfortunately, traditional cryptographic algorithms and protocols (including schemes above and incorporating TLS, RSA, and AES) are not well suited in big data applications, as they need to perform a significant number of computations in practice. In turn, cloud providers face increasing CPU processing times and power usage to appropriately maintain services. In the modern computing era with quantum architecture and increased access to network and cloud resources, the speed and integrity of such outmoded cryptographic models will be put to the test.

Networks of connectivity-enabled devices, known as internet of things or IoT, involve interrelated devices that connect and exchange data with other IoT devices and the cloud. As the number of IoT devices and their applications continue to significantly increase, managing and administering edge and access networks have become increasingly more challenging. Currently, there are approximately 31 billion ‘‘things’’ connected to the internet, with a projected rise to 75 billion devices by 2025. Because of IoT interconnectivity and ubiquitous device use, assessing the risks, designing/specifying what’s reasonable, and implementing controls can be overwhelming to conventional frameworks. Any approach to better IoT network security, for example by improved detection and denial or restriction of access by unauthorized devices, must consider its impact on performance such as speed, power use, interoperability, and scalability. The IoT network’s physical and MAC layers are not impenetrable and have many known threats, especially identity-based attacks such as MAC spoofing events. Common network infrastructure uses WPA2 or IEEE 802.11i to help protect users and their devices and connected infrastructure. However, the risk of MAC spoofing remains, as bad actors leverage public tools on 802.11 commodity hardware, or intercept sensitive data packets at scale, to access users physical layer data, and can lead to wider tampering and manipulation of hardware-level parameters.

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The exchange of information among nodes in a communications network is based upon the transmission of discrete packets of data from a transmitter to a receiver over a carrier according to one or more of many well-known, new or still developing protocols. In this context, a protocol consists of a set of rules defining how the nodes interact with each other based on information sent over the communication links. Often, multiple nodes will transmit a packet at the same time and a collision occurs. During a collision, the packets are disrupted and become unintelligible to the other devices listening to the carrier activity. In addition to packet loss, network performance is greatly impacted. The delay introduced by the need to retransmit the packets cascades throughout the network to the other devices waiting to transmit over the carrier. Therefore, packet collision has a multiplicative effect that is detrimental to communications networks. As a result, multiple international protocols have been developed to address packet collision, including collision detection and avoidance. Within the context of wired Ethernet networks, the issue of packet collision has been largely addressed by network protocols that try to detect a packet collision and then wait until the carrier is clear to retransmit. Emphasis is placed in collision detection, i.e., a transmitting node can determine whether a collision has occurred by sensing the carrier. At the same time, the nature of wireless networks prevents wireless nodes from being able to detect a collision. This is the case, in part, because in wireless networks the nodes can send and receive but cannot sense packets traversing the carrier after the transmission has started. Another problem arises when two transmitting nodes are out of range of each other, but the receiving node is within range of both. In this case, a transmitting node cannot sense another transmitting node that is out of communications range. IEEE 802.11 protocols are the basis for wireless network products using the Wi-Fi brand and are the world's most widely used wireless computer networking standards. With IEEE 802.11 packet collision features come deficiencies, like fairness. 802.11’s approach to certain parameters after each successful transmission may cause the node who succeeds in transmitting to dominate the channel for an arbitrarily long period of time. As a result, other nodes may suffer from severe short-term unfairness. Also, the current state of the network (e.g., load) is something that also should be factored. In general, there is a need for techniques to recognize network patterns and determine certain parameters that are responsive to those network patterns.

Silicon photonics is increasingly used in an array of communications and computing applications. In many applications, photonic chips must be coupled to optical fibers, which remains challenging due to the size mismatch between the on-chip photonics and the fiber itself. Existing approaches suffer from low alignment tolerance, sensitivity to fabrication variations, and complex processing, all of which hinder mass manufacture.To address these problems, researchers at UC Berkeley have developed a coupling mechanism between a silicon integrated photonic circuit and an optical fiber which uses a microlens to direct and collimate light into the fiber. Researchers have demonstrated that this device can achieve low coupling loss at large alignment tolerances, with an efficient and scalable manufacturing process analogous to existing manufacture of electronic integrated circuits. In particular, because the beam is directed above the silicon chip, this method obviates dry etching or polishing of the edge of the IC and allows the silicon photonics to be produced by dicing in much the same way as present electronic integrated circuits.

In most wireless ad-hoc multi-hop networks, a node competes for access to the same wireless communication channel, often resulting in collisions (interference) and ineffective carrier sensing. These issues have been targeted through the medium access control (MAC) interconnection layer by a variety of channel access schemes, towards improving how the nodes share the wireless channel and achieve a high quality of service. For example, there are contention-based MAC schemes, like Carrier-Sense Multiple Access (CSMA) and Additive Links On-Line Hawaii Area (ALOHA), and contention-free MAC schemes, like time division multiplexing access (TDMA). However, the former is a poor performer in hidden- and exposed-terminal environments, and the latter, where the node system is time-synchronized and the time frame is divided and multiple time-slots are allocated to the nodes, has limited data rates (bandwidth) and undesirable latency. Over the years, there have been many other MAC schemes that address interference and conflict, as well as improving criteria like throughput, fairness, latency, energy, and overhead. These modern protocols implement more sophisticated distributed transmission queues consisting of a sequence of transmission turns that grows and shrinks on demand. However, challenges remain in these more recent MAC protocols, such as long delays for allowing nodes to join the network, and/or the use of transmission frames with complex structures to allocate time slot portions to signaling packets for elections.