Packet scheduling strategies for emerging service models in the internet

Traditional as well as emerging new Internet applications such as video-conferencing and live multimedia broadcasts from Internet TV stations will rely on scheduling algorithms in switches and routers to meet a diversity of service requirements desired from the network. This dissertation focuses on four categories of service requirements that cover the vast majority of current as well as emerging new applications: best-effort service, guaranteed service (delay and bandwidth), controlled load service, and soft real-time service. For each of these service types, we develop novel packet scheduling strategies that achieve better performance and better fairness than existing strategies.Best-effort and guaranteed services: A fair packet scheduler designed for best- effort service can also be employed to achieve bandwidth and delay guarantees. This dissertation proposes a novel fair scheduling algorithm, called Greedy Fair Queueing (GrFQ),that explicitly incorporates the goal of achieving better fairness into the actions of the scheduler. A simplified version of the scheduler is also proposed for easier deployment in real networks. Controlled load service: This dissertation analyzes and defines requirements on packet schedulers serving traffic that request the controlled load service (part of the Integrated Services architecture). We then propose a novel scheduler, called the CL(®) scheduler, which provides service differentiation for aggregated traffic for controlled load service. The proposed scheduler satisfies the defined requirements with a very low processing complexity and without requiring per-flow management. Soft real-time service: We formally define the service requirements of soft real-time applications which have delay constraints but which can tolerate some packet losses. Two novel schedulers of different levels of complexity are proposed. These schedulers achieve better performance (lower overall loss rates) and better fairness than previously known schedulers.We adapt a metric used widely in economics, called the Gini index, to our purpose of evaluating the fairness achieved by our schedulers under real traffic conditions. The Gini index captures the instantaneous fairness achieved at most instants of time as opposed to previously used measures of fairness in the networking literature. Using real video, audio and gateway traffic traces, we show that the proposed schedulers achieve better performance and fairness characteristics than other known schedulers.Ph.D., Electrical Engineering -- Drexel University, 200

Cooperative Transmission for Underwater Acoustic Communications

Underwater acoustic channels normally have low data rate, long propagation delay, severe multipath effect, and time varying fading. Cooperative transmission is a new wireless communication technique in which diversity gain is achieved by utilizing relay nodes as virtual antennae. In this paper, we investigate cooperative transmission techniques for underwater acoustic communications. First, we study the performance of several cooperative transmission schemes, originally designed for radio communications, in an underwater scenario. Second, by taking advantage of the low propagation speed of sound, we design a new wave cooperative transmission scheme. In this scheme, the relay nodes amplify the signal received from the source node, and then forward the signal immediately to the destination. The goal is to alter the multipath effect at the receiver. Third, we derive the performance upper bound for the proposed wave cooperative transmission scheme. The simulation results show that the proposed wave cooperative transmission has significant advantages over the traditional direct transmission and the existing cooperative transmission schemes originally designed for radio wireless networks. ©2008 IEEE

HYPRO: A Hybridly Normalized Probabilistic Model for Long-Horizon Prediction of Event Sequences

In this paper, we tackle the important yet under-investigated problem of making long-horizon prediction of event sequences. Existing state-of-the-art models do not perform well at this task due to their autoregressive structure. We propose HYPRO, a hybridly normalized probabilistic model that naturally fits this task: its first part is an autoregressive base model that learns to propose predictions; its second part is an energy function that learns to reweight the proposals such that more realistic predictions end up with higher probabilities. We also propose efficient training and inference algorithms for this model. Experiments on multiple real-world datasets demonstrate that our proposed HYPRO model can significantly outperform previous models at making long-horizon predictions of future events. We also conduct a range of ablation studies to investigate the effectiveness of each component of our proposed methods.Comment: NeurIPS 2022 camera-read

HYBRID FINITE-DISCRETE ELEMENT MODELLING OF BLAST-INDUCED EXCAVATION DAMAGED ZONE IN THE TOP-HEADING OF DEEP TUNNELS

A hybrid finite-discrete element method (FEM/DEM) is introduced to model the excavation damage zone induced by blast in a deep tunnel. The key components of the hybrid finite-discrete element method, i.e. transition from continuum to discontinuum through fracture and fragmentation, and detonation-induced gas expansion and flow through fracturing rock, are introduced in detail. The stress and crack initiation and propagation of an uniaxial compression test is then modelled by the proposed method and compared with those well documented in literature to calibrate the hybrid FEM/DEM. The modelled stress-loading displacement curve presents a typical failure process of brittle materials. The calibrated method is then used to model the stress and crack initiation and propagation induced by blast for the last step of excavation in a deep tunnel. A separation contour, which connects the borehole through the radial cracks from each borehole, is observed during the excavation process. The newly formed tunnel wall is produced and the main components of excavation damage zone (EDZ) are obtained. Therefore, the proposed treatment has the capabilities of modelling blast-induced EDZ and rock failure process. It is concluded that the hybrid FEM/DEM is a valuable numerical tool for studying excavation damage zone in terms of crack initiation and propagation and stress distribution

Non-contact and label-free biomechanical imaging: Stimulated Brillouin microscopy and beyond

Brillouin microscopy based on spontaneous Brillouin scattering has emerged as a unique elastography technique because of its merit of non-contact, label-free, and high-resolution mechanical imaging of biological cell and tissue. Recently, several new optical modalities based on stimulated Brillouin scattering have been developed for biomechanical research. As the scattering efficiency of the stimulated process is much higher than its counterpart in the spontaneous process, stimulated Brillouin-based methods have the potential to significantly improve the speed and spectral resolution of existing Brillouin microscopy. Here, we review the ongoing technological advancements of three methods, including continuous wave stimulated Brillouin microscopy, impulsive stimulated Brillouin microscopy, and laser-induced picosecond ultrasonics. We describe the physical principle, the representative instrumentation, and biological application of each method. We further discuss the current limitations as well as the challenges for translating these methods into a visible biomedical instrument for biophysics and mechanobiology

The Benefit of Imitating Particular Individuals

Abstract We examined the benefits of different search strategies by testing four computational models. In one model, agents in a group always innovated. The other three models incorporated some mechanisms of imitation. In the second model, each agent imitated the best solution of a random other. In the third model, each agent followed preferential attachment and imitated the best solution of the agent that was asked by many agents. In the fourth model, each agent developed a familiarity with an agent based on how often it asked a certain agent, and imitated this agent. In two simulation studies, following the most popular or the most familiar agent resulted in a good compromise between efficiency and diversity in finding good solutions. People's desire to follow particular individuals may be a key to their adaptive behavior, allowing them to disseminate ideas efficiently while encouraging the exploration of new ideas

Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning

Large language models have shown astonishing performance on a wide range of reasoning tasks. In this paper, we investigate whether they could reason about real-world events and help improve the prediction performance of event sequence models. We design LAMP, a framework that integrates a large language model in event prediction. Particularly, the language model performs abductive reasoning to assist an event sequence model: the event model proposes predictions on future events given the past; instructed by a few expert-annotated demonstrations, the language model learns to suggest possible causes for each proposal; a search module finds out the previous events that match the causes; a scoring function learns to examine whether the retrieved events could actually cause the proposal. Through extensive experiments on several challenging real-world datasets, we demonstrate that our framework -- thanks to the reasoning capabilities of large language models -- could significantly outperform the state-of-the-art event sequence models.Comment: NeurIPS 2023 camera-read

Tunable Correlated Chern Insulator and Ferromagnetism in Trilayer Graphene/Boron Nitride Moir\'e Superlattice

Studies on two-dimensional electron systems in a strong magnetic field first revealed the quantum Hall (QH) effect, a topological state of matter featuring a finite Chern number (C) and chiral edge states. Haldane later theorized that Chern insulators with integer QH effects could appear in lattice models with complex hopping parameters even at zero magnetic field. The ABC-trilayer graphene/hexagonal boron nitride (TLG/hBN) moir\'e superlattice provides an attractive platform to explore Chern insulators because it features nearly flat moir\'e minibands with a valley-dependent electrically tunable Chern number. Here we report the experimental observation of a correlated Chern insulator in a TLG/hBN moir\'e superlattice. We show that reversing the direction of the applied vertical electric field switches TLG/hBN's moir\'e minibands between zero and finite Chern numbers, as revealed by dramatic changes in magneto-transport behavior. For topological hole minibands tuned to have a finite Chern number, we focus on 1/4 filling, corresponding to one hole per moir\'e unit cell. The Hall resistance is well quantized at h/2e2, i.e. C = 2, for |B| > 0.4 T. The correlated Chern insulator is ferromagnetic, exhibiting significant magnetic hysteresis and a large anomalous Hall signal at zero magnetic field. Our discovery of a C = 2 Chern insulator at zero magnetic field should open up exciting opportunities for discovering novel correlated topological states, possibly with novel topological excitations, in nearly flat and topologically nontrivial moir\'e minibands.Comment: 16 pages, 4 figures, and 2 extended figure