arXiv subjects

Jing Fu

Publications and source records attributed to Jing Fu.

29 records · Page 2Linked to original sources

arXiv2023

A Study of a Loss System with Priorities

The Erlang loss formula, also known as the Erlang B formula, has been known for over a century and has been used in a wide range of applications, from telephony to hospital intensive care unit management. It provides the blocking probability of arriving customers to a loss system involving a finite number of servers without a waiting room. Because of the need to introduce priorities in many services, an extension of the Erlang B formula to the case of a loss system with preemptive priority is valuable and essential. This paper analytically establishes the consistency between the global balance (steady state) equations for a loss system with preemptive priorities and a known result obtained using traffic loss arguments for the same problem. This paper, for the first time, derives this known result directly from the global balance equations based on the relevant multidimensional Markov chain. The paper also addresses the question of whether or not the well-known insensitivity property of the Erlang loss system is also applicable to the case of a loss system with preemptive priorities, provides explanations, and demonstrates through simulations that, except for the blocking probability of the highest priority customers, the blocking probabilities of the other customers are sensitive to the holding time distributions and that a higher variance of the service time distribution leads to a lower blocking probability of the lower priority traffic.

math.PR↗

arXiv2023

Nanoscale Analysis of Frozen Water by Atom Probe Tomography Using Graphene Encapsulation and Cryo-Workflows: A Parametric Study

There has been an increasing interest in atom probe tomography (APT) to characterise hydrated and biological materials. A major benefit of APT compared to microscopy techniques more commonly used in biology is its combination of outstanding 3D spatial resolution (~0.2 nm) and mass sensitivity. APT has already been successfully used to characterise biological materials, revealing key structural information at the atomic scale, however there are many challenges inherent to the analysis of hydrated materials. New preparation protocols, often involving sample preparation and transfer at cryogenic temperature, enable APT analysis of hydrated materials and have the potential to enable 3D atomic scale characterisation of biological materials in the near-native hydrated state. In this study, APT specimens of pure water at the tips of tungsten needles were prepared at room temperature by graphene encapsulation. A parametric study was conducted where samples were transferred at either room temperature or cryo-temperature and analysed by APT by varying parameters such as the flight path and pulsing mode. The differences between the acquisition scenarios are presented along with recommendations for future studies.

physics.app-ph↗

arXiv2023

A Restless Bandit Model for Energy-Efficient Job Assignments in Server Farms

We aim to maximize the energy efficiency, gauged as average energy cost per job, in a large-scale server farm with various storage or/and computing components modeled as parallel abstracted servers. Each server operates in multiple power modes characterized by potentially different service and energy consumption rates. The heterogeneity of servers and multiple power modes complicate the maximization problem, where optimal solutions are generally intractable. Relying on the Whittle relaxation technique, we resort to a near-optimal, scalable job-assignment policy. Under a mild condition related to the service and energy consumption rates of the servers, we prove that our proposed policy approaches optimality as the size of the entire system tends to infinity; that is, it is asymptotically optimal. For the non-asymptotic regime, we show the effectiveness of the proposed policy through numerical simulations, where the policy outperforms all the tested baselines, and we numerically demonstrate its robustness against heavy-tailed job-size distributions.

math.OC↗

arXiv2023

Combinatorial-restless-bandit-based Transmitter-Receiver Online Selection for Distributed MIMO Radars With Non-Stationary Channels

We track moving targets with a distributed multiple-input multiple-output (MIMO) radar, for which the transmitters and receivers are appropriately paired and selected with a limited number of radar stations. We aim to maximize the sum of the signal-to-interference-plus-noise ratios (SINRs) of all the targets by sensibly selecting the transmitter-receiver pairs during the tracking period. A key is to model the optimization problem of selecting the transmitter-receiver pairs by a restless multi-armed bandit (RMAB) model that is able to formulate the time-varying signals of the transceiver channels whenever the channels are being probed or not. We regard the estimated mean reward (i.e., SINR) as the state of an arm. If an arm is probed, the estimated mean reward of the arm is the weighted sum of the observed reward and the predicted mean reward; otherwise, it is the predicted mean reward. We associate the predicted mean reward with the estimated mean reward at the previous time slot and the state of the target, which is estimated via the interacting multiple model-unscented Kalman filter (IMM-UKF). The optimized selection of transmitter-receiver pairs at each time is accomplished by using Binary Particle Swarm Optimization (BPSO) based on indexes of arms, each of which is designed by the upper confidence bound (UCB1) algorithm. Above all, a multi-group combinatorial-restless-bandit technique taking into account of different combinations of transmitters and receivers and the closed-loop scheme between transmitter-receiver pair selection and target state estimation, namely MG-CRB-CL, is developed to achieve a near-optimal selection strategy and improve multi-target tracking performance. Simulation results for different scenarios are provided to verify the effectiveness and superior performance of our MG-CRB-CL algorithm.

eess.SY↗

arXiv2022

Substrate-mediated Borophane Polymorphs through Hydrogenation of Two-dimensional Boron Sheets

Two-dimensional boron monolayer (borophene) stands out from the two-dimensional atomic layered materials due to its structural flexibility, tunable electronic and mechanical properties from a large number of allotropic materials. The stability of pristine borophene polymorphs could possibly be improved via hydrogenation with atomic hydrogen (referred to as borophane). However, the precise adsorption structures and the underlying mechanism are still elusive. Employing first-principles calculations, we demonstrate the optimal configurations of freestanding borophanes and the ones grown on metallic substrates. For freestanding β12 and χ3 borophenes, the energetically favored hydrogen adsorption sites are on the top of the boron atoms with CN=4 (CN: coordination number), while the best absorption sites for α' borophene are on the top of the boron atoms with CN=6. With various metal substrates, the hydrogenation configurations of borophene are modulated significantly, attributed to the chemical hybridization strength between B pz and H s orbitals. These findings provide a deep insight into the hydrogenating borophenes and facilitate the stabilization of two-dimensional boron polymorphs by engineering hydrogen adsorption sites and concentrations.

cond-mat.mtrl-sci↗

arXiv2022

Energy Efficient Priority-Based Task Scheduling for Computation Offloading in Fog Computing

Fog computing offers a flexible solution for computational offloading for Internet of Things (IoT) services at the edge of wireless networks. It serves as a complement to traditional cloud computing, which is not cost-efficient for most offloaded tasks in IoT applications involving small-to-medium levels of computing tasks. Given the heterogeneity of tasks and resources in fog computing, it is vital to offload each task to an appropriate destination to fully utilize the potential benefit of this promising technology. In this paper, we propose a scalable priority-based index policy, referred to as the Prioritized Incremental Energy Rate (PIER), to optimize the energy efficiency of the network. We demonstrate that PIER is asymptotically optimal in a special case applicable for local areas with high volumes of homogeneous offloaded tasks and exponentially distributed task durations. In more general cases with statistically different offloaded tasks, we further demonstrate the improvement of PIER over benchmark policies in terms of energy efficiency and the robustness of PIER to different task duration distributions by extensive simulations. Our results show that PIER can perform better than benchmark policies in more than 78.6% of all simulation runs.

math.OC↗

arXiv2020

Graphene nanopipette enabled liquid delivery at zeptoliter precision

Accurate extraction of liquid is the first step towards low-volume liquid delivery and nanocharacterization, which plays a significant role in biomedical research. In this study, a tip-shaped graphene nanopipette (GNP) is proposed by encapsulating the biomolecule solution on the prefabricated metal tip with graphene. The volume of the encapsulated liquid is highly controllable at zeptoliter precision by tuning the encapsulating speed and the number of graphene encapsulation rounds. Using protein (ferritin) solution as an example, it has been confirmed by finite element analysis and the controlled experiments that the GNP allows the delivery of ferritin solution at the zeptoliter-scale. Furthermore, GNP is demonstrated as a new type of tip-shaped liquid cell, which is suitable for multiple nanocharacterization techniques. In particular, due to the ultra-sharp tip shape, isotope (13C)-labelled glucose solution encapsulated in GNP has been characterized by atom probe tomography (APT) in the laser-pulsed mode. Analysis of the mass spectrum and the reconstructed three-dimensional chemical maps reveals the quantitative distribution and the compositions of individual glucose molecules. The GNP is expected to be introduced to deliver liquid in the range of zeptoliters to attoliters, and brings a new capability for characterization of biological specimens in their near-native state.

physics.app-ph↗

arXiv2020

Direct imaging of liquid-nanoparticle interface with atom probe tomography

Understanding the structure and chemical composition at the liquid-nanoparticle (NP) interface is crucial for a wide range of physical, chemical and biological processes. In this study, direct imaging of the liquid-NP interface by atom probe tomography (APT) is reported for the first time, which reveals the distributions and the interactions of key atoms and molecules in this critical domain. The APT specimen is prepared by controlled graphene encapsulation of the solution containing nanoparticles on a metal tip, with an end radius in the range of 50 nm to allow field ionization and evaporation. Using Au nanoparticles (AuNPs) in suspension as an example, analysis of the mass spectrum and three-dimensional (3D) chemical maps from APT provides a detailed image of the water-gold interface with near-atomic resolution. At the water-gold interface, the formation of an electrical double layer (EDL) rich in water (H2O) molecules has been observed, which results from the charge from the binding between the trisodium-citrate layer and the AuNP. In the bulk water region, the density of reconstructed H2O has been shown to be consistent, reflecting a highly packed density of H2O molecules after graphene encapsulation. This study is the first demonstration of direct imaging of liquid-NP interface using APT with results providing an atom-by-atom 3D dissection of the liquid-NP interface.

cond-mat.mtrl-sci↗

arXiv2020

A Restless Bandit Model for Resource Allocation, Competition and Reservation

We study a resource allocation problem with varying requests, and with resources of limited capacity shared by multiple requests. It is modeled as a set of heterogeneous Restless Multi-Armed Bandit Problems (RMABPs) connected by constraints imposed by resource capacity. Following Whittle's relaxation idea and Weber and Weiss' asymptotic optimality proof, we propose a simple policy and prove it to be asymptotically optimal in a regime where both arrival rates and capacities increase. We provide a simple sufficient condition for asymptotic optimality of the policy, and in complete generality propose a method that generates a set of candidate policies for which asymptotic optimality can be checked. The effectiveness of these results is demonstrated by numerical experiments. To the best of our knowledge, this is the first work providing asymptotic optimality results for such a resource allocation problem and such a combination of multiple RMABPs.

math.OC↗

arXiv2020

Energy-Efficient Job-Assignment Policy with Asymptotically Guaranteed Performance Deviation

We study a job-assignment problem in a large-scale server farm system with geographically deployed servers as abstracted computer components (e.g., storage, network links, and processors) that are potentially diverse. We aim to maximize the energy efficiency of the entire system by effectively controlling carried load on networked servers. A scalable, near-optimal job-assignment policy is proposed. The optimality is gauged as, roughly speaking, energy cost per job. Our key result is an upper bound on the deviation between the proposed policy and the asymptotically optimal energy efficiency, when job sizes are exponentially distributed and blocking probabilities are positive. Relying on Whittle relaxation and the asymptotic optimality theorem of Weber and Weiss, this bound is shown to decrease exponentially as the number of servers and the arrival rates of jobs increase arbitrarily and in proportion. In consequence, the proposed policy is asymptotically optimal and, more importantly, approaches asymptotic optimality quickly (exponentially). This suggests that the proposed policy is close to optimal even for relatively small systems (and indeed any larger systems), and this is consistent with the results of our simulations. Simulations indicate that the policy is effective, and robust to variations in job-size distributions.

cs.DC↗

arXiv2020

Harmonic surface mapping algorithm for electrostatic potentials in an atomistic/continuum hybrid model for electrolyte solutions

Simulating charged many-body systems has been a computational demanding task due to the long-range nature of electrostatic interaction. For the multi-scale model of electrolytes which combines the strengths of atomistic/continuum electrolyte representations, a harmonic surface mapping algorithm is developed for fast and accurate evaluation of the electrostatic reaction potentials. Our method reformulates the reaction potential into a sum of image charges for the near-field, and a charge density on an auxiliary spherical surface for the far-field, which can be further discretized into point charges. Fast multipole method is used to accelerate the pairwise Coulomb summation. The accuracy and efficiency of our algorithm, as well as the choice of relevant numerical parameters are demonstrated in detail. As a concrete example, for charges close to the dielectric interface, our method can improve the accuracy by two orders of magnitudes compared to the Kirkwood series expansion method.

physics.comp-ph↗