arXiv subjects

Tianyi Yang

Publications and source records attributed to Tianyi Yang.

At least 55 records · Page 3Linked to original sources

arXiv2023

Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal Attention

Prompt and accurate detection of system anomalies is essential to ensure the reliability of software systems. Unlike manual efforts that exploit all available run-time information, existing approaches usually leverage only a single type of monitoring data (often logs or metrics) or fail to make effective use of the joint information among different types of data. Consequently, many false predictions occur. To better understand the manifestations of system anomalies, we conduct a systematical study on a large amount of heterogeneous data, i.e., logs and metrics. Our study demonstrates that logs and metrics can manifest system anomalies collaboratively and complementarily, and neither of them only is sufficient. Thus, integrating heterogeneous data can help recover the complete picture of a system's health status. In this context, we propose Hades, the first end-to-end semi-supervised approach to effectively identify system anomalies based on heterogeneous data. Our approach employs a hierarchical architecture to learn a global representation of the system status by fusing log semantics and metric patterns. It captures discriminative features and meaningful interactions from heterogeneous data via a cross-modal attention module, trained in a semi-supervised manner. We evaluate Hades extensively on large-scale simulated data and datasets from Huawei Cloud. The experimental results present the effectiveness of our model in detecting system anomalies. We also release the code and the annotated dataset for replication and future research.

cs.SE↗

arXiv2023

Eadro: An End-to-End Troubleshooting Framework for Microservices on Multi-source Data

The complexity and dynamism of microservices pose significant challenges to system reliability, and thereby, automated troubleshooting is crucial. Effective root cause localization after anomaly detection is crucial for ensuring the reliability of microservice systems. However, two significant issues rest in existing approaches: (1) Microservices generate traces, system logs, and key performance indicators (KPIs), but existing approaches usually consider traces only, failing to understand the system fully as traces cannot depict all anomalies; (2) Troubleshooting microservices generally contains two main phases, i.e., anomaly detection and root cause localization. Existing studies regard these two phases as independent, ignoring their close correlation. Even worse, inaccurate detection results can deeply affect localization effectiveness. To overcome these limitations, we propose Eadro, the first end-to-end framework to integrate anomaly detection and root cause localization based on multi-source data for troubleshooting large-scale microservices. The key insights of Eadro are the anomaly manifestations on different data sources and the close connection between detection and localization. Thus, Eadro models intra-service behaviors and inter-service dependencies from traces, logs, and KPIs, all the while leveraging the shared knowledge of the two phases via multi-task learning. Experiments on two widely-used benchmark microservices demonstrate that Eadro outperforms state-of-the-art approaches by a large margin. The results also show the usefulness of integrating multi-source data. We also release our code and data to facilitate future research.

cs.SE↗

arXiv2023

Truthful and Stable One-sided Matching on Networks

Mechanism design on social networks is a hot research direction recently, and we have seen many interesting results in auctions and matching. Compared to the traditional settings, the new goal of the network settings is that we need to design incentives to incentivize the participants of the game to invite their neighbors on the network to join the game. This is challenging because they are competing for something (e.g., resources or matches) in the game. In one-sided matching, especially house exchange, the well-known unique truthful, stable and optimal solution called Top Trading Cycle (TTC) cannot achieve the new goal. Existing works have tried to add constraints on TTC to obtain the incentive, but it only works in trees and it does not guarantee any stability. In this paper, we move this forward and propose the first mechanism called Leave and Share (LS) which not only achieves the goal in all networks but also gives the most stable solution in the new settings. In terms of optimality, as it is impossible to achieve it in any network, we conduct simulations to compare it with the extensions of TTC.

cs.GT↗

arXiv2023

FUSEE: A Fully Memory-Disaggregated Key-Value Store (Extended Version)

Distributed in-memory key-value (KV) stores are embracing the disaggregated memory (DM) architecture for higher resource utilization. However, existing KV stores on DM employ a semi-disaggregated design that stores KV pairs on DM but manages metadata with monolithic metadata servers, hence still suffering from low resource efficiency on metadata servers. To address this issue, this paper proposes FUSEE, a FUlly memory-diSaggrEgated KV StorE that brings disaggregation to metadata management. FUSEE replicates metadata, i.e., the index and memory management information, on memory nodes, manages them directly on the client side, and handles complex failures under the DM architecture. To scalably replicate the index on clients, FUSEE proposes a client-centric replication protocol that allows clients to concurrently access and modify the replicated index. To efficiently manage disaggregated memory, FUSEE adopts a two-level memory management scheme that splits the memory management duty among clients and memory nodes. Finally, to handle the metadata corruption under client failures, FUSEE leverages an embedded operation log scheme to repair metadata with low log maintenance overhead. We evaluate FUSEE with both micro and YCSB hybrid benchmarks. The experimental results show that FUSEE outperforms the state-of-the-art KV stores on DM by up to 4.5 times with less resource consumption.

cs.DC↗

arXiv2022

Report of the Topical Group on Electroweak Precision Physics and Constraining New Physics for Snowmass 2021

The precise measurement of physics observables and the test of their consistency within the standard model (SM) are an invaluable approach, complemented by direct searches for new particles, to determine the existence of physics beyond the standard model (BSM). Studies of massive electroweak gauge bosons (W and Z bosons) are a promising target for indirect BSM searches, since the interactions of photons and gluons are strongly constrained by the unbroken gauge symmetries. They can be divided into two categories: (a) Fermion scattering processes mediated by s- or t-channel W/Z bosons, also known as electroweak precision measurements; and (b) multi-boson processes, which include production of two or more vector bosons in fermion-antifermion annihilation, as well as vector boson scattering (VBS) processes. The latter categories can test modifications of gauge-boson self-interactions, and the sensitivity is typically improved with increased collision energy. This report evaluates the achievable precision of a range of future experiments, which depend on the statistics of the collected data sample, the experimental and theoretical systematic uncertainties, and their correlations. In addition it presents a combined interpretation of these results, together with similar studies in the Higgs and top sector, in the Standard Model effective field theory (SMEFT) framework. This framework provides a model-independent prescription to put generic constraints on new physics and to study and combine large sets of experimental observables, assuming that the new physics scales are significantly higher than the EW scale.

hep-ph↗

arXiv2022

Predicted superconductivity and superionic state in the electride Li$_5$N under high pressure

Recently, electrides have received increasing attention due to their multifunctional properties as superconducting, catalytic, insulating, and electrode materials, with potential to offer other performance and possess novel physical states. This work uncovers that Li$_5$N as an electride possess four novel physical states simultaneously: electride state, super-coordinated state, superconducting state, and superionic state. By obtaining high-pressure phase diagrams of the Li-N system at 150-350 GPa using a crystal structure search algorithm, we find that Li$_5$N can remain stable as P6/mmm structure and has a 14-fold super-coordination number, as verified by Bader charge and electron localization function analysis. Aditionally, we find that its superconducting transition temperature decreases continuously with increasing pressure, contrary to the behavior of most high-pressure superconducting materials. Its superconducting transition temperature reaches the highest among all known electride at 150 GPa (Tc = 48.97 K). Besides, Li$_5$N exhibits the superionic state at 3000 K, in which N atoms act like solid, while some Li atoms flow like liquid. The above results are further verified at a macroscopic level by using deep learning potential molecular dynamics simulations.

cond-mat.supr-con↗

arXiv2022

Understanding the relation between thermal Sunyaev-Zeldovich decrement and halo mass using the SIMBA and TNG simulations

The relation between the integrated thermal Sunyaev-Zeldovich (tSZ) $y$-decrement versus halo mass ($Y$--$M$) can potentially constrain galaxy formation models, if theoretical and observational systematics can be properly assessed. We investigate the $Y$--$M$ relation in the SIMBA and IllustrisTNG-100 cosmological hydrodynamic simulations, quantifying the effects of feedback, line-of-sight projection, and beam convolution. We find that SIMBA's AGN jet feedback generates strong deviations from self-similar expectations for the $Y$--$M$ relation, especially at $M_{500}<10^{13}M_{\odot}$. In SIMBA, this is driven by suppressed in-halo $y$ contributions owing to lowered halo baryon fractions. IllustrisTNG results more closely resemble SIMBA without jets. Projections of line-of-sight structures weaken these model differences slightly, but they remain significant -- particularly at group and lower halo masses. In contrast, beam smearing at $\textit{Planck}$ resolution makes the models indistinguishable, and both models appear to agree well with $\textit{Planck}$ data down to the lowest masses probed. We show that the arcminute resolution expected from forthcoming facilities would retain the differences between model predictions, and thereby provide strong constraints on AGN feedback.

astro-ph.CO↗

arXiv2022

A Universal Profile for Stacked Filaments from Cold Dark Matter Simulations

We study the stacked filaments connecting group-mass halo pairs, using dark-matter-only N-body simulations. We calculate the dark matter over-density profile of these stacked filaments at different redshifts as a function of the distance perpendicular to the filament axis. A four-parameter universal functional form, including three comoving scale radii and one amplitude parameter (core density), provides a good fit out to a radius of 20 cMpc/h for stacked filaments over a range of redshifts, lengths and masses. The scale radii are approximately independent of redshift but increase as power-laws with the comoving filament length. Lastly, we compare the scaling of the filament mass measured directly from the simulations to the predicted scaling from the halo-halo-matter three-point correlation function as a function of redshift and of the mass of the halo pairs. We find that both measured scalings are similar to, but somewhat shallower than the predictions, by 10% and 30%, respectively. These results provide a template to interpret present and upcoming observational results based on stacking, for example, weak lensing, thermal and kinetic Sunyaev-Zel'dovich, or X-ray observations.

astro-ph.CO↗

arXiv2022

Superconductivity and magnetism in compressed actinium-beryllium-hydrogen alloys

The discovery of new high-temperature superconductors is one of the most critical problems in materials, chemistry, and physics. This work systematically investigates fluorite-like structures of XBeH8 (X is Ac, Th, Pa, U, and Np) to gain physical insight into the pressure effects on the properties. Our results reveal that AcBeH8 and ThBeH8 are two potential high-temperature superconductors, where AcBeH8 reaching a superconducting transition temperature of 284.11 K at 150 GPa and even a value of 203.29 K at 50 GPa, ThBeH8 has Tc is 217.65 K at 200 GPa, and the predicted results provide strong candidates for achieving high temperature or even room temperature superconductivity. The analysis of pressure effects demonstrates unusual charge transfer and atomic structure in the system, with s-f migration in Ac/Th atoms and s-p migration in Be atoms, similar to the high-pressure behavior of alkaline earth metals. In the past long time, superconductivity and magnetism were considered unable to coexist. However, UBeH8 and NpBeH8 are two potential magnetic superconductors with maximum Tc of 60.70 and 107.18 K at 100 and 350 GPa, respectively, and Hubbard U calculations predict their magnetic moments with 1.52 to 1.90 and 2.49 to 2.92 muB at 0 K. The coexistence of magnetic and superconducting states may be attributed to the different sublattice actions.

cond-mat.supr-con↗

arXiv2022

Managing Service Dependency for Cloud Reliability: The Industrial Practice

Interactions between cloud services result in service dependencies. Evaluating and managing the cascading impacts caused by service dependencies is critical to the reliability of cloud systems. This paper summarizes the dependency types in cloud systems and demonstrates the design of the Dependency Management System (DMS), a platform for managing the service dependencies in the production cloud system. DMS features full-lifecycle support for service reliability (i.e., initial service deployment, service upgrade, proactive architectural optimization, and reactive failure mitigation) and refined characterization of the intensity of dependencies.

cs.DC↗

arXiv2022

Boosted tau lepton as a microscope and macroscope

Anomalies from the LHCb lepton flavour universality and Fermilab muon anomalous magnetic momentum, show tantalizing hints of possible new physics from the lepton sectors. Due to its large mass and shorter lifetime than muon, the tau lepton is believed to couple more to possible new physics beyond the standard model. Traditionally, tau leptons are probed through the decay products due to tau's short life time. On the other hand, at a high energy scale, a large fraction of tau leptons could be boosted to a much longer life time and fly a visible distance from several centimetres up to kilometer length scale, yet very informative to new physics beyond the standard model or high energy cosmic rays. In this article, we show unique yet promising tau physics by exploiting long-lived taus as a microscope or macroscope, to measure tau's anomalous magnetic momentum to an unprecedented level of accuracy and detect high energy cosmic neutrinos at the 1 TeV to 1 PeV scale, respectively.

hep-ph↗

arXiv2022

Design of a $μ$SR spectrometer with ultrahigh arrays at China Spallation Neutron Source

A new muon source has been proposed to conduct muon spin rotation/relaxation/resonance ($μ$SR) measurements at China Spallation Neutron Source (CSNS). Only 1 Hz of the CSNS proton beams (25 Hz in total) will be allocated for muon production. To make better use of muons in every pulse, an ultrahigh-array $μ$SR spectrometer (UHAM) with thousands of detector channels is under design. Due to such a high granularity of detectors, multiple counting events generated from particle scattering or spiral motions of positrons in a strong longitudinal field should be carefully considered in the design. Six different structures were modeled and simulated based on two types of angular orientations (parallel arrangement and pointing arrangement) and three kinds of spectrometer geometries (cylinder, cone and sphere). A quality factor, $Q$, was proposed to evaluate the performance of these structures by integrating their impacts on the overall asymmetry, the counting rate and the percentage of multiple counts. According to the simulation, the conical structure with detectors pointing to the sample has the highest $Q$ in both zero field and longitudinal field. The results also show that all kinds of structures cannot be operated under strong longitudinal fields with a strength over 2 T. The full simulation of a $μ$SR spectrometer can provide good guidance for the construction of the UHAM in the upcoming upgrade of CSNS.

physics.ins-det↗

arXiv2022

The physics case for a neutrino lepton collider in light of the CDF W mass measurement

We propose a neutrino lepton collider where the neutrino beam is generated from TeV scale muon decays. Such a device would allow for a precise measurement of the W mass based on single W production: nu l to W. Although it is challenging to achieve high instantaneous luminosity with such a collider, we find that a total luminosity of 0.1/fb can already yield competitive physics results. In addition to a W mass measurement, a rich variety of physics goals could be achieved with such a collider, including W boson precision measurements, heavy leptophilic gauge boson searches, and anomalous Znunu coupling searches. A neutrino lepton collider is both a novel idea in itself, and may also be a useful intermediate step, with less muon cooling required, towards the muon-muon collider already being pursued by the energy frontier community. A neutrino neutrino or neutrino proton collider may also be interesting future options for the high energy frontier.

hep-ph↗

arXiv2022

As-Li electrides under high pressure: superconductivity, plastic, and superionic states

Inorganic electrides are a new class of compounds catering to the interest of scientists due to the multiple usages exhibited by interstitial electrons in the lattice. However, the influence of the shape and distribution of interstitial electrons on physical properties and new forms of physical states are still unknown. In this work, crystal structure search algorithms are employed to explore the possibility of forming new electrides in the As-Li system, where interstitial electrons behave as 1D electron chains (1D electride) in Pmmm phase of AsLi$_7$ and transform into 0D electron clusters (0D electride) in P6/mmm phase at 80 GPa. The P6/mmm phase has relatively high superconductivity at 150 GPa (Tc=38.4K) than classical electrides, even at moderate pressure with Tc=16.6K. The novel superconducting properties are conjectured to be possibly due to three Van Hove singularities at the Fermi level. In addition, a Dirac cone in the band has been observed, expanding the sources of Dirac materials. The survival of AsLi$_7$ at room temperature is confirmed by molecular dynamics simulation at 300 K. At 1000 K, the As atoms in the system act like solid, while a portion of the Li atoms cycle around the As atoms, and another portion of the Li atoms flow freely like liquid, showing the novel physical phenomenon of the coexistence of the plastic and superionic states. This suggests that the superionic and plastic states cannot only be found in hydrides but also in the electride. Our results indicate that superconducting electride AsLi$_7$ with superionic and plastic states can exist in Earth's interior.

cond-mat.supr-con↗

arXiv2022

Characterizing and Mitigating Anti-patterns of Alerts in Industrial Cloud Systems

Alerts are crucial for requesting prompt human intervention upon cloud anomalies. The quality of alerts significantly affects the cloud reliability and the cloud provider's business revenue. In practice, we observe on-call engineers being hindered from quickly locating and fixing faulty cloud services because of the vast existence of misleading, non-informative, non-actionable alerts. We call the ineffectiveness of alerts "anti-patterns of alerts". To better understand the anti-patterns of alerts and provide actionable measures to mitigate anti-patterns, in this paper, we conduct the first empirical study on the practices of mitigating anti-patterns of alerts in an industrial cloud system. We study the alert strategies and the alert processing procedure at Huawei Cloud, a leading cloud provider. Our study combines the quantitative analysis of millions of alerts in two years and a survey with eighteen experienced engineers. As a result, we summarized four individual anti-patterns and two collective anti-patterns of alerts. We also summarize four current reactions to mitigate the anti-patterns of alerts, and the general preventative guidelines for the configuration of alert strategy. Lastly, we propose to explore the automatic evaluation of the Quality of Alerts (QoA), including the indicativeness, precision, and handleability of alerts, as a future research direction that assists in the automatic detection of alerts' anti-patterns. The findings of our study are valuable for optimizing cloud monitoring systems and improving the reliability of cloud services.

cs.SE↗

arXiv2021

Searching for heavy leptoquarks at a muon collider

The LHCb Collaboration recently gave an update on testing lepton flavour universality with $B^+ \rightarrow K^+ \ell^+ \ell^-$, in which a 3.1 standard deviations from the standard model prediction was observed. The g-2 experiment also reports a 3.3 standard deviations from the standard model on muon anomalous magnetic moment measurement. These deviations could be explained by introducing new particles including leptoquarks. In this paper, we show the possibility to search for heavy spin-1 leptoquarks at a future TeV scale muon collider by performing studies from three channels: 1) same flavour final states with either two bottom or two light quarks, 2) different flavour quark final states, and 3) a so-called "VXS" process representing the scattering between a vector boson and a leptoquark to probe the coupling between leptoquark and tau lepton. We conclude that a 3 TeV muon collider with $3~{ab^{-1}}$ of integrated luminosity is already sufficient to cover the leptoquark parameter space in order to explain the LHCb lepton flavour universality anomaly.

hep-ph↗

arXiv2021

AID: Efficient Prediction of Aggregated Intensity of Dependency in Large-scale Cloud Systems

Service reliability is one of the key challenges that cloud providers have to deal with. In cloud systems, unplanned service failures may cause severe cascading impacts on their dependent services, deteriorating customer satisfaction. Predicting the cascading impacts accurately and efficiently is critical to the operation and maintenance of cloud systems. Existing approaches identify whether one service depends on another via distributed tracing but no prior work focused on discriminating to what extent the dependency between cloud services is. In this paper, we survey the outages and the procedure for failure diagnosis in two cloud providers to motivate the definition of the intensity of dependency. We define the intensity of dependency between two services as how much the status of the callee service influences the caller service. Then we propose AID, the first approach to predict the intensity of dependencies between cloud services. AID first generates a set of candidate dependency pairs from the spans. AID then represents the status of each cloud service with a multivariate time series aggregated from the spans. With the representation of services, AID calculates the similarities between the statuses of the caller and the callee of each candidate pair. Finally, AID aggregates the similarities to produce a unified value as the intensity of the dependency. We evaluate AID on the data collected from an open-source microservice benchmark and a cloud system in production. The experimental results show that AID can efficiently and accurately predict the intensity of dependencies. We further demonstrate the usefulness of our method in a large-scale commercial cloud system.

cs.SE↗

arXiv2021

TOUR: Dynamic Topic and Sentiment Analysis of User Reviews for Assisting App Release

App reviews deliver user opinions and emerging issues (e.g., new bugs) about the app releases. Due to the dynamic nature of app reviews, topics and sentiment of the reviews would change along with app release versions. Although several studies have focused on summarizing user opinions by analyzing user sentiment towards app features, no practical tool is released. The large quantity of reviews and noise words also necessitates an automated tool for monitoring user reviews. In this paper, we introduce TOUR for dynamic TOpic and sentiment analysis of User Reviews. TOUR is able to (i) detect and summarize emerging app issues over app versions, (ii) identify user sentiment towards app features, and (iii) prioritize important user reviews for facilitating developers' examination. The core techniques of TOUR include the online topic modeling approach and sentiment prediction strategy. TOUR provides entries for developers to customize the hyper-parameters and the results are presented in an interactive way. We evaluate TOUR by conducting a developer survey that involves 15 developers, and all of them confirm the practical usefulness of the recommended feature changes by TOUR.

cs.SE↗