1,236 research outputs found
HTSC and FH_HTSC: XOR-based codes to reduce access latency in distributed storage systems
A massive distributed storage system is the foundation for big data operations. Access latency performance is a key metric in distributed storage systems since it greatly impacts user experience while existing codes mainly focus on improving performance such as storage overhead and repair cost. By generating parity nodes from parity nodes, in this paper we design new XOR-based erasure codes hierarchical tree structure code (HTSC) and high failure tolerant HTSC (FH_HTSC) to reduce access latency in distributed storage systems. By comparing with other popular and representative codes, we show that, under the same repair cost, HTSC and FH.HTSC codes can reduce access latency while maintaining favorable performance in other metrics. In particular, under the same repair cost, FH.HTSC can achieve lower access latency, higher or equal failure tolerance and lower computation cost compared with the representative codes while enjoying similar storage overhead. Accordingly, FH.HTSC is a superior choice for applications requiring low access latency and outstanding failure tolerance capability at the same time.postprin
Performance models of access latency in cloud storage systems
Access latency is a key performance metric for cloud storage systems and has great impact on user experience, but most papers focus on other performance metrics such as storage overhead, repair cost and so on. Only recently do some models argue that coding can reduce access latency. However, they are developed for special scenarios, which may not reflect reality. To fill the gaps between existing work and practice, in this paper, we propose a more practical model to measure access latency. This model can also be used to compare access latency of different codes used by different companies. To the best of our knowledge, this model is the first to provide a general method to compare access latencies of different erasure codes.postprin
Latency performance model of direct and k-access reads in distributed storage systems
2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS
Differentially Private Federated Clustering over Non-IID Data
In this paper, we investigate federated clustering (FedC) problem, that aims
to accurately partition unlabeled data samples distributed over massive clients
into finite clusters under the orchestration of a parameter server, meanwhile
considering data privacy. Though it is an NP-hard optimization problem
involving real variables denoting cluster centroids and binary variables
denoting the cluster membership of each data sample, we judiciously reformulate
the FedC problem into a non-convex optimization problem with only one convex
constraint, accordingly yielding a soft clustering solution. Then a novel FedC
algorithm using differential privacy (DP) technique, referred to as DP-FedC, is
proposed in which partial clients participation and multiple local model
updating steps are also considered. Furthermore, various attributes of the
proposed DP-FedC are obtained through theoretical analyses of privacy
protection and convergence rate, especially for the case of non-identically and
independently distributed (non-i.i.d.) data, that ideally serve as the
guidelines for the design of the proposed DP-FedC. Then some experimental
results on two real datasets are provided to demonstrate the efficacy of the
proposed DP-FedC together with its much superior performance over some
state-of-the-art FedC algorithms, and the consistency with all the presented
analytical results.Comment: 31 pages, 4 figures, 1 tabl
Privacy-preserving Federated Primal-dual Learning for Non-convex and Non-smooth Problems with Model Sparsification
Federated learning (FL) has been recognized as a rapidly growing research
area, where the model is trained over massively distributed clients under the
orchestration of a parameter server (PS) without sharing clients' data. This
paper delves into a class of federated problems characterized by non-convex and
non-smooth loss functions, that are prevalent in FL applications but
challenging to handle due to their intricate non-convexity and non-smoothness
nature and the conflicting requirements on communication efficiency and privacy
protection. In this paper, we propose a novel federated primal-dual algorithm
with bidirectional model sparsification tailored for non-convex and non-smooth
FL problems, and differential privacy is applied for strong privacy guarantee.
Its unique insightful properties and some privacy and convergence analyses are
also presented for the FL algorithm design guidelines. Extensive experiments on
real-world data are conducted to demonstrate the effectiveness of the proposed
algorithm and much superior performance than some state-of-the-art FL
algorithms, together with the validation of all the analytical results and
properties.Comment: 30 pages, 8 figure
Inelastic X-Ray Scattering Study of Exciton Properties in an Organic Molecular crystal
Excitons in a complex organic molecular crystal were studied by inelastic
x-ray scattering (IXS) for the first time. The dynamic dielectric response
function is measured over a large momentum transfer region, from which an
exciton dispersion of 130 meV is observed. Semiempirical quantum chemical
calculations reproduce well the momentum dependence of the measured dynamic
dielectric responses, and thus unambiguously indicate that the lowest Frenkel
exciton is confined within a fraction of the complex molecule. Our results
demonstrate that IXS is a powerful tool for studying excitons in complex
organic molecular systems. Besides the energy position, the IXS spectra provide
a stringent test on the validity of the theoretically calculated exciton wave
functions.Comment: 4 pages, 4 figure
Critical exponents of the two-layer Ising model
The symmetric two-layer Ising model (TLIM) is studied by the corner transfer
matrix renormalisation group method. The critical points and critical exponents
are calculated. It is found that the TLIM belongs to the same universality
class as the Ising model. The shift exponent is calculated to be 1.773, which
is consistent with the theoretical prediction 1.75 with 1.3% deviation.Comment: 7 pages, with 10 figures include
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