scholarly journals FO-Sketch: A Fast Oblivious Sketch for Secure Network Measurement Service in the Cloud

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 2020
Author(s):  
Lingtong Liu ◽  
Yulong Shen ◽  
Shuiguang Zeng ◽  
Zhiwei Zhang
Keyword(s):  
Large Scale ◽  
Heavy Traffic ◽  
Network Measurement ◽  
Third Party ◽  
Divide And Conquer ◽  
Security Requirements ◽  
Public Cloud ◽  
Cloud Infrastructure ◽  
Measurement Interval ◽  
Local Flow

Network measurements are the foundation for network applications. The metrics generated by those measurements help applications improve their performance of the monitored network and harden their security. As severe network attacks using leaked information from a public cloud exist, it raises privacy and security concerns if directly deployed in network measurement services in a third-party public cloud infrastructure. Recent studies, most notably OblivSketch, demonstrated the feasibility of alleviating those concerns by using trusted hardware and Oblivious RAM (ORAM). As their performance is not good enough, and there are certain limitations, they are not suitable for broad deployment. In this paper, we propose FO-Sketch, a more efficient and general network measurement service that meets the most stringent security requirements, especially for a large-scale network with heavy traffic volume and burst traffic. Let a mergeable sketch update the local flow statistics in each local switch; FO-Sketch merges (in an Intel SGX-created enclave) these sketches obliviously to form a global “one big sketch” in the cloud. With the help of Oblivious Shuffle, Divide and Conquer, and SIMD speedup, we optimize all of the critical routines in our FO-Sketch to make it 17.3x faster than a trivial oblivious solution. While keeping the same level of accuracy and packet processing throughput as non-oblivious Elastic Sketch, our FO-Sketch needs only ∼4.5 MB enclave memory space in total to record metrics and for PORAM to store the global sketch in the cloud. Extensive experiments demonstrate that, for the recommended setting, it takes only ∼ 0.6 s in total to rebuild those data during each measurement interval.

Container Orchestration With Cost-Efficient Autoscaling in Cloud Computing Environments

2020 ◽  
pp. 190-213
Author(s):  
Maria Rodriguez ◽  
Rajkumar Buyya
Keyword(s):  
Cluster Size ◽  
Large Scale ◽  
Management Approach ◽  
Public Cloud ◽  
Cloud Infrastructure ◽  
Initial Placement ◽  
Cloud Environments ◽  
Computing Environments ◽  
Cost Efficient ◽  
Container Orchestration

Containers are widely used by organizations to deploy diverse workloads such as web services, big data, and IoT applications. Container orchestration platforms are designed to manage the deployment of containerized applications in large-scale clusters. The majority of these platforms optimize the scheduling of containers on a fixed-sized cluster and are not enabled to autoscale the size of the cluster nor to consider features specific to public cloud environments. This chapter presents a resource management approach with three objectives: 1) optimize the initial placement of containers by efficiently scheduling them on existing resources, 2) autoscale the number of resources at runtime based on the cluster's workload, and 3) consolidate applications into fewer VMs at runtime. The framework was implemented as a Kubernetes plugin and its efficiency was evaluated on an Australian cloud infrastructure. The experiments demonstrate that a reduction of 58% in cost can be achieved by dynamically managing the cluster size and placement of applications.

scholarly journals Interactive Analytics for Very Large Scale Genomic Data

2015 ◽  
Author(s):  
Cuiping Pan ◽  
Nicole Deflaux ◽  
Gregory McInnes ◽  
Michael Snyder ◽  
Jonathan Bingham ◽  
...  
Keyword(s):  
Large Scale ◽  
Biological Function ◽  
Genomic Data ◽  
Biological Information ◽  
Data Handling ◽  
Public Cloud ◽  
Information Compression ◽  
Cloud Infrastructure ◽  
Global Alliance ◽  
Web Browser

Large scale genomic sequencing is now widely used to decipher questions in diverse realms such as biological function, human diseases, evolution, ecosystems, and agriculture. With the quantity and diversity these data harbor, a robust and scalable data handling and analysis solution is desired. Here we present interactive analytics using public cloud infrastructure and distributed computing database Dremel and developed according to the standards of Global Alliance for Genomics and Health, to perform information compression, comprehensive quality controls, and biological information retrieval in large volumes of genomic data. We demonstrate that such computing paradigms can provide orders of magnitude faster turnaround for common analyses, transforming long-running batch jobs submitted via a Linux shell into questions that can be asked from a web browser in seconds.

Public cloud computing for seismological research: Calculating large-scale noise cross-correlations using ALIYUN

2018 ◽  
Vol 31 (5-6) ◽  
pp. 227-233
Author(s):  
Weitao Wang ◽  
◽  
Baoshan Wang ◽  
Xiufen Zheng ◽  
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Public Cloud ◽  
Cross Correlations

scholarly journals A Phylogenomic Supertree of Birds

Diversity ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 109 ◽  
Author(s):  
Rebecca T. Kimball ◽  
Carl H. Oliveros ◽  
Ning Wang ◽  
Noor D. White ◽  
F. Keith Barker ◽  
...  
Keyword(s):  
Large Scale ◽  
Sequence Data ◽  
Bird Species ◽  
Divide And Conquer ◽  
Clear Understanding ◽  
Whole Genome ◽  
Efficient Manner ◽  
Sequence Capture ◽  
Branch Lengths ◽  
Supertree Methods

It has long been appreciated that analyses of genomic data (e.g., whole genome sequencing or sequence capture) have the potential to reveal the tree of life, but it remains challenging to move from sequence data to a clear understanding of evolutionary history, in part due to the computational challenges of phylogenetic estimation using genome-scale data. Supertree methods solve that challenge because they facilitate a divide-and-conquer approach for large-scale phylogeny inference by integrating smaller subtrees in a computationally efficient manner. Here, we combined information from sequence capture and whole-genome phylogenies using supertree methods. However, the available phylogenomic trees had limited overlap so we used taxon-rich (but not phylogenomic) megaphylogenies to weave them together. This allowed us to construct a phylogenomic supertree, with support values, that included 707 bird species (~7% of avian species diversity). We estimated branch lengths using mitochondrial sequence data and we used these branch lengths to estimate divergence times. Our time-calibrated supertree supports radiation of all three major avian clades (Palaeognathae, Galloanseres, and Neoaves) near the Cretaceous-Paleogene (K-Pg) boundary. The approach we used will permit the continued addition of taxa to this supertree as new phylogenomic data are published, and it could be applied to other taxa as well.

scholarly journals TreeMerge: a new method for improving the scalability of species tree estimation methods

2019 ◽  
Vol 35 (14) ◽  
pp. i417-i426 ◽  
Author(s):  
Erin K Molloy ◽  
Tandy Warnow
Keyword(s):  
Large Scale ◽  
Species Tree ◽  
New Method ◽  
Divide And Conquer ◽  
Supplementary Information ◽  
Estimation Methods ◽  
Running Time ◽  
Tree Estimation ◽  
Computationally Intensive ◽  
A Minor

Abstract Motivation At RECOMB-CG 2018, we presented NJMerge and showed that it could be used within a divide-and-conquer framework to scale computationally intensive methods for species tree estimation to larger datasets. However, NJMerge has two significant limitations: it can fail to return a tree and, when used within the proposed divide-and-conquer framework, has O(n5) running time for datasets with n species. Results Here we present a new method called ‘TreeMerge’ that improves on NJMerge in two ways: it is guaranteed to return a tree and it has dramatically faster running time within the same divide-and-conquer framework—only O(n2) time. We use a simulation study to evaluate TreeMerge in the context of multi-locus species tree estimation with two leading methods, ASTRAL-III and RAxML. We find that the divide-and-conquer framework using TreeMerge has a minor impact on species tree accuracy, dramatically reduces running time, and enables both ASTRAL-III and RAxML to complete on datasets (that they would otherwise fail on), when given 64 GB of memory and 48 h maximum running time. Thus, TreeMerge is a step toward a larger vision of enabling researchers with limited computational resources to perform large-scale species tree estimation, which we call Phylogenomics for All. Availability and implementation TreeMerge is publicly available on Github (http://github.com/ekmolloy/treemerge). Supplementary information Supplementary data are available at Bioinformatics online.

Divide and conquer: A hierarchical approach to large-scale structure-from-motion

2017 ◽  
Vol 157 ◽  
pp. 190-205 ◽  
Author(s):  
Brojeshwar Bhowmick ◽  
Suvam Patra ◽  
Avishek Chatterjee ◽  
Venu Madhav Govindu ◽  
Subhashis Banerjee
Keyword(s):  
Structure From Motion ◽  
Large Scale ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Divide And Conquer ◽  
Hierarchical Approach

The relation between seismic P‐ and S‐wave velocity dispersion in saturated rocks

Geophysics ◽  
1994 ◽  
Vol 59 (1) ◽  
pp. 87-92 ◽  
Author(s):  
Gary Mavko ◽  
Diane Jizba
Keyword(s):  
Wave Velocity ◽  
Large Scale ◽  
Velocity Dispersion ◽  
Seismic Velocity ◽  
Ultrasonic Velocities ◽  
S Wave ◽  
Local Flow ◽  
Wave Velocities ◽  
Shear Compliance

Seismic velocity dispersionin fluid-saturated rocks appears to be dominated by tow mecahnisms: the large scale mechanism modeled by Biot, and the local flow or squirt mecahnism. The tow mechanisms can be distuinguished by the ratio of P-to S-wave dispersions, or more conbeniently, by the ratio of dynamic bulk to shear compliance dispersions derived from the wave velocities. Our formulation suggests that when local flow denominates, the dispersion of the shear compliance will be approximately 4/15 the dispersion of the compressibility. When the Biot mechanism dominates, the constant of proportionality is much smaller. Our examination of ultrasonic velocities from 40 sandstones and granites shows that most, but not all, of the samples were dominated by local flow dispersion, particularly at effective pressures below 40 MPa.

End-User-Driven Approach for Regulatory Compliance in the Public Cloud

2021 ◽  
Vol 12 (3) ◽  
pp. 1-19
Author(s):  
Jitendra Singh ◽  
Vikas Kumar
Keyword(s):  
Present State ◽  
Business Groups ◽  
Regulatory Compliance ◽  
Third Party ◽  
Expert Advice ◽  
Small Scale ◽  
Public Cloud ◽  
End User ◽  
The Public ◽  
Limited Budget

Regulatory compliance is equally binding on small and medium business groups. Owing to the small scale and limited budget, such SMBs are unable to seek expert advice. To adequately guard the SMBs in regulatory compliance, the present work proposed a third-party managed-end user-driven approach that renders the list of regulatory acts applicable in one's case according to the country of one's residence, services subscribed, and type of the operations to be carried out in subscribed cloud paradigm. The list of applicable regulatory acts are rendered at the subscriber's end only. In addition, the proposed method notifies the present state of compliance of under-considered cloud providers. Based on the recommendation received, the subscriber can proceed with his decision to subscribe or not to subscribe in the event if desired compliances do not exist. This technological assistance will eliminate the need to possess the required knowledge in regulatory acts or seeking advice from the regulatory expert.

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