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When Network Matters: Data Center Scheduling with Network Tasks

F. Giroire, N. Huin, A. Tomassilli, S. Perennes
2019 IEEE INFOCOM 2019 - IEEE Conference on Computer Communications  
According to recent studies, network transfers represent up to 50% of the completion time of classical jobs. Thus, network resources must be considered when placing jobs in a data center.  ...  We consider the placement of jobs inside a data center. Traditionally, this is done by a task orchestrator without taking into account network constraints.  ...  Modeling Data Center Orchestration with Communication We show here that we can model data center task orchestration and network resource allocation using our scheduling framework with a simple set of network  ... 
doi:10.1109/infocom.2019.8737415 dblp:conf/infocom/GiroireHTP19 fatcat:ypzw3ket5fahnppgxzr6dtfjla

Efficient dynamic task scheduling in virtualized data centers with fuzzy prediction

Xiangzhen Kong, Chuang Lin, Yixin Jiang, Wei Yan, Xiaowen Chu
2011 Journal of Network and Computer Applications  
Efficient dynamic task scheduling in virtualized data centers with fuzzy prediction. J Network Comput Appl (2010) ,  ...  This paper proposes an efficient dynamic task scheduling scheme for virtualized data centers.  ...  Efficient dynamic task scheduling in virtualized data centers with fuzzy prediction. J Network Comput Appl (2010), doi:10.1016/j.jnca.2010.06.001  ... 
doi:10.1016/j.jnca.2010.06.001 fatcat:s4drn3lvljahbl5d5bwt2xlnia

Evidence that Executive Productivity Matters When Determining Optimal Incentive Levels

Jean Canil
2009 Social Science Research Network  
Specifically, we find that larger grants are associated with lower productivity, but we also find that in-the-money (ITM) grants are associated higher executive productivity.  ...  Given that large-firm CEOs in our Australian data set are less productive than small-firm CEOs in our sample, we show empirically that ITM grants rather than larger grants are preferred to incentivize  ...  However, since in our sample 30 Solving this expression with our data yields a γ value of 0.394 which is remarkably close to the Baker and Hall (2004) estimate for Execucomp data.  ... 
doi:10.2139/ssrn.1361264 fatcat:vgsivtxusrfereuefcmhrt2vfu

When things matter: A survey on data-centric internet of things

Yongrui Qin, Quan Z. Sheng, Nickolas J.G. Falkner, Schahram Dustdar, Hua Wang, Athanasios V. Vasilakos
2016 Journal of Network and Computer Applications  
A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous.  ...  objects to the Internet and facilitating machineto-human and machine-to-machine communication with the physical world.  ...  Transaction Handling: When the data being updated is spread across hundreds or thousands of networked computers/smart things with differing update policies, it would be difficult to define what the transaction  ... 
doi:10.1016/j.jnca.2015.12.016 fatcat:4roub2ifdjgide4kxhmqqrk44i

When Does Domestic Saving Matter for Economic Growth?

Philippe Aghion, Diego A. Comin, Peter Howitt, Isabel Tecu
2009 Social Science Research Network  
does not matter for growth.  ...  In relatively poor countries, catching up with the frontier requires the involvement of a foreign investor, who is familiar with the frontier technology, together with e ort on the part of a local bank  ...  In our model, savings matter only because of their role as collateral when undertaking technology adoption projects with a foreign investor.  ... 
doi:10.2139/ssrn.1328359 fatcat:b5ppofld6fantetgqvjqbc4sam

What Do Neural Networks Learn When Trained With Random Labels? [article]

Hartmut Maennel and Ibrahim Alabdulmohsin and Ilya Tolstikhin and Robert J. N. Baldock and Olivier Bousquet and Sylvain Gelly and Daniel Keysers
2020 arXiv   pre-print
In this paper, we show analytically for convolutional and fully connected networks that an alignment between the principal components of network parameters and data takes place when training with random  ...  We study deep neural networks (DNNs) trained on natural image data with entirely random labels.  ...  The paper aims at improving our understanding of how DNNs learn from data and therefore does not have a direct impact on applications or society.  ... 
arXiv:2006.10455v2 fatcat:hk2y5zpubnbkzagbourle7xtqa

When Nudges Fail: Slippery Defaults

Lauren E. Willis
2012 Social Science Research Network  
, and it is perceptions that matter here.  ...  When the choice to opt out of a default is not made plain, people may perceive a default as unchangeable. 36 This is likely to be the case in unfamiliar task environments.  ...  Experience with other mandated disclosures cautions that consumers rarely read them, and even when they do, they do not understand them or use the information in them accurately. 277 Firm marketing is  ... 
doi:10.2139/ssrn.2142989 fatcat:kcorrlwoifgzjmgu3oghal442q

Front Matter [chapter]

2014 Data Center Handbook  
Acknowledgments The Data Center Handbook is a collective representation  ...  , sDn, and sDDC in Data Centers 391 Omar Cherkaoui and Ramesh Menon 20.1 introduction, 391 20.2 Virtualization in Data Centers, 392 20.3 Cloud as an extension of the Data Center, 393 20.4 networking  ...  open standards, 585 31.8 Grid-Distributed Data Centers and networks, 586 31.9 summary of Dr strategies, 587 31.10 Challenges to Grid-responsive Data Centers, 587 31.11 U.s.  ... 
doi:10.1002/9781118937563.fmatter fatcat:jwr6vm7tsrfefg5iwkhtgemg3y

Network Consumption and Storage Needs when Working in a Full-Time Routine Digital Environment in a Large Nonacademic Training Hospital

Marius Nap
2016 Pathobiology (Basel)  
Abstract Objective: Digital pathology is indisputably connected with high demands on data traffic and storage.  ...  Results: The results showed that data traffic inside the hospital network (1 Gbps) never exceeded 80 Mbps for scanner-to-server activity, and activity from the server to the workstation took at most 5  ...  Discussion Data Traffic Some 10 years ago when we made our first steps in digital pathology, we arranged a meeting with the IT department because we wondered if the network capacity in our hospital would  ... 
doi:10.1159/000442388 pmid:27101003 fatcat:neztkyciaratbjol54jfcq4use

Crowd-sensing: Why context matters

Iacopo Carreras, Daniele Miorandi, Andrei Tamilin, Emmanuel R. Ssebaggala, Nicola Conci
2013 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)  
The underlying idea is that people, together with their mobile device, can act as mobile and pervasive sensors, gathering information about the surrounding environment and potentially providing direct  ...  ) the synchronization of tasks with the remote server, and (ii) the proper task execution when notified by the CM.  ...  When the uncertainty on the user location due to the coarse accuracy of the network localization overlaps with the spatial validity of the closest task, we should switch to GPS localization.  ... 
doi:10.1109/percomw.2013.6529518 dblp:conf/percom/CarrerasMTSC13a fatcat:ynyqrljf25aqlfttm2ykj2p2fu

When 2 or 3 Come Together

Tracey L. Meares, Kelsi Brown Corkran
2005 Social Science Research Network  
If collaboration between churches and the police through religious activity enhances the community efficacy of poor minority neighborhoods, is there any way to reconcile the benefits of such activity with  ...  In reality, they are often the heart of the matter.  ...  suggest a parallel problem existed with respect to goals for which the relationships among WSC churches were harnessed.Specifically, the data indicate that prior to the prayer vigils the networks among  ... 
doi:10.2139/ssrn.835664 fatcat:z3peyd2e25d35hsbo4cwtsorye

Redliking: When Redlining Goes Online

Allyson Gold
2020 Social Science Research Network  
For hosts with an unused home, a spare room, or an extra couch, Airbnb provides an opportunity to create new income streams and increase wealth.  ...  Empirical research on host earning rates found that White hosts earn significantly more than minorities, even when controlling for location, size, and amenities.  ...  Airbnb partnered with Asian Americans Advancing Justice, Center for Democracy & Technology, Color of Change, The Leadership Conference on Civil & Human Rights, LULAC, the NAACP, National Action Network  ... 
doi:10.2139/ssrn.3522156 fatcat:3vzeev3azjfyhnr5zmkhow2twe

Back Matter

IALLT Editors
2019 IALLT Journal of Language Learning Technologies  
IALL Monographs: Task-Based Activities, Volume II $10 $25 $ - Task-Based Activities, Volume I $10 $15 $ - Designing the Learning Center of the Future $10 $15 $ - IALL Lab Design Kit (First  ...  Additional support also includes help with hardware selection and configuration as well as help with network connections and usage.  ... 
doi:10.17161/iallt.v27i3.9572 fatcat:35o75ie7kfaexjctdqqmyd3twq

Front Matter: Volume 10646

Ivan Kadar
2018 Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII  
These two-number sets start with 00, 01, 02, 03, 04,  ...  Data Size Variability  Pyramid approach [13]  When size is different than trained network but, is fixed.  ...  allow the network to learn when to "forget" previous hidden states and when to update hidden states given new information.  ... 
doi:10.1117/12.2500434 fatcat:wfvvakrbsrfrbiiglzdvnp34o4

Front Matter

2021 2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)  
The analytical capability of machine learning (ML) methods has proven to be extremely accurate and in some cases superior to classical statistical approaches for solving this task.  ...  Novel machine learning applications are pioneering the conversion of these multimodal data into measures of quality of life, capturing symptoms like fatigue, stress, and depression.  ...  Along with these molecular data, dense, rich phenotypic data are also available on comprehensive clinical data sets from health care provider organizations, clinical trials, population health registries  ... 
doi:10.1109/bhi50953.2021.9508590 fatcat:sba7l5z735arnnkksekqhmnifq
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