Reliability

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A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing


Cloud computing is a technique proposed based on the distribution of processing and storage resources across various multiple servers. The user can easily access the services and applications of cloud at any location and moment in this infrastructure. Although these capabilities have made the cloud services more flexible and available, issues such as scheduling and load balancing for optimal use of resources, have always been the main challenges in this infrastructure.

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Dataset Details

Citation Author(s):
Submitted by:
Nawzad Al-Salihi
Last updated:
Wed, 04/18/2018 - 07:25
DOI:
10.21227/H2G95P
Data Format:
 
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[1] , "A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2G95P. Accessed: Jun. 17, 2018.
@data{h2g95p-18,
doi = {10.21227/H2G95P},
url = {http://dx.doi.org/10.21227/H2G95P},
author = { },
publisher = {IEEE Dataport},
title = {A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing},
year = {2018} }
TY - DATA
T1 - A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2G95P
ER -
. (2018). A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing. IEEE Dataport. http://dx.doi.org/10.21227/H2G95P
, 2018. A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing. Available at: http://dx.doi.org/10.21227/H2G95P.
. (2018). "A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing." Web.
1. . A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2G95P
. "A Load Balancing Mechanism to Reduce Energy Consumption with Preservation QoS in Cloud Computing." doi: 10.21227/H2G95P

Convolutional neural network errors


This file contains all data used on paper "Analyzing and Increasing the Reliability of Convolutional Neural Networks on GPUs"

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Dataset Details

Citation Author(s):
Submitted by:
Fernando dos Santos
Last updated:
Mon, 01/22/2018 - 06:50
DOI:
10.21227/H2WT0P
Data Format:
 
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[1] , "Convolutional neural network errors", IEEE Dataport, 2018. [Online]. Available: http://dx.doi.org/10.21227/H2WT0P. Accessed: Jun. 17, 2018.
@data{h2wt0p-18,
doi = {10.21227/H2WT0P},
url = {http://dx.doi.org/10.21227/H2WT0P},
author = { },
publisher = {IEEE Dataport},
title = {Convolutional neural network errors},
year = {2018} }
TY - DATA
T1 - Convolutional neural network errors
AU -
PY - 2018
PB - IEEE Dataport
UR - 10.21227/H2WT0P
ER -
. (2018). Convolutional neural network errors. IEEE Dataport. http://dx.doi.org/10.21227/H2WT0P
, 2018. Convolutional neural network errors. Available at: http://dx.doi.org/10.21227/H2WT0P.
. (2018). "Convolutional neural network errors." Web.
1. . Convolutional neural network errors [Internet]. IEEE Dataport; 2018. Available from : http://dx.doi.org/10.21227/H2WT0P
. "Convolutional neural network errors." doi: 10.21227/H2WT0P

The Measurement Coverage for Boolean Tomography with Limited End Monitors


This dataset includes all the datum of our  numerial simulations, which are generated from networks with 5-25 end-to-end paths.

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Dataset Details

Citation Author(s):
Submitted by:
Shengli Pan
Last updated:
Sun, 12/17/2017 - 08:31
DOI:
10.21227/H2VP9D
Data Format:
 
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[1] , "The Measurement Coverage for Boolean Tomography with Limited End Monitors", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2VP9D. Accessed: Jun. 17, 2018.
@data{h2vp9d-17,
doi = {10.21227/H2VP9D},
url = {http://dx.doi.org/10.21227/H2VP9D},
author = { },
publisher = {IEEE Dataport},
title = {The Measurement Coverage for Boolean Tomography with Limited End Monitors},
year = {2017} }
TY - DATA
T1 - The Measurement Coverage for Boolean Tomography with Limited End Monitors
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2VP9D
ER -
. (2017). The Measurement Coverage for Boolean Tomography with Limited End Monitors. IEEE Dataport. http://dx.doi.org/10.21227/H2VP9D
, 2017. The Measurement Coverage for Boolean Tomography with Limited End Monitors. Available at: http://dx.doi.org/10.21227/H2VP9D.
. (2017). "The Measurement Coverage for Boolean Tomography with Limited End Monitors." Web.
1. . The Measurement Coverage for Boolean Tomography with Limited End Monitors [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2VP9D
. "The Measurement Coverage for Boolean Tomography with Limited End Monitors." doi: 10.21227/H2VP9D