Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

< Back to Article

Fig 1.

The field concept of Google BigTable.

More »

Fig 1 Expand

Table 1.

An example of the Row Table.

More »

Table 1 Expand

Table 2.

An example of the Schema Table.

More »

Table 2 Expand

Fig 2.

Overall system architecture of our proposed DaaS.

More »

Fig 2 Expand

Fig 3.

Overall system structure and components of our proposed DaaS.

More »

Fig 3 Expand

Fig 4.

Demonstration of the Processor operation structural diagram when a client issues an Http request.

More »

Fig 4 Expand

Fig 5.

Example of the XML format of the data received by our proposed system.

More »

Fig 5 Expand

Fig 6.

Example of the system-stored physiological data format in XML.

More »

Fig 6 Expand

Table 3.

XML tag and element definitions in our proposed system.

More »

Table 3 Expand

Fig 7.

File storage data format illustration.

More »

Fig 7 Expand

Fig 8.

Result of ECG data stored as an XML file.

More »

Fig 8 Expand

Fig 9.

ECG data results with null values stored as an XML file.

More »

Fig 9 Expand

Fig 10.

Diagram illustrating the metadata database when a client issues an Http request.

More »

Fig 10 Expand

Table 4.

Hardware and software environment configurations of the experiments.

More »

Table 4 Expand

Fig 11.

Test data I source format with continuous ECG data in XML.

More »

Fig 11 Expand

Fig 12.

Test data II source format with temperature data in XML.

More »

Fig 12 Expand

Fig 13.

MySQL database storage method I, storing values in different records.

More »

Fig 13 Expand

Fig 14.

MySQL database storage method II storing 5 minutes of ECG data in a record.

More »

Fig 14 Expand

Fig 15.

Performance results of InnoDB and MyISAM in the MySQL database for writing different sizes of data.

More »

Fig 15 Expand

Fig 16.

Write performance of test data I for writing different sizes of data.

More »

Fig 16 Expand

Fig 17.

Write performance of test data II for writing different sizes of data.

More »

Fig 17 Expand

Fig 18.

Performance results of continuous reading test data I for different sizes of data.

More »

Fig 18 Expand

Fig 19.

Result of reading a specific region of test data I for different sizes of data.

More »

Fig 19 Expand

Fig 20.

Different numbers of users writing 5 minutes of test data I.

More »

Fig 20 Expand

Fig 21.

Different numbers of users reading randomly reading 10 seconds of ECG data.

More »

Fig 21 Expand

Table 5.

Initial disk usage of servers in the disk usage experiment.

More »

Table 5 Expand

Table 6.

Disk usage after server balancing in the disk usage experiment.

More »

Table 6 Expand

Fig 22.

Disk usage variation in each server for 1000 users.

More »

Fig 22 Expand

Table 7.

Initial disk usage of servers in the disk loading experiment.

More »

Table 7 Expand

Table 8.

Disk usage after server balancing in the disk loading experiment.

More »

Table 8 Expand

Fig 23.

Disk usage variation with adding a new Server #2 with 0% disk load.

More »

Fig 23 Expand

Table 9.

Initial state of each server for the CPU load balancing experiment.

More »

Table 9 Expand

Table 10.

Number of users in each server after load balancing experiment.

More »

Table 10 Expand

Fig 24.

Average CPU load of the servers after each test.

More »

Fig 24 Expand

Fig 25.

Data size in the hard disk for different periods of data.

More »

Fig 25 Expand

Fig 26.

XML storage format modification results.

More »

Fig 26 Expand

Fig 27.

Storage size comparison after modification.

More »

Fig 27 Expand