Development of Power Monitoring System to Support
Fair Operation of Data Center to the Customers
Akhmad Alimudin1, Ferry Astika S1, Hikmatulloh Hari Mukti1, Meis Musida2
1

Electronic Engineering Polytechnic Institute of Surabaya, Indonesia
2

XL Axiata Tbk, Indonesia

alioke@pens.ac.id, ferryas@pens.ac.id, hari11@it.student.pens.ac.id, meism@xl.co.id

This paper presents a power monitoring system to provide the information of the electricity used in the racks
of data center. Our Idea to implement a context of power monitoring system is how to deliver the current
electricity used and the excess power of the electricity used of a rack and its cost in data center to the data
center corporation and to the customers. We implement the system that retrieves data periodically every one
second for real time monitoring and one minute interval for system requirement, The one second interval
only aimed to be presented in the web and will not be saved in the database but the one minute interval will
be saved to be processed further. After retrieving one minute interval data, we process it to be presented into
periodically graphs and process it data to get excess power from the contract agreement. We perform ourproposed system to fulfill the request from XL Data Center to support fair operation of the data center.
Keywords : power monitoring system, data center, fair operation, electricity, excess power
1. Introduction
Data center can be defined as any space whose
main function is to house hold servers, electronics
computing, communicate with other computer
networks and manage the interaction between
users and server-based software and web portal.
Moreover, data center is used for managing dataand important operation, confidential such as
email and company or government database. All
this time, server reliability is measured from its
ability to be functioning properly and minimum
loses data. Reliability is strongly linked not only
to the server characteristics but also theinfrastructure as well, which include the power
distribution an environmental management.
Electricity is the one of the important factors indata center business. Joko Suryana in his researchsaid that the total the Indonesia’s power
consumption is 109.098 kW. Electric power
consumtion reaches 40% -50% more than the totalmonthly operating costs [1]. Andreuw THAF also
said the same thing that electrical components
contribute about 40% to operating costs [2]. Rack
servers are the one of electrical components ofdata center. The power usage of rack servers
affects the operational costs as well. And thecalculation of electricicy costs of the rack servers
will impact the profit and loss of monthly
operational costs.
Unfortunately, there is no power monitoring
system that provides information when there arechanges in the use of electricity while the changes
can be affect the costs. The change of the costs
can benefit customers but it inflicts the financial
loss of the provider if the usage of the electricity
is actually more than what it was declared in thecontract. (In the case study at XL Data Center, theamount of electric current that is allowed is 10Ampere).
Whereas, the real time conditions of racks in data
center is customers’ right. This research willdevelop a new way in the web-based powermonitoring system to provide the information ofpower usage of the customers’ servers directly.
2. Related Works
In [3], the amount of electricity usage for data
centers around the world has doubled during theyears 2000-2005. Almost entirely is the result of

the increasing the number of serves. The total
powes used by IT equipment in the data cener byapproximately 0.5% of world electricity
consumtion in 2005. In [4], Neil describes theconventional way of describing the density of thedata centers is still primitive, incomplete andambiguous. This paper outlines the requirements
for density specification and introduces a new
method for density specification. In [5], the use ofpower in data center is much greated than incommercial office buildings in general, because of
the density of computer equipment. Calculate theelectricity usage of equipment with more accuratecomputer also can have a significant impact. In[6], the projection growth of data center in 2000 isthree times each year in US. In the year 2020, it’s
likely to increase 4-fold. In [7], the issues
discussed was the center of power distribution of
adata center such as power distribution must not
be interrupted, the power supply efficiency andpower density in Watts / ft2.
3. Uniqueness
Most data center calculate the cost of electricity
based on electricity current written in the contract
agreement without calculating if there is power
exceed the agreement. And few of them arecalculating the excess power based on electric
current exceed the agreement using AMP meter inthe end of the month. Calculating electric current
exceed using Power Distribution Unit integrated
with this Power Monitoring System that
periodically record the electric usage of data
center is a new way.

In the power monitoring application, the design isdivided in two concepts, hardware side andapplication side.
1. Hardware• There are 1000 racks in data center.
• Every rack contains 2 PDUs.
• Each PDU has one port RJ45 that used forcommunication.
• So there will be 2000 IP Address will beassigned in the network plus 1 more IP
Address for server.
• The closest subnet type is Class B in Netmask
21. The range of the IP Address is from
255.255.248.0 ~ 255.255.255.254.
• Both PDU ports in a rack are connected to asecond hierarchy switch.
• Each second hierarchy switch is connected tothe main switch. In the main switch there is
one server that connected to it. The scheme ison Figure 2.

4. Discussion
A. System DesignFig 2. Network Scheme

1stRACKPDU
PDU

1000thRACKPDUPDUSWITCHSWITC
HSNMP

2. Application

POW
E
R

In application side, the process is performedby power monitoring system application. Inthe application, there are 2 roles:• Admin role

SNMPSYSFig 1. System DesignTEM

UserAdminAdmin is the ones who manage the entiresystem. Admin has privileged to monitor

the entire PDUs. Admin also can add, edit,
and delete data.
• Users role
Users are the customers who rent the rack.
Users have privileged to monitor their ownrack. Monitor the real time electric current
and monitor the power usage by time.
The data are obtained and need to beprocessed to get the average electric current
every 5 minutes, 30 minutes, 1 hour, 2 hours
and 1 day. The one hour average of electric
current are saved in the database for further
process and the others are not purposed to besaved and it just saved in the database fortemporary time because it just proposed to be
showing in the graph for a temporary time.
The one hour average of electric current isused for analytic purpose and for calculating
the excess power of the rack. The process ofcalculating the excess power is passing
through these following steps:
1. Each rack has 2 PDU, the sum of the onehour electric current average of both PDUs
are the total current of the rack every onehour.
2. The total current of the rack every one
hour will be processed to get the electric
power and power hour. The formula to get
the electric power and power hour are
explained below :Q = V.I.cosθ/1000
W = Q.t

(3.1)
(3.2)

W = Power hourt = Time (number of hours in a month)
Q = the reactive power
V = Voltage (220V)
I = Electric Current
Cos = Power Factor (known to be 0.92)
From formula 3.1 and 3.2, where the electric
current is known to be 10 A, the power
threshold can be calculated.

3. To get the power used in a month, the electric
current is knows to be the average current of
every one hour in a month. The formula canbe derived as follows:

Where n = the number of hours of a month.
4. The formula to get the excess power can bederived as follows:
EP=Power used - Power threshold(3.4)
Where EP > 0
EP = Excess Power5. After excess power calculated, the electric
current that actually used in one month can beobtained by divide excess power with powerusage of 1 A.
Excess current = excess power/Wof 1Amp (3.5)
4.1. Experiment and Analysis
The purpose of this experiment is to determine
whether the system is running well and working
properly. The experimentand analysis focus ondata retrieval, excess power calculation, andpresenting the data.
A. The Experiment
1. Retrieving Data from the PDUs
1.1. Periodic retrieval system for system
requirements
There are many PDUs to be retrieved its data(3.1)
and data should be retrievedat the same time.
(3.2)
It means, there
should be no waiting time foreach process. For this reason, PHP-Forking isused to answer this problem. This retrieving
data function saved in a single PHP file and it
run by crontab every minute interval.
Processes inside are divided into different
child of process and run together at the sametime without waiting each process to be done.
This system has been implemented in serverof Politeknik Elektronika Negeri Surabaya(PENS) and in server of XL Data CenterJakarta. In PENS, one rack is registered in thesystem, the rack has 2 PDUs which the id are
45 and 46. Look at table 2, the table shows
the both PDUs have the data retrieved in thesame time.
Table 1. Realtime Electric Current Data Of PENS
Fig 3. Monitoring Page (PENS)In XL Data Center Jakarta, the real time data
retrieval also run well without problem. Thereal time data retrieval in XL is in figure 4:
In XL Data Center Jakarta, one rack isregistered as well, the id of the PDU are 47
and 48. The result are the same as in server ofPENS, the both PDUs have the data retrievedin the same time. The result is on table 1.

Fig 4. Monitoring Page of PT. BSA (customer of XL Data Center)

Table 2. Realtime electric current data of XL

1.2. Data Retrieval by Customers and Admin
Data retrieved by customers and admin isperformed when monitoring page is openedin browser. This is performed by using a PHP
script which is run by AJAX in JavaScript
according to target of the PDU. To get thedata, it requires IP Address of the PDU andits OID. The purpose of retrieving real timedata is to be shown in the graph and not to be
saved in the database. The experiment ofrunning this system in the server of PENS
shows that real time data retrieval run wellwithout problem, the status of the processreturn 200 means the processes are complete.
The figure of the real time data retrieval in
PENS is in figure 3:

1.3. Presenting Data
The presentation of data are divided into 3
categories:
1.3.1. Real time Data Presentation
In this category, the data is presented into
real time every one second interval, 5minutes average, 30 minutes average, 2hours average and 1 day average for each
PDU. The figure of real time every one
second interval is shown in the figure 5 and6.

Fig 5. Real time one second interval

The data presentation for 5 minutes average,
30 minutes average, 2 hours average and 1
day average is shown in the figure 4.8 to
4.11. In 5 minutes average, each point in thegraph presents the average of electric
current usage in 5 minutes. Figure 7 showsthe electric current usage of the day is far
below the electric current threshold.

histogram,daily
histogram,
weeklyhistogram, monthly histogram and yearly
histogram. From those graphs admin or user
can see the trend of power usage.
Fig 6. The daily graph (5 minutes average)

In 30 minutes average, each point in thegraph presents the average of electric
current usage in 30 minutes. Figure 7 showsthe electric current usage of the week is far
below the electric current threshold.

The daily histogram present the electric
current usage in 24 hours point graph. Eachpoint present the average of electric current
usage of same hour in a month. Figure 10shows the electric current usage of June
2015. None of the point reach the threshold.

Fig 7. The weekly graph (30 minutes average)
Fig 10. Daily Histogram

In 2 hours average, each point in the graphpresents the average of electric current
usage in 2 hours. Figure 8 shows the electric
current usage of the month is far below theelectric current threshold.

Fig 8. The monthly graph (2 hours average)

In 1 day average, each point in the graphpresents the average of electric current
usage in 1 day. Figure 9 shows the electric
current usage of the year is far below theelectric current threshold.

Fig 9. The yearly graph (1 day average)

The data presented for analytic purpose ispresented in histogram graph. There are 4

The weekly histogram present the electriccurrent usage in 7 days of the week pointgraph. Each point present the average ofelectric current usage of same day in amonth. Fig 13 shows the electric current
usage of June 2015. None of the point reachthe threshold.
1.4. Excess Power Calculation
The system has been implemented since April
2015 in XL Data Center Jakarta but there are
no data above the threshold. So for testing thecost calculation, the dummy data is used. For
example the power usage in June is 2025,012
kWh with power limit according to thecontract for 10A is 1350,008 kWh. The
excess power is 675,004 kWh with electriccurrent exceed is 5A above the threshold. The
exceed electricity cost is 5 multiple by cos
per Ampere. The result of the calculation isshown in the figure 11:• Data center from small scale to big scale canuse this system to provide tranparency
electricity infomation of each rack in data
center.
Fig 11. Billing from June 2015

The basic cost is Rp. 1.000.000,00 and theexcess power excess is Rp. 2.500.000, 00 so
the total cost is Rp. 3.500.000,00.
The following are real the billing informationof PT. Buana Solution Andalan, customer of
XL Data Center Jakarta, on April shown infigure 12:

Fig 12. Billing from April 2015

5. Conclusion
Based on experiments and analysis can beconcluded that:• With this power monitoring system, the powerusage of a rack and the excess power usage
cost can be calculated using the method of thisresearch. The data retrieve from PDU is thesame as the data retrieved from conventional
power meter because PDU is also an industrystandard. So the calculation using this methodby utilizing the PDU is a new way compared tothe conventional way.
• Realtime monitoring presented in graphprovide the information more readable andeasy to understand.
• All the data retrieved from PDU is presented inthe graph, so both provider and customer cananalyze it or compare the data to the billing
calculation.

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