Systems With Central Monitoring

International Journal of Engineering & Technology IJET-IJENS Vol: 11 No: 01 117

117401-2727 IJET-IJENS February 2011 IJENS

I J E N S

Abstract Monitoring and control of power systems, cooling

and environmental parameters in data centers, aim at a central

monitoring of all elements of infrastructure, despite the

different nature of all data and alarms. The architecture of

monitoring and control system is analyzed in this paper taking

into account the requirements for a centralized architecture.

The bandwidth will be influenced more by monitoring cameras.

The number of monitoring cameras, frame resolution, frame

speed transmission and the level of compression, are taken into

consideration in calculating the impact of video frames in the

bandwidth.

Index Term Monitoring, control, video frames, bandwidth

I. INTRODUCTION

To monitor and control a system, means to get information

from the equipment or system, to analyze this information and

to register it as an alarm or data. Further this information is

stored and used to construct the history of monitored

parameters. The process from this perspective, deals with

managing the data center, while power system, cooling or

environmental control parameters are a function of the creation

of a reliable infrastructure and high availability for these

parameters [1, 3, 4].

Power monitoring equipment, basically has to do with

monitoring and control equipment such as UPS (uninterrupted

power systems), PDU (power distribution panels), DC power

supply systems and all other devices that are part of the AC

and DC power. Regardless of the type of equipment monitored

or controlled, the goal is to ensure an uninterrupted supply of

data center [2].

Monitoring and control of cooling systems, or in general,

HVAC systems (heating, ventilation and air conditioning

systems), deals essentially with temperature control at the

entrance and exit of equipment, mainly servers, in order

determining the temperature of the work of HVAC equipment,

and in order to eliminate condensation point in data centers or

in specific equipment in particular [8, 11, 12].

It takes more importance in the case of temperature control of

the "blade servers" in data centers, while these devices have

specific requirements for temperature. The same control is also

to monitor the relative humidity, taking care to maintain within

the limit, the corresponding value. Processes of growth or

lowering the level of relative humidity are automatic processes,

controlled by the measured values and the logic of the

functioning of the system.

Monitoring and control of environmental parameters, has to

do with monitoring and controlling temperature, humidity, air

flow flow and water detection in the data center.

The system also includes video monitoring, access control,

and fire suppression system.

There are a large number of sensors and parameters to be

checked and this increases the complexity of monitoring and

control system.

The band width required for transmitting data from all

devices and sensors, should be calculated, by taking into

account the existence and considerable weight of video frames.

II. THE ARCHITECTURE OF MONITORING AND CONTROL SYSTEM

There are several methods for managing data center. One of

management systems is the traditional system which controls

each device separately, as in Fig. 1. The advantage of this

method of control lies in the use of special monitoring

programs thus eliminating the presence of a single point of

failure in the system [7, 9, 10, 13]. This structure gives the

possibility of use of different communication protocols as well

as non-standard or unique interfaces in the system of

monitoring and control. The main disadvantage of this system

lies in the large number of individual programs, which do not

allow real-time control of all systems.

Central monitoring system is another option for control and

monitoring systems. His principal scheme is given in Fig. 2.

Obvious advantage of this architecture is that it monitors, from

a single program, all subsystems, thus providing the

possibility of real-time monitoring of the whole system.

Disadvantage of this model is the presence of a single control

program which is a single point of failure in the system. This

Systems with Central Monitoring and Control for

Data Center Infrastructure and the Effect of

Video Frames in the Transmission Bandwidth

Bexhet Kamo1, Rozeta Miho

1, Vladi Kolici

1, Olimpjon Shurdi

1, Algenti Lala

1

1Faculty of Information Technology, Polytechnic University of Tirana

ALBANIA

e-mail: {bkamo, rmiho, vkolici, oshurdi, alala}@fti.edu.al



I J E N S

problem can be eliminated by using some additional elements

in the system. The revised scheme with central monitoring

system is presented in Fig. 3.

Fig. 1. Traditional monitoring and control system

In the revised scheme, the elements use the same

communication protocol and communicate with the central

program through LAN network [5, 6]. The presence of a

communication card in any device, also allows separate control

of their own, in case that the central program is damaged. Local

data storage for a certain time, depending on the memory of

communication card, eliminates the problem of access to data

in the event of a breakdown of central monitoring system. The

disadvantage of this configuration lies in the protocol or

standard communication interface, which should have any

equipment. Such a thing is not always possible due to lack of

standardization for interfaces and sensors. For this reason, we

may use, architecture presented in Fig.4

Fig. 2. System with central monitoring

So the revised final scheme may include any sensor regardless

of its interface. Sensors should be managed by a "device -

access point" which will play the role of the interface between

sensors and central monitoring system. Access Point,

should be able to maintain for a period of time, data sensors,

and enable the management of sensors from the central

program, even locally through its SNMP interface.



I J E N S

Fig. 3. System with central monitoring in LAN

Fig. 4. Central monitoring system with no standard interface sensors



I J E N S

III. THEORETICAL CALCULATION OF THE BANDWIDTH

The bandwidth calculation shoul take into consideration all

data generated from all devices and sensors. Since the video

cameras are the main sensors that will effect mostly the

bandwidth we consider only the effect of video surveillance

cameras during the bandwidth calculation. The effect of other

data is relatively small compared to video frames and it will

occupy a relatively small bandwidth.

The bandwidth calculation, for video transmission, is based

on parameters that are deterministic in the size of video frames.

By calculating the size of video frames and by selecting the

frame rate and compression method, we calculate the

bandwidth required for real time video transmission. Fig. 5,

shows the graph that can be used for bandwidth calculation.

Fig. 5. Flowchart for the bandwidth calculation, occupied by video frames

The size of bandwidth is the bandwidth required for video

frames transmission plus bandwidth required for environmental

data and alarms. Since the bandwidth required for

environmental data and alarms is relatively small, we study in



I J E N S

details only the bandwidth required for real time video

transmission. Some other parameters that are not mentioned in

the flowchart but that have an important role in real time video

transmission are latency, caused by compression method

selected and motion detection (an parameter of video cameras).

The latency is an important parameter (that affects the real time

video transmission) and for bandwidth optimization we should

select between compression methods that offer an acceptable

latency and a higher video compression value. There are a lot

of compression methods like MJPEG, MPEG4, H264, etc. To

optimize the bandwidth we may change parameters like:

resolution and bit per pixel, frame rate and compression value.

Frame resolution and bit per pixel value, are both related to the

image quality. So if we intent to decrease the resolution or the

bit per pixel value, we will lose the image quality. For video

surveillance with normal quality is required to have a

resolution of 640 x 480 and 24 bit per pixel value. Using matlab

we can calculate the uncompressed frame size for different

resolution values, as in Fig. 6.

Fig. 6. Uncompressed frame size for different resolutions and bit per pixel values

The frame rate is a parameter that takes values from 1 to 30

frames per second. As lower the frame rate as lower the

bandwidth required. For video surveillance with a normal

quality is required a frame rate of 25 frame per second, but

based on the bandwidth value we can transmit using lower

values, like 15, 10 or 5 frames per second. Using matlab, we

may create an idea how the bandwidth changes for different

frame rate values, as in Fig. 7 (the case is studied for images

with 640 x 480 resolution and 16 bit/pixel value). The blue color

graph, in Fig. 7, shows the bandwidth required for one

video camera with frame rates from 1 to 30 frames per second,

640 x 480 resolution and 16 bit/pixel value.

In order to optimize the bandwidth required, we compress the

video frames. In Fig. 7, is showed the required bandwidth for

different compression values. The bandwidth optimization can

be done by changing the up mentioned parameters in a level

that not change the minimum quality required.



I J E N S

Fig. 7. Bandwidth for one video camera for different frame rates and compression rates for a frame with 640 x 480 resolution and 16 bit per pixel

value

IV. RESULTS AND DISCUSSIONS

Based on a real system design and in the theoretical

calculations of bandwidth, is implemented in practice a

monitoring and control system with central control and

monitoring. The configuration of system is given in fig. 8. The

system has two rooms and a control centre. Each room has a

base station where video cameras and environmental sensors

are connected. Besides, in the base stations are connected also

sensors of alarms and data that comes from third party devices.

Video, alarms and data collected to the bases station are

transmitted, through the

router, to the control centre. What should be solved next is the

maximum number of video cameras for each base station. This

number can be calculated based on the base station interface

bandwidth. It is an Ethernet interface and offers 100Mbps and

if the monitoring will be in a LAN (100Mbps) considering that

around 10% will be used for other data there is 90% or 90Mbps

to be used for video surveillance. The maximum number of

video sensors can be calculated using formula (1).

(1) comp. x bit/pixel x frame)(pixels/ Resolution x sec)s/ rate(frame sFrame'

(bit/sec)Bandwidth _ SensorsNr

where comp. is the value of compression (for instance, if the

compression is 10:1, comp. value is 0.1). Whether frames

parameters (that comes from the image processor) are set as:

640 x 480, 24 bit color, 25 frames per second, compression of

10:1, we see that one video sensor occupies around 19Mbps

and for three video cameras, for example, is needed around

60Mbps. The number of sensors depends on resolution and

frame rate and considering a fixed bit per pixel value and a fixed

bandwidth the dependence (using matlab) is given in Fig. 9.



I J E N S

Fig. 8. Connection of the base station with sensors and information routing in the real system

Fig. 9. Max. number of video cameras, 100Mbps network, different resolutions, 24bit per pixel and 20:1 compression value



I J E N S

A system designed for video, alarms and environmental real

time monitoring, requires an accurate calculation of the

bandwidth. The bandwidth will be shared for video cameras

and for environmental sensors, but since the video occupies a

large part of the bandwidth, we pay more attention to the real

time video transmission, without considering bandwidth

occupied by alarms and data of environmental sensors.

In order to optimize the bandwidth, we take into consideration

parameters that are deterministic in video size, like: resolution,

bit per pixel value, frame rate, number of cameras in system and

compression method. In this paper we showed a simple method

to calculate and optimize the bandwidth, by changing: frame

rate, number of video cameras, bit per pixel value, resolution

and compression value. The parameter or parameters that will

be change for

bandwidth optimization depends on system requirements and

for each case we should decide what to change. Whether there

are strictly requirements for a parameter, let say frame quality,

we keep as unchanged this parameter (in our case the minimum

required resolution and bit per pixel value) and operate with

other parameters (in this case: frame rate, number of video

cameras and compression method).

The selected compression method should not affect the video

quality requirements so we may use MJPEG by compressing

each frame or may use MPEG-4 or H264 for a higher

compression [14, 15, 16]. The selection between compression

methods will be based on latency and video quality allowed by

system requirements. The graphics and dependencies showed

above can be used to create an idea for the bandwidth required

in a real case.

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