systems with central monitoring
DESCRIPTION
Systems With Central MonitoringTRANSCRIPT
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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
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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.
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Fig. 3. System with central monitoring in LAN
Fig. 4. Central monitoring system with no standard interface sensors
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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
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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.
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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.
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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
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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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