=Paper=
{{Paper
|id=Vol-1538/paper-07
|storemode=property
|title=Design of Network Infrastructure of a Cloud Data Center for use in Health Sector
|pdfUrl=https://ceur-ws.org/Vol-1538/paper-07.pdf
|volume=Vol-1538
|authors=Chris Talavera Ormeño,Julio Santisteban
|dblpUrl=https://dblp.org/rec/conf/latincom/OrmenoS15
}}
==Design of Network Infrastructure of a Cloud Data Center for use in Health Sector==
https://ceur-ws.org/Vol-1538/paper-07.pdf
7th Latin American Workshop On Communications - 2015
Design Of Network Infrastructure Of A Cloud Data Center For Use In
Health Sector
Chris Talavera Julio Santisteban
Urb. Campiña Paisajista s/n Barrio Urb. Campiña Paisajista s/n Barrio
de San Lázaro, Arequipa, Perú de San Lázaro, Arequipa, Perú
Universidad Católica San Pablo Universidad Católica San Pablo
chris.talavera@ucsp.edu.pe jsantisteban@ucsp.edu.pe
Abstract—This article presents the design of the network in- Cloud, Community Cloud and Hybrid Cloud which combine
frastructure of a Data Center that meets the requirements arising two or more forms of clouds (private, community or public)
from Cloud Computing, for use in the Health Sector of Arequipa [2], [8], [3], [12].
city, focusing on network layer 2 and its dimensionality to
meet the requirements of several health service applications. The Cloud infrastructure consists of data centers that hosts
network infrastructure dimensionality calculation is a complex servers and using different levels of organization or virtu-
challenge for an of the ground project , in this article we present alization techniques it offers cloud services [24]. A logical
a novel approach to solve this challenge. view of a Cloud Data Center (CDC) shown in 1. This
Index Terms—Data Center, Cloud Computing, Network Design. model represents the basic components or building blocks of
any CDC. This view introduces encapsulation and insulation
I. I NTRODUCTION layers and impose support system modularity. There are differ-
ent layers: infrastructure, databases, middleware, applications,
We live in a connected world. Almost two billion people management, monitoring and security layer, which one have
connect to the Internet and to address this need the community specific roles and consolidated once formed the Data Center
of information technology has created a new service deliv- in Cloud.
ery mechanism called "Cloud Computing". In the healthcare
industry, Cloud Computing might be a paradigm shift in the
use of information technology, among others: transparent man- III. S TATE OF THE A RT
agement and access to electronic health records of patients, There are many benefits by incorporating Cloud Computing
secure and reliable data storage and transmission, automation in the healthcare industry, but to implement that, the design
processes, streamlining workflow and consolidate assets of of a Data Center of next generation is necessary, thereby,
information technologies for providers of healthcare services; some services providers have developed a reference archi-
thus leading to obtain a higher quality of service. tectures, for example Cisco [20], proposes an architecture
Cloud computing especially facilitate the provision of which consists of three blocks: the first block is composed
healthcare products and services to patients in remote areas by network, computing and storage, this layer houses all the
and those who have limited access to quality medical services. services provided to consumer. The second block is security
For that reason, comunication infraestructure has to be power- layer, the key point is that security should be end-to-end
full and it needs a hardy data center. Having a data center is not architecture. The third layer is about infrastructure and services
a new idea, but they need to make some changes to support managment. This architecture just shows goals to take account
the specific characteristics of Cloud Computing in the most on the creation of Cloud Data Center but does not deliver a
optimal way. Therefore, this article shows how to design a clear methodology.
network infrastructure using as a stege the MINSA (Ministerio Concerning the design of the data center network on [6]
de Salud) namely system of Healthcare in Arequipa, Peru. can be found the more used topologies types, as a the Fat
Tree topology, consisting of two sets of elements, the core and
II. T HEORETICAL F RAMEWORK Pods; the Bcube topology that was proposed for Modular Data
The National Institute of Standards and Technology (NIST) Center, building to allow installation and procedures simpler
define Cloud Computing as a technology model that enables physical migration compared with regular Data Centers and
ubiquitous, adapted and demand access network to share a DCELL topology defined recursively and uses servers for
set of configurable computing resources that can be quick packet forwarding [25].
provisioned and released with management efforts reduced or Another important issue of Cloud Data Center are the
minimal interaction of the service provider [2], [8]. The main virtualization techniques, respecto that [14] shows evidence
features of Cloud Computing are self-demand, comprehensive that the latest network technologies have not been developed
network access, resource pooling, scalability, it is based on keeping in mind the needs of virtualization, and as a result,
the supply of services mainly Software as a Service (SaaS), the network can become a bottleneck for these implementa-
Platform as Service (PaaS) and Infrastructure as a Service tions. This article, also expose that static topologies require
(IaaS) and there are 04 types of Cloud: Public Cloud, Private manual intervention to deploy and migrate virtual machines,
Copyright © 2015 for the individual papers by the papers’ authors. Copying permitted for private and academic purposes. This volume is published and
copyrighted by its editors. Latin American Workshop On Communications' 2015 Arequipa, Peru Published on CEUR-WS: http://ceur-ws.org/Vol-1538/
Figure 2. IT Parameters
Year Attentions
2011 2 770 054
2012 2 920 191
2013 3 078 465
2014 3 245 318
2015 3 421 214
2016 3 606 644
2017 3 802 124
2018 4 008 199
Table I
P ROJECTION OF USERS - ANUAL ATTENTIONS
A. Current Situation of MINSA
Overall, the potential beneficiaries in healthcare industry
is the staff working in MINSA: health professionals, admin-
istrative staff and patients. On [Guias MINSA] it is shown
that in Peru there are various categories of establishments
which respond to different social and health realities and
they are designed to meet demands equivalent. Thus, the
level of complexity of the care services is directly related to
health service development, specialization and modernization
of its resources. There are 111 health facilities located in the
province, which are distributed as I-1, I-2, I-3, I-4, II-1, II-2,
II-E,III-1, III-2, III-E.
Figure 1. Reference Architecture Cloud Data Center
which adds cost and hinders the ability of the organization B. Design Parameters
to respond quickly to changes in the environment, for that For proper planning process of infrastructure cloud data
reason OpenFlow is presented as an open source standard center, three fundamental IT parameters has to be considered:
designed to address these shortcomings. Based on Ethernet criticality, capacity and growth or expansion plan. It is shown
technology, OpenFlow separates the data path and control in the 2 that only criticality and growth plan directly affects
path by an independent controller. This introduces a new the design of the network infrastructure [16].
network abstraction layer, analogous to server virtualization,
According to [5]] to choose this parameters there are several
in consequence allows the network to act as a single structure.
methods for example the TIER UPTIME which gives 4 levels
The benefits are simplicity, being open, scalable and fast.
of availability. A second method is tied to TIA 942 [1], [17]
where the division of 4 levels or Tiers is standard: TIER
IV. D ESIGN OF C LOUD DATA C ENTER I for basic infrastructure without redundancies, TIER II for
Infrastructure components with redundant capacity, TIER III
In this section is proposed the solution of Cloud Data for redundancy N+1 and TIER IV infrastructure for fault-
Center, the first step is identified the current stage of the tolerant 2(N+1). For a healthcare cloud data center it is
healthcare industry specially the main beneficiaries; in the considered TIER IV.
second stage design parameters are defined. The third process The first step of design of Cloud Data Center is understand-
is develop the analysis of network traffic; in the fourth step ing the needs of the healthcare industry, therefore, the number
different network topologies are identified and compared with of network users considering the use of statistical data was
each other in order to choose the best performance. The final projected, as Perú has a constant growth, the average annual
step is to perform the dimensioning of links and finally the growth rates is 5.42% . The projection per each year is shown
Data Center interconnect with each of the health centers. in I and II.
Year Medical Staff Administrative Staff
2011 3 173 851
because Cloud Computing, as part of scalability, automatic re-
2012 3 419 973 sources allocation is performed using mechanisms autoscaling
2013 3 684 1 113 where alarms are configured appropriately to respond in the
2014 3 969 1 273
best way to a requirement, precisely the most used algorithms
2015 4 276 1 456
2016 4 607 1 665 keep on queuing theory [11], [13], [21], [10], [18].
2017 4 964 1 904 The queuing model used is denoted as M/M/c/c, Where M
2018 5 348 2 178 is a system of arrivals that occurs according to Poison process
Table II
P ROJECTED NUMBER OF WORKERS IN MINSA ratio of λ, where the arrival times are exponentially distributed
with mean µ, c represents the number of servers and the
maximum number of customers system´s allowed (when c + 1
Implicated Fc (%) ρhora (Erl.) ρhorapico (Erl.)
80 122 140
requests coming into the system, the service is denied for the
Patient 65 99 114 latter).
40 6 7 In addition, as a parameter of quality of service has decided
80 3 4
Medical Staff 65 2 2
to consider the total response time of the service(s) for a Cloud
40 2 2 Data Center should not be over 450ms [18]. It may have been
Administrative Staff 100 2 2 chosen as a quality parameter the CPU utilization of the server,
Table III
T RAFFIC INTENSITY BY TYPE OF HEALTHCARE USERS
which according to[13] should be at least 85%.
Thus, following Little relations and queuing theory, the
following relationship was obtained (1) [18], [7], [19].
C. Traffic Analysis µ
s= λ (1)
∗µ
In this section the calculation of minimum, maximum and 1 + cn
margin for the network throughput is found, in this way the
goal is comply with the parameters of future growth. Using the where:
concurrency factor (CF) which determines the ratio between s : Average service time
total simultaneous users and users who use the network in the λ : Arrival rate
day, not having accurate statistics, an analysis is made for each µ : Service time
involved in the healthcare industry. c : Number of servers
Criteria or considerations for the calculation of traffic: n : Number of cores server
1) The peak time is 10 to 20% of daily traffic, so they will The first required parameter is the arrival rate to the system
take 15% to make the calculations. (λ), Number that can be taken as the maximum network
2) FC for each involved in the health industry was found, throughput, 141 Erlangs plus margin of 15 Erlangs, ie 161
IE, patients, health and administrative staff. Erlangs. Regarding the length of service, is necesary to know
how long a server take to process a request, no doubt this
The III summarizes the data obtained and thereby the require-
parameter is random, but an approach can be arrive with
ment for the network is known.
some tests such as those in [18], where different instances
Respecto to growth parameters defined, the IV shows the
are analyzed in Amazon, so the average value is 178ms (µ).
minimum, maximum and margin capacity.
It has also considered a single core server (n = 1) And the
average service time is 450ms. The number of required servers
D. Definition of Network Servers is 48, which should form clusters or it have to be virtualized.
Although the determination of servers of CDC is essential, In order to test these results, real cases have been investi-
there is no standard way to find the exact number of these gated, in this way it is possible to have a more realistic idea
devices [18], this reality is that any service provider that offers of how many servers would be required in an environment of
Cloud Computing had to start him infrastructure from zero, is Healthcare. So, first a survey was conducted to people involved
actually found in the process of adapting their traditional data of Information Technology area with goal to know the used
center to the new trend. way that they use to perform sizing of servers and the most
In this paper, the number of servers was calculated based on used applications; the survey and its results can be seen in [15].
the modeling of the process to entry to themselves, using the On the other hand, statistics of the use of networks, servers
queuing theory and prefixing a parameter of quality of service and applications that run on public institutions was obtained,
as: time of service or the CPU usage threshold. This idea borns as well as the number of concurrent users that it houses. The
important thing is to know how many cores of 1GHz each
Parameter Quantity (Erl) Total (Erl) institution uses on their network and how many concurrent
Max. Throughput 146 161 users are allowed. In theV, the information is shown.
Min. Throughput 127 142 The data presented show a ratio factor equal to 0.049,
Margin 15 through it the necessary number of cores is calculated to allow
Total 288
Table IV
421 users, which is the number of jobs per peak hour at this
G ROWTH PLAN PARAMETERS stage. The total number of servers to use is 27, according to
real statistics, this result shows that the formula previously
Institution Cores 1GHz % Use Real Cores Concurrent Optimizes
All Uplink Extesión Scaling
users the density
in active VLAN between link
Provincial Municipality of 11.90 80 9.52 200 of Access
state support Switch
Arequipa Switch
District Municipality of 34.36 60 20.62 350 Trinagle
NO YES NO NO
Cerro Colorado Loop
Arequipa Judiciary 59.20 70 41.44 800 Square Loop YES YES YES YES
Catholic San Pablo 96.00 60 57.60 1300 U free Loop YES NO YES NO
University Inverted U
YES YES YES YES
Table V free loop
S TATISTICAL INFORMATION FROM SERVERS AT DIFFERENT INSTITUTIONS Table VII
C OMPARING DESIGNS L AYER 2 NETWORK
Fat - Tree DCell BCube
Scalability Good Excelent Good
Incremental Good Poor Poor
Scalabily The hierarchical model divides networks into modular blocks:
Agility Yes Yes Yes access layer, distribution, and core, the next step in design to
Cabling Easy Very Dificult Dificult CDC consist of to select features for each layer in order to
Switch fault Poor Good Good
tolerance
improve network performance. Thus, the core layer should be
Link fault tolerance Good Very Poor Poor work on Layer 3 of the OSI model to enable the core links
Server fault God Very Poor Poor to achieve scalability, rapid convergence and to avoid risk of
tolerance
uncontrollable broadcast.
Throughput Constant Incremental Incremental
degradation degradation The aggregation layer is very important as this determines
Cost Regular Low Low the stability and scalability of the entire data center network,
Tráffic balance Yes No Yes
Table VI
as recommended in [22], it is best to model the aggregation
C OMPARATION BETWEEN TOPOLOGIES OF C LOUD DATA C ENTER layer switches with pairs of interconnected modules that
provide services such as content switching, firewall, intrusion
detection, and network analysis. Redundancy is important to
consider, in this sense, integrated services will be defined in
used to calculate the number of servers, allows us to have a
the "active/active" mode.
reliability of about 57%, which can be improved if we use
The access layer works in layer 2 and the model with square
another queue.
loop was chosen, because its resistance to failure is greater
compared to model-free loop in addition, the comparison made
E. Network Topology in the VII shows that this topology provides benefits such as:
Each topology network has several advantages regarding extension of VLAN, virtual machine mobility, service module
performance, remember that there are many dimensions to redundancy.
characterize this parameter, such as: latency, bandwidth, cost, In this CDC network design a subnet storage must be con-
resistance to failure, etc. sidered, specifically a SAN (Storage Area Network) because it
In VI a summary of the comparison of technologies is is a subnet with high speed storage devices. It is an important
presented, considering the above data and some others taken part of design therefore it allows a high throughput and lowest
from [6] and its translation to the different dimensions of latency which creates a high performance across the network.
performance. To find the size of the links in the network, calculate the
By the above comparison, it can be stated that the hierar- current and future demand for traffic per user is needed,
chical Fat-Tree topology is the best suited for network design therefore, an estimated analysis of the various applications
Cloud Data Center. Even though Fat-Tree topology is not per- and services that use each involved in the industry is made
fect in fact its biggest problem is the emergence of bottlenecks health. But this analysis of traffic must not specifically take
in the root of the tree, but its advantages and differences with each application else must make a distinction made by type of
other network topologies make to take the decision to use this traffic. It is important to note that various services of Cloud
design topology of the network architecture. Computing (SaaS, PaaS or IaaS), does not introduce a new
Considering the traffic analysis and the procedures per- traffic pattern themselves instead, they should be seen as a
formed to find the number of network servers, the number new way of consuming different resources [20].
of ports required for each server can be calculated, because For each applications or services more important the traffic
a fat-tree topology is constructed by k-ports and can support ua calculated, considering in each case the concurrency factor,
3
a 100% throughput performance between k4 servers, using k2 VIII shows the results.
border switches and k2 aggregation [6], [23]. Then, the analysis establishes that the peak bandwidth
Therefore, theoretically it has: required by the network user is 3.16 Gbps. To avoid saturation
1) Number of ports: 6 on network ports, these should be at least twice the calculated
2) Number of pods: 6 capacity, ie. about 6.31 Gbps. Therefore the network ports of
3) Number of core switches: 6 access switches must be 10 Gbps.
4) Number of aggregation switches: 3 To calculate the speed of the backbone links distribution
5) Number of access switches: 3 Poisson formula is used to find the probability of arrivals to
Individual Capacity Traffic Type Individual Capacity (Kbps)
Applications Total TRraffic (Mbps)
(Kbps) Telephony over IP 22.58
Telephony over IP 88.8 37.69 Video over IP 884.74
Vídeo over IP 2 530.0 1 073.86 Messaging 0.088
Mail 2.58 11.97 Data Bases 94.38
Data bases 94.38 893.02 File Sharing 11.38
Share files 11.38 59.95 Internet Download 11.38
Internet Download 11.38 68.52 Access Web Pages 56.89
Acces to Web Page 56.89 342.50 Table IX
Complementary 669.8 691.80 I NDIVIDUAL CAPACITY BY TYPE OF TRAFFIC
services
Total (Mbps) 3.39 3 156.46
Table VIII
T OTAL CAPACITY FOR NETWORK SERVICES
Figure 4. General view of Cloud Data Center
distribution of MINSA patients and staff by level of care and
health establishment category, so individual capacity traffic
Figure 3. Network Diagram type is shown at IX.
On the other hand, because the information handled in the
healthcare industry is very delicate, it is important to consider
the up-link ports, based on 2. a backup to the whole network, but for Cloud Computing the
e−λ (λ)r current traditional model of active Data Center and passive
P (r) = (2) Data Center, has to be replaced by a new model of extended
r!
single data center, in which the different locations DC look as
Where:
if they were a single seat and the service is actively provided
P (r) : Probability of arrivals to up-link ports
from different physical locations. Therefore the network in
r : Number of arrivals to up-link port
general, will be seen as shown in 4.
λ : Average rate of arrivals to up-link port
To calculate, we need the number of ports of each switch,
at this case 6 but adding redundancies will take as approx. V. C ONCLUSIONS AND F UTURE W ORK
12 ports. Thus, assuming that switches of 12 ports is used, 1) It has been identified the technical mechanisms required
the number of simultaneous arrivals is at least 12, the average for the design of network infrastructure Cloud Data
speed is 12 arrivals per unit time and probability of arrival in Center, these are: Criticality through which we can
the up-link will be 0.11437. The result is used to calculate the choose according to the characteristics of applications
speed links up-link Access Switch, by3, proposed by[9], [4]. available network; Capacity and Growth, these design
factors set out to find the maximum and minimum
network load and an expansion margin considering it
V el.ptosup−link ≥ (N úm.ptos)∗(V el.ptoshalf −duplex )∗P (r)
should be a short time because it is active equipment
(3)
and technology in general.
Therefore, the above result is determined the speed uplink
2) This work has completed an estimate of network traffic,
ports it must be greater than 13.7244Gbps, so the ports should
based on an analysis of the reality of health facilities and
be 40 Gbps or 100 Gbps for the smooth operation of the
in general of the MINSA (Ministry of Health), it is also
switch and the entire network is ensured. The network design
thought of short growth of the number of beneficiaries.
is shown at 3.
Thus, it is estimated that the network requires links 10
and 40 GbE. On the other hand, via a mathematical
F. WAN Interconnection formula validated through statistical defined design that
To find the speed of the WAN links that reach health facil- requires about 48 servers of 1 core.
ities traffic demand of each one must be calculate. To achieve 3) A data center is a centralized area for storage, handling
this, the first step is to calculate the individual requirements of and distribution of data and information, which consists
each person according to the type of traffic and then make a of several components such as network infrastructure,
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