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Circulation in Computer ScienceVol.

Copyright © 2016 The Authors. This is an open-access article distributed under

the terms of the Creative Commons Attribution License 4.0

unrestricted use, distribution, and reproduction in any medium, provided the

original author and source are credited.

Performance Analysis

Nnamdi Azikiwe University Awka

E. O. Nonum Dept. of Computer Science / Maths

Novena University Ogume, Delta State, Nigeria

ABSTRACT

This work centres on the study of campus wifi hotspot

networks in Nigeria universities, using the Nnamdi Azikiwe

University Awka as a case study. A Campus Wide Area

Network (CWN) provides a means of communication and

collaboration in data intensive environments. These are vital

key factors to building a strong knowledge culture and

facilitating collaborative research for any educational

institution. Network stumbler (Wifi Network Analyzer) and

Iperf were installed on different laptop computers in the

respective Access Points (AP) while being monitored from a

dedicated server running on Mikrotik and wireshark. This was

used in collecting useful data needed for the chara

of the UNIZIK wifi hotspot network in terms of Received

signal strength index (RSSI), Data throughput and

latency/network delay. The AP distance from user is carefully

measured with a meter tape. Performance analysis carried out

on this university wifi hotspots shows that the network offers

a delay of 0.1545s by default that increases by a factor of

0.001s; a data throughput of 37.30Mbps that decreases by a

factor of 0.25Mbps for any user added to the network. Also,

that an RSSI of -35.438dBm was obtained at the AP base

station which decreases by a factor of 0.4925dBm for any 1m

distance away from the APand finally that a traditional

hotspot networks based on IEEE 802.11 series lacks

integrated intelligence for services convergence, QoS

performance and in most cases suffers from interoperability

problems.

Keywords Campus, Wide area Network, Wifi, Access Point, Throughput,

Latency, Received Signal Strength Index.

Internal Users

Students

-Need basic Access to Student resources

- Diverse client devices

- Massive User base

The different access and connectivity needs of the user group

present varying challenges to the network infrastructure

design and its administration [3]. In addition, addressing the

challenges has to be done with consideration for the size and

the scope of the CWN.

Circulation in Computer Science Vol. 1, Number 1, pp: (1-9), May 2016

Available online at www.ccsarchive.org

access article distributed under

Creative Commons Attribution License 4.0, which permits

unrestricted use, distribution, and reproduction in any medium, provided the

Analysis of WiFi Hotspot Network


Computer Science / Maths,

Nigeria

P. O. OtasowieDept. of Electrical Electronic Engineering,

University of Benin,Benin City,

This work centres on the study of campus wifi hotspot

networks in Nigeria universities, using the Nnamdi Azikiwe

University Awka as a case study. A Campus Wide Area

Network (CWN) provides a means of communication and

collaboration in data intensive environments. These are vital

key factors to building a strong knowledge culture and

facilitating collaborative research for any educational

Wifi Network Analyzer) and

Iperf were installed on different laptop computers in the

respective Access Points (AP) while being monitored from a

dedicated server running on Mikrotik and wireshark. This was

used in collecting useful data needed for the characterisation

of the UNIZIK wifi hotspot network in terms of Received

signal strength index (RSSI), Data throughput and

latency/network delay. The AP distance from user is carefully

measured with a meter tape. Performance analysis carried out

ity wifi hotspots shows that the network offers

a delay of 0.1545s by default that increases by a factor of

0.001s; a data throughput of 37.30Mbps that decreases by a

factor of 0.25Mbps for any user added to the network. Also,

s obtained at the AP base

station which decreases by a factor of 0.4925dBm for any 1m

distance away from the APand finally that a traditional

hotspot networks based on IEEE 802.11 series lacks

integrated intelligence for services convergence, QoS

ce and in most cases suffers from interoperability

Campus, Wide area Network, Wifi, Access Point, Throughput,

1. INTRODUCTION A Campus Wide Area Network (CWN) provides a means of

communication and collaboration in data intensive

environments. These are vital key factors to building a strong

knowledge culture and facilitating collaborative research for

any educational institution. It includes the different kinds of

wireless networks that support IEEE 802.11 as well as IEEE

802.3 standards [1]. The

implementation combines the scalability of virtual LANs and

the flexibility of switched Ethernet with the mobility

wireless LAN access. In this type of network, a suite of

general purpose software tools can be deployed to monitor the

status of the network, measure the bandwidth utilization,

control access to the network, and authenticate users.

These networks are found in most tertiary educational

institutions today. A typical campus network interconnects

hundreds of departments across so many buildings, providing

high speed access for both students and staff. Once,

connected, users have access to a wide range of res

such as printers, network file servers, research materials,

lecture notes, tutorials, and even lecture on demand [2].

Other services in CWN includes streaming multimedia,

skyping between classes, peer to peer file sharing.

Applications such as email, discussion forums, bulletin

boards, class schedulers, resource booking systems and

various other administrative applications are also available

through the campus network.

Within the CWN, the users can essentially be partitioned into

three functional groups namely: students, staff and visitors.

These user groups are most often granted different access

rights to resources on the CWN depending on the general

needs of the particular group as shown in Table 1.1

Table 1.1: User groups in a CWN

Internal Users External users

Staff

Need basic Access to Student resources - Need access to teaching and

research resources

- Requires secured access

- long-term user accounts

-Limited access depending on

requirements

- Short term user accounts

-Diverse client devices

The different access and connectivity needs of the user groups

present varying challenges to the network infrastructure

]. In addition, addressing the

challenges has to be done with consideration for the size and

However, the CWN can be achieved with wireless

technologies such as Cellular Systems

3G, B3G, 4G, Satellite Systems, Paging Systems, Cordless

Phone, Wireless LAN, Wireless Local Loop, Wireless Data

Service, Bluetooth, Ultra Wide Band (

Hotspot Network in


Otasowie Dept. of Electrical Electronic Engineering,

University of Benin, Benin City, Nigeria

A Campus Wide Area Network (CWN) provides a means of

communication and collaboration in data intensive

environments. These are vital key factors to building a strong

knowledge culture and facilitating collaborative research for

It includes the different kinds of

wireless networks that support IEEE 802.11 as well as IEEE

802.3 standards [1]. The campus-wide wireless

implementation combines the scalability of virtual LANs and

the flexibility of switched Ethernet with the mobility of

wireless LAN access. In this type of network, a suite of

general purpose software tools can be deployed to monitor the

status of the network, measure the bandwidth utilization,

control access to the network, and authenticate users.

und in most tertiary educational

institutions today. A typical campus network interconnects

hundreds of departments across so many buildings, providing

high speed access for both students and staff. Once,

connected, users have access to a wide range of resources

such as printers, network file servers, research materials,

lecture notes, tutorials, and even lecture on demand [2].

Other services in CWN includes streaming multimedia,

skyping between classes, peer to peer file sharing.

l, discussion forums, bulletin

boards, class schedulers, resource booking systems and

various other administrative applications are also available

Within the CWN, the users can essentially be partitioned into

roups namely: students, staff and visitors.

These user groups are most often granted different access

rights to resources on the CWN depending on the general

needs of the particular group as shown in Table 1.1.

External users

Visitors

Limited access depending on

Short term user accounts

Diverse client devices

However, the CWN can be achieved with wireless

technologies such as Cellular Systems-1G, 2G, 2.5G (GPRS),

3G, B3G, 4G, Satellite Systems, Paging Systems, Cordless

Phone, Wireless LAN, Wireless Local Loop, Wireless Data

Service, Bluetooth, Ultra Wide Band (UWB), hotspot, etc [4].

Circulation in Computer Science, Vol. 1, Number 1, pp: (1-9), May 2016.

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The rest of this paper is organized as follows. Section II

presents review of related works while section III gives details

of the material and methods used in the research.

2. RELATED RESEARCH EFFORTS Various works were studied in relation to campus hotspots. A

review study was carried in Grid WLAN[5] Cognitive hotspot

radio network based on Minipop access point [6], Fuzzy

TCPWLAN[7], and RTC-GWLAN[8]. In most existing

deployments, these wireless implementation formats faces a

myriad of obstacles, but fundamental to the performance of

any system are the propagation characteristics that restrict

delivery of signal power as well as Quality of Service. Also,

deployment scenarios of these networks create interference.

Most hotspots in Nigerian tertiary institutions are faced with

several performance issues as the IEEE 802.11 infrastructures

are not optimized for high density services such as cloud

services [4]. The purpose of this case study is to ascertain the

behaviour and performance of user traffic over the radio

environment of CWN.

3. MATERIALS AND METHODS

3.1 Traditional CWN System Analysis In this section, an analysis of the traditional CWN network

will be carried out so as to help us portray their limitations

Consequently,the Nnamdi Azikiwe University, Awka campus

was visited, its key design features/parameters were obtained

and the performance analysis was carried out.

3.2 UNIZIK Campus Network Testbed Considering the peculiarity of UNIZIK environment, this

work characterizes a real life traditional hotspot testbed in

terms of Received Signal Strength (RSS), Mobile Node

distance, latency and throughput using Mikrotik-AP

Infrastructure in Nnamdi Azikiwe University, Awka. Data

collection was carried out in Awka environment.The main

campus as shown in Figure 2.1 is located on 378 hectares

(3.78km2) of hilly savannah in the town of Awka, about

eighty two kilometers south-west of Enugu and twenty three

kilometers north south of Awka. The Awka campus houses

the Faculties of Agriculture, Arts, Biological Sciences,

Management Sciences, Education, Engineering, Physical

Sciences, Social Sciences, and many research centres.

Figure 2.1: NAU Campus Wifi Traditional WLAN Testbed

The hotspot environment derives network connectivity via the

Mikrotik TR-5800 Series (broadband wireless backhaul

radios) and 2400 TR-AP hotspot technology respectively. The

2400 TR-AP outdoor Wi-Fi base stations runs with 802.11n

in 2.4 GHz and 5 GHz unlicensed bands and in 700MHz

licensed band, offering end-to-end solutions including access,

backhaul, CPEs, management and service provisioning tools.

With up to nine embedded radios, 3x3 MIMO and three

spatial data streams, 2400 TR-AP base stations can offers

theoretical 450Mbps data speeds. The specification used for

the access points are: 2400 TR-AP Base Station, 15806101,

5.8GHz spatially adaptive, multi-radio base station, with an

array of 3 sectorial antennas, 5.8GHz self backhaul, PoE input

(Power over Ethernet injector), Pole mount kit, FCC /TUV

compliant. An integration of the 2400 TR-AP base station

with the 5800 backhaul radio is referred to as a Mikrotik

access point (TR-AP).

In the characterization, consideration was made on a large

area of different locations as basic setting. Due to a potentially

high number of users, several mikrotik TR-APs based on

802.11 that operate on different IEEE channels are placed

within this area. Users appear in these locations at different

points in time and at different places. Firstly, looking at figure

2.1, there have several locations where several respective

Mikrotik-APs are deployed, namely; Admin block,

Engineering Faculty, Law faculty, Chike Okoli, etc. Each of

the backhaul AP terminates in the NOC switching system as

shown in Figure 2.2.


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Figure 2.2: NAU Switching System (Source NAU NOC Admin Block)

Figure 2.3: NAU Battery Bank System (Chike Okoli Centre)

3.2.1. Tools for measurement and Test Places These programs were used viz: Network stumbler (Wifi

Network Analyzer) and Iperf were installed on different

laptop computers in the respective APs while being monitored

from a dedicated server running on Mikrotik and wireshark.

Network stumbler (Wifi Network Analyzer)installed in

android phone captures among other parameters; Received

Signal Strength, signal to noise ratio, latency, but throughput

– used Iperf program while the AP distance from user is

measured with a meter tape. Considering the settings, to

understand the basic performance of the IEEE802.11n during

the test, we disabled Dynamic Host Configuration Protocol

(DHCP), firewalls and other security settings. Static setting

was used to avoid the additional resource consumption on the

server, which is required to create a secure and flexible

wireless connection.

The approach here is to find the bestplace with good

receptivity for various frame sizes; hence, the first experiment

was conducted in NOC (Admin-Block) as shown in figure 2.2.

The location is an open building with several offices whose

ground floor is used for the measurement. Measurement was

carried out up to 100m from the building to the point where

the access point (TR-AP) is mounted. The NAU hotspot

network is an open or flat network where IPs are assigned to

devices dynamically. For each client TR-AP, maximum

allowable user is 1005 owing to the switch capacity.

From the Admin block; NOC, measurements on various

network metrics from users (mobile hosts) scattering at

different locations within the building and to other TR-APs.

Signal measurements were taken by following the network

map of figure 2.1.


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3.2.2 Measurement Infrastructure Equipment

Description To analyse the Unizik CWN, the following devices with their

configurations and settings were used, viz:

i. CWN Switching DataCenter System:

For the testbed, the Mikrotik APs terminates at the NOC

switching modules. The various APs were configured for user

access. Figure 2.2 show NAU main campus switching system

in the setup with the battery bank as shown in Fig 2.3.

ii. Mikrotik AP Antenna

The AP-TR 5800 series which is a broadband wireless

backhaul radios provide high data throughput over long

distances. This was configured to drive data rates up to

54Mbps at Half-Duplex speeds.

Operating in the license-free 5 GHz frequencies. The TR-5800

Series was used in Point-to-Point (PtP) wireless links and can

also be used in Line-of-Sight (LoS) running at 5.3 to 5.8 GHz

backhaul point-to-point solution. The TR 5800 beamforming

technology is:

- Based on TR-AP’s Beamforming Wi-Fi chip

- Leverages up to 3 radio and 3 high-gain antennas for

optimal performance beamforming signal.

- Performs per-packet true beamforming in both the

uplink and downlink

- Exploits multi-path for its advantage by coherently

combining all reflections, thus creating optimal signal

at the receiver with up to 10 dB beamforming gain.

This doubles the range, improves in building

penetration, and increases aggregated base station

capacity as air transmissions are more efficient

- Inherently suppresses interferences by an average of

8dB, thus providing significant advantage in noisy

environments

- Supports off-the-shelf standard Wi-Fi 802.11a/b/g/n

CPEs.

- TR-AP base stations leverage on following unique

technologies and capabilities which further enhance the

technological lead:

- Space Division Multiple Access (SDMA) technology –

enables transmitting to multiple users simultaneously,

thus further increasing the base station capacity

- Dynamic Interference Handling (DIH) capability –

enables continuous adaptation of the air access

parameters according to the noise and interference

level, thus maximizing the base stations capacity in

noisy environments

- Down-tilted antennas – further reduce the noise and

interference levels

- Automatic Channel Selection (ACS) capability –

automatically selects the clearest radio channel for best

radio performance

- Carrier grade – robust mechanical solution with

bottom-up IP-67 design for reliable operation in

extreme outdoor conditions, easy and fast installation,

low power consumption, and enhanced management

solution. Figure 2.5 shows the TR-AP nanostation used

in thetraditional CWN analysis. Figure 2.6 shows the

5800 Backhaul Mikrotik nanostation with mount kit.

Figure 2.5: 5800 Client Mikrotik Nanostations (Author’s testbed)

Figure 2.6: 5800 Backhaul Mikrotik Nanostation with mount kit (Authors testbed)


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Figure 2.7a: Antenna mast with Mikrotik Figure 2.7b: Sectorial Antenna

Backhaul radios (Author’s testbed) (Author’s testbed)

Admin Block (NOC) Ping Connectivity System

Configurations

i. Computer 1 (IEEE802.11g):

- Operating System: Windows Vista Home Premium (6.0,

Build 6002);

- Processor: AMD Turion (tm) 64x2 (2CPUs), ~2,0GHz;

- Memory: 2046MB RAM;

- Wireless g adapter: Atheros AR5007EG Wireless Network

Adapter.

- IEEE802.11g settings: additional channel coding speed up to

¾, OFDM symbol guard interval 800ns and 20 MHz wide

channel.

Android Mobile Phone (Mobile Network: HSDPA):

- Operating System: GINGERBREAD~Android

version 2.3.6 (BV: S5300XXLF5, KV: 2.6.35.7);

- Processor: armeabi @832.9MHz (1 CPU), ~832

MHz;

- Memory: 2GB RAM;

- Wireless HSDPA software: The Broadcom

BCM4329 802.11 network software.

3.2.3 Data Collection and Analysis The switching in the NOC was configured to supports over

10,000 user session and over 7,000 are students with 2 major

servers among the 6 servers in stock (HP proliant 380G5,

370G5 server cluster model running on Linux), hundreds of

switches which rank from 64 to 16 ports were implemented in

NAU campus Wifi open network, and two routers. The server

cluster, on Mikrotik RouterOS V2.5 coordinates the traffic

flow on the NOC. Essentially, users connect to network from

their respective Mikrotik TR-APs from 8am-6pm in the NOC.

The servers maintain reservations across the network and

allocate tenant requests in an on-line fashion. Given our focus

on quantifying the traffic performance in traditional WLAN,

this work then used Wireshark to capture network statistics

alongside with the Mikrotik on the two-server IPs. In this

work, over 1000 data captures were gathered from Admin

block, Management Sciences and School of Arts, but the

average values were used for our traditional hotspot study.

The parameters for data collection system is depicted in Table

2.1. Extended discussions was detailed in section ??

Table 2.1: Traditional WLAN Parameters

Unizik CWN Parameters Specifications

Link Connection TR-AP PtP

Switch ports Two Ports

Terminal Test node Snifers 2 major nodes

Network Architecture WLAN ESS

Network Topology Servers-In-Stars

Wimax AP NO

Server Clustering NO


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Storage Area Network (SAN) Yes

Virtualization NO

RSVP NO

TCP SACK

Coverage 300-500m

Table 2.2 shows the average of data captured from the various faculties, Nnamdi Azikiwe University, Awka

Table 2.2: Performance Metrics DataSet for UNIZIK

DISTANCE

From AP (m)

SNR (db RSSI (dBm) Latency

(Secs)

User Density Throughput

(BYTES/SEC)

5 35.5 -44 0.0000 10 26.21

10 38.5 -46 0.011338 20 67.32

15 38.4 -40 0.01308 30 0.00

20 43.5 -45 0.016744 40 2112.06

25 30.5 -47 0.03401 50 5.31

30 39.5 -48 0.039216 60 0.00

35 46 -55 0.045707 70 746.64

40 44.5 -52 0.59716 80 6.24

45 52.5 -54 0.67431 90 9.81

50 40 -60 0.68394 100 37.61

55 20.5 -59 0.072659 110 183113.37

60 38.5 -64 0.80217 120 2804.63

65 32.5 -68 0.82303 130 4990.89

70 27.5 -66 0.0835 140 8929.90

75 7.5 -70 0.092646 150 179.96

80 15 -78 0.97584 160 11.88

85 19 -72 0.102671 170 27.81

90 15 -81 0.105997 180 40.33

95 23 -84 0.107058 190 1171.10

100 29 -88 0.109879 200 21.56

105 15 -92 0.11 210 0.00


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Figure 2.8: A Plot of Traditional Throughput Behaviour for UNIZIK wifi hotspot

The equation that characterises the behaviour of Data

Throughput as the user density increases is given by:

y = -4.1066x + 9277

with a variance of R² = 4E-05bps.

therefore, the standard deviation (SD) = 0.0063bps. This

means that the network offers a data throughput of 0.9277bps

when no servive user has been added to the network but the

network data throughput decreases by a factor of 4.1066s for

any one user added. The plot of Received signal strength

behaviour is shown in Figure 2.9. Basically, in

telecommunications, received signal strength index (RSSI) is

a measurement of the power present in a received radio signal.

RSSI is usually invisible to a user of a receiving device.

However, because signal strength can vary greatly and impact

on functionality in hotspot scenarios, the IEEE 802.11 devices

often make the measure available to users as captured with the

sniffing tool above. Figure 2.10: shows the network latency

behaviour.

Figure 2.9: A Plot of Traditional Signal Strength Behaviour

The equation that characterises the behaviour of the received

signal strength as as the distance from the access points

increases is given by: y = -0.4925x - 35.438 with a variance of

R² = 0.9545dB. therefore, the standard deviation (SD) =

0.9770s. This means that the received signal strength at the

access point base station is -35.438dB but decreases by a

factor of 0.4925dB for any distance of 1m away from the

access point

y = 4.1066x + 9277

R² = 4E-05

0.00

20000.00

40000.00

60000.00

80000.00

100000.00

120000.00

140000.00

160000.00

180000.00

200000.00

0 50 100 150 200 250

Av

g.T

hro

ug

hp

ut

(By

tes/

Se

c)

Hotspot User Density

Throughput (BYTES/SEC) Vesus Hotspot User Density

Throughput (BYTES/SEC)

Linear (Throughput (BYTES/SEC))

y = -0.4925x - 35.438

R² = 0.9545

-100

-80

-60

-40

-20

0

0 20 40 60 80 100 120

Re

ceiv

ed

Sig

na

l S

tre

ng

th I

nd

ex

(d

BM

)

Distance from the Access Points (m)

RSSI (dBm)

RSSI (dBm)

Linear (RSSI (dBm))


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Figure 2.10: A Plot of Traditional Latency Behaviour

The equation that characterises the behaviourof Network

delay / Latency as the user density increases is given by: y =

0.001x + 0.1545 with a variance of R² = 0.0335s. therefore,

the standard deviation (SD) = 0.5788s. This means that the

network offers a delay of 0.1545s when no servive suer has

been added to the network but the network delay to data

traffic increases by a factor of 0.001s for any one user added.

4. DISCUSSION OF RESULTS From UNIZIK testbed, the following results were obtain:

As shown in figure 2.8, as the user density increases, the

average throughput starts to drop from its peak threshold. This

is peculiar with traditional WLANs From Figure 2.8, poor

quality of service usually results owing to high congestion rate

at peak traffic periods with high network density. Usually,

when the number of users on the network is below a certain

threshold, the network can perform optimally up till the peak

point. Afterwards, a gradual degradation of the output is

observed. This is regardless of the hotspot maximum buffer

configuration. Dynamic controls and intelligent user density

load control is practically difficult to obtain. Poor throughput

in bandwidth limited hotspot network like in Unizik case

study results from 100 users and above, but will eventually

return to its steady state condition with extreme user

dissatisfaction orchestrated by packet drops, network crash,

etc

From the plot of Figure 2.9, as the users move away from the

base station access point, the RSSI drops proportionally which

show that the hotspot devices cannot dynamically manage

user mobility.

In this research, after the investigations and analysis on the

selected testbed, the following were the identified challenges

with the traditional hotspot testbeds, viz: poor scalability,

impaired throughput behaviour, High infrastructure Economy

and peak network congestion.

This findings now makes it imperative to evolve an improved

services convergence network that will offer maasive

scalabiliy, reliable QoS as well addressing interoperability

problems.

5. CONCLUSION In today’s fast paced cloud computing era, QoS in high

density CWN deployment is perceived as a critical asset

considering the end user perspective. The traditional hotspot

networks based on IEEE 802.11 series lacks integrated

intelligence for service, convergence,reliable QoS

performance and in most cases suffers from interoperability

problems. Actual performance results greatly vary particularly

with (a) line of sight issues; (b) Fresnel zone issues; (c)

towers heights (d) noise floors; and: (e) and spectrum issues

such as interference.The challenge of traditional WLAN IEEE

802.11 in transmission delay of sensitive realtime voice, video

and data in this era of cloud computing can be devastating.

Packet drop and QoS degradation in existing CWN is

completely unacceptable. Again, flexibility and excellent QoS

is the desire of every hotspot user in CWN generally. In order

to achieve these, a cognitive hotspot WiMAX driven CWN

that is backward compatible with IEEE 802.11x (IEEE

802.11a, IEEE 802.11b, IEEE 802.11g, and IEEE 802.11n) is

proposed. This is intended for high density Campus hotspot

environment.

6. ACKNOWLEDGEMENT The authors wish to appreciate the ICT unit of Nnamdi

Azikiwe University, Awka, and Kswitche consult for their

supports in providing the relevant materials for this study.

7. REFERENCES [1] S. Banerji, R.S. Chowdhury, “On IEEE 802.11: Wireless

LAN Technology”, International Journal of Mobile

Network Communications & Telematics (IJMNCT) Vol.

3, Issue. 4, 2013. [DOI: 10.5121/ijmnct.2013.3405],

http://arxiv.org/abs/1307.2661.

[2] ANT Labs: http://www.antlabs.com/downloads/

PressRelease/Whitepaper_NUS.pdf, Retrieved on 15th

April, 2015.

[3] An Introduction to Wireless Networking (Part 1) -

802.11, Overview by Andrew Z. Tabona [Published

on 20 May 2004 / Last Updated on 20 May 2004].

http://blogs.aerohive.com/blog/the-byod-blog/an-

introduction-to-80211ac,Retrived on 15th April, 2015.

y = 0.001x + 0.1545

R² = 0.0335

0

0.2

0.4

0.6

0.8

1

1.2

0 50 100 150 200 250

Av

g.l

ate

ncy

Re

spo

nse

(S

ecs

)

Hotspot User Density

Network Latency (Sec) Against User Density

Latency (Secs)

Linear (Latency (Secs))


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[4] C.C.Udeze, Okafor K.C, C.C.Okezie,I.O.Okeke, .G.C.

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