VISUALIZATION OF MEASURED AND ESTIMATED

NETWORK CHARACTERISTICS OF THE INTERNET

Masahito Shiba

Faculty of Science and Technology, Ryukoku University, Otsu, Japan

Keywords:

Visualization, Network Characteristics.

Abstract:

Information provided by research on the measurement and estimation of network characteristics of the Inter-

net is vast; therefore, it is difﬁcult to understand and analyze it. We developed a system that includes tools to

analyze and visualize both measured and estimated network characteristics of the Internet in order to obtain

useful information from these characteristics. Our tools can process large amount of data on network charac-

teristics that were preliminarily measured and estimated. The tools use geographic information for analysis

and visualization; users can add codes and extend the functions of analysis and visualization. Moreover, users

can easily analyze and visualize the network characteristics of the Internet for various purposes. This paper

describes the visualization of network characteristics of the Internet by the tools.

1 INTRODUCTION

There are numerous studies on the measurement of

the network characteristics of the Internet. Because

it is difﬁcult to measure the characteristics of all net-

work links and nodes on the Internet, these studies

measure the network characteristics of some of the

links and estimate the network characteristics of oth-

ers by using the measured characteristics. Most of the

studies concentrate on performing measurement and

estimation correctly; therefore, techniques for analyz-

ing the measured and estimated data and effectively

utilizing them are not adequately studied. Because

the measured and estimated data on the network char-

acteristics of the Internet is vast, it is difﬁcult to un-

derstand and analyze this data.

We developed a system that includes tools to an-

alyze and visualize the network characteristics of the

Internet in order to reveal useful information. This

system has the following features:

• It analyzes and visualizes large amount of data of

the network characteristics that are preliminarily

measured and estimated.

• It can process network characteristics by using lo-

cations of nodes.

• Users can easily extend the functionality of anal-

ysis and visualization.

Most tools for visualizing network informationare

used to monitor networks, detect abnormalities, and

collect statistical information. With such tools, it is

important to analyze packet transmission in real time.

However, because the Internet has a large number of

nodes, it is difﬁcult to process the measured data in

real time. Therefore, it is important to analyze the

data using various methods for investigating the net-

work characteristics of the Internet.

In a network that has nodes spread over a wide

area such as the Internet, distances between nodes

have considerable impact on network characteristics.

Our system uses geographic information for analyz-

ing and visualizing network characteristics.

The system supports various uses by allowing

users to freely set visualization styles. Moreover,

users can add codes for visualizing data and extend

system functionality so that they can easily analyze

and visualize network characteristics for various pur-

poses.

2 NETWORK

CHARACTERISTICS

2.1 Visualization

Various studies on visualization of network informa-

tion proposed several systems; these systems have the

following features as the key functions of visualiza-

tion:

772

Shiba M..

VISUALIZATION OF MEASURED AND ESTIMATED NETWORK CHARACTERISTICS OF THE INTERNET.

DOI: 10.5220/0003865807720775

In Proceedings of the International Conference on Computer Graphics Theory and Applications (IVAPP-2012), pages 772-775

ISBN: 978-989-8565-02-0

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

• Monitoring network packets and displaying their

information in real time.

• Providing statistical graphs of network trafﬁc

among nodes.

These features are important and useful for man-

aging networks. However, these features are not well

suited for analyzing the characteristics of a network

having nodes spread across a wide area such as the

Internet. Our proposed system has the following fea-

tures:

• It supports networks having many nodes physi-

cally spread across a wide area.

• It is browser-based and applicable in various en-

vironments.

• Its functions are sufﬁciently ﬂexible, and thus can

be used for various purposes.

Because there are many nodes on the Internet,

the number of network links among these nodes that

need to be managed and analyzed is extremely large.

Our system can manage data from a large number

of links and can provide graphs of the data pertain-

ing to speciﬁc nodes according to user demands. In

a widespread network such as the Internet, the loca-

tions of nodes are important information. Our system

has a function for displaying nodes on a map, thus al-

lowing users to visually understand geographical re-

lationships among the nodes.

Although some existing systems can display net-

work informationon a map (Wawrzoniak et al., 2004),

their functions do not sufﬁciently support the analysis

of network characteristics. On the other hand, net-

work managers, network researchers, and internet ap-

plication developers require different information on

network characteristics. Assuming them as users, the

proposed system has various functions for analyzing

network characteristics. The functions of this system

include displaying information and providing graphs

in various forms; therefore, the system can ﬂexibly

support demands of different users as well as can be

applied in various desktop and mobile environments.

2.2 S3

We used the network characteristics data collected by

S3 (a scalable sensing service) (Yalagandula et al.,

2006) that runs on PlanetLab. S3 is a system for

measuring a wide area network; it measures the In-

ternet using the nodes of PlanetLab. In the S3 sys-

tem, software components called sensor pods run on

each node and measure the characteristics of the links

among the nodes. Each sensor pod has modules that

measure various parameters such as latency, loss, and

bandwidth(Sharma et al., 2006; Ribeiro et al., 2003;

Strauss et al., 2003; Mahajan et al., 2003). The sen-

sor pods run their modules at appropriate periods and

perform the necessary measurement.

All sensor pods work in cooperation, and the in-

formation measured by them is collected by the S3

server. In addition, the S3 server estimates network

characteristics. For latency, as an example, the S3

system does not measure the latencies of all links;

it measures the latencies of only a part of the links

and estimates the latencies of other links by using the

measured latencies.

3 VISUALIZATION

Because information on the network characteristics

measured and estimated by S3 is vast, it is difﬁcult

for users to intuitively understand it. In addition,

since the network characteristics of the Internet have

not been extensively researched, the measured or esti-

mated data are not sufﬁciently analyzed. Therefore, it

is difﬁcult to directly obtain useful information from

the measured or estimated data, and the data of the

characteristics obtained from existing research are not

practically used. As a result, because no effective

method has been established to obtain valuable infor-

mation on network characteristics, it is important to

understand the data and reveal whatever valuable in-

formation can be obtained. We have developed a sys-

tem for visualizing the measured and estimated net-

work characteristics of the Internet.

3.1 Display on a World Map

Our system has a database of the network characteris-

tics preliminarily measured or estimated and tools for

visualizing them. Figure 1 shows a tool of the system

that visualizes the network characteristics on a world

map. This tool displays the locations of source and

destination nodes and the links between them using

Google Maps. This tool has the following features:

• Users can see geographical relationships among

nodes.

• Users can select a node and see measured and es-

timated data on the basis of the selected node.

• Users can use the tools in various environments.

To understand the characteristics of a network in

which nodes are spread across a wide area such as

the Internet, consideration of node locations is impor-

tant. This is because the distances between nodes can

be exceedingly long and can affect the performance

of network links; some of the links are spread across

VISUALIZATION OF MEASURED AND ESTIMATED NETWORK CHARACTERISTICS OF THE INTERNET

773

Figure 1: Nodes and links displayed on the world map.

national boundaries and seas. In addition, geograph-

ical locations of the nodes should be considered for

understanding the measured and estimated character-

istics of their links. Our tool enables users to easily

see geographical relationships among nodes by dis-

playing the nodes and their links on a world map.

Moreover, this tool can display a table that lists the

measured and estimated characteristics of all links of

a source node that is speciﬁed by a user. The user

can sort data with respect to various parameters such

as latency or bandwidth, and the tool can display the

results of the best links on the map. Owing to this

function, users can easily see the measured and esti-

mated characteristics of the links on the basis of spe-

ciﬁc nodes along with geographic information.

In addition, another advantage of the tool is that

it can be run in various environments. The tool is

written in JavaScript, and users can run it by using

their web browsers. Most of the popular environments

have web browsers that can run JavaScript; therefore,

users can use the tool in most of the environments.

Users can access the web page and the script of the

tool from a web server. In addition, the tool gets data

of the network characteristics from the web server.

Therefore, only web browsers are required to use the

tool. Because most environments have web browsers,

in most cases, users can run the tool and visualize the

network characteristics without any preparation.

3.2 Display of More Detailed

Information

We developed another tool for analyzing and visual-

izing the measured and estimated network character-

istics in detail using Squeak. This visualization tool

allows users to add codes and extend the functional-

ity of analysis and visualization. The users can easily

add their code by using the environment provided by

Squeak. Moreover, because a Squeak plugin enables

popular browsers to run Squeak programs, the tools

can be run in many environments.

Although the measured and estimated network

characteristics of the Internet are valuable for network

managersand Internet application developers, they re-

quire different parts of these large data in different

forms. The tool allows users to freely deﬁne the form

of displaying the network characteristics and provides

application ﬂexibility for various purposes. For ex-

ample, there are certain types of graphs and tables

that can be displayed as units and users can freely

arrange them in a window of the tool. These units

are called views (Figure 2). Following types of views

are available: System information, Node information,

Histogram of all links, Filtered link graph, Node list,

Link table, Spiral graph, Closest node set graph, Grid

graph, Histogram, and Node correlation.

System Information is a view that displays infor-

mation about the tool and the visualized data such

as the number of links measured and estimated and

the number of sites and nodes used for measurement.

Node information displays detailed information about

a node such as host name, IP address, and its site.

Histogram of All Links is a view that displays a

histogram of the measured or estimated network char-

acteristics of the Internet. Because data of all links are

displayed, users can see the state and trend of the en-

tire network.

Filtered Link Graph is a view that displays the

links that satisfy a condition of the network character-

istics speciﬁed by the user. The links are displayed in

a graph and users can easily see the size of the param-

eters. For example, when Filtered link graph draws

nodes and links using latency, the nodes are arranged

as distances between the nodes in the graph and are

proportional to the latencies between the nodes. Users

can see these latencies intuitively by examining the

lengths of the lines between the nodes.

In addition to displaying information of the entire

network, the tool can display the network characteris-

tics of an individual node selected by a user in detail.

Node List is a view that displays host names of all

nodes, and users can easily select a node in this view.

Link Table is a view that displays the network

characteristics of the links whose source node se-

lected by the user in a tabular form. The user can

sort data with respect to latency and bandwidth and

can easily see the nodes that have good links with the

source node.

Spiral Graph is a view that displays the links be-

tween a speciﬁed source node and the destination

nodes that have the best links with the source node in

IVAPP 2012 - International Conference on Information Visualization Theory and Applications

774

Spiral graph. Grid graph. Closest node set graph. Histogram.

Figure 2: Views.

a spiral form. Nodes are drawn as boxes and are color-

coded according node locations. Users can intuitively

see that the nodes of similar colors are closely located.

Users can select a parameter to extract good links and

set the number of links to be drawn in the graph. The

source node is arranged at the center of the graph and

the distances between the source node and each desti-

nation node are set according to the network charac-

teristics. For example, for the case in which latency

is used for the evaluation of links, a destination node

that has a small latency link with the source node is

drawn close to the source node. The destination nodes

are sorted by the network characteristics and arranged

on the graph in a spiral form.

Closest Node Set Graph is a view that displays

the graph of a speciﬁed node and some nodes that

have the best links with the speciﬁed node. The dis-

tances between each node are calculated according

to network characteristic parameters such as latency

and bandwidth, and the nodes are arranged according

to the calculated distances between them. Users can

change the parameters to calculate distances and the

number of nodes to be displayed.

Grid Graph is a view that displays the graph of

nodes that have good links in a grid form. This view

draws nodes starting with a node speciﬁed by the user

and arranges other nodes with the best link side by

side. The evaluation of links is expressed by the thick-

ness of the lines that connect the nodes. For example,

lines of small latency links are thick.

Histogram displays all the links of a speciﬁed

source node. Users can select a parameter to display,

such as latency or bandwidth. Although some views

such as spiral graph display only a part of the links

of a speciﬁed source node, histogram displays all the

links of a speciﬁed source node, and users can easily

see the state and trend of the links of the node.

Node Correlation is a view that displays correla-

tions between a speciﬁed node and other nodes. Users

can select a parameter to calculate correlations, such

as latency or bandwidth. It is believed that nodes with

strong correlations are closely located.

Users can arrange these views in the window of

the tool and visualize the network characteristics in

various ways. Because of this ﬂexibility, the tool can

be used by users for different purposes

4 CONCLUSIONS

This paper describes the tools of system for analyz-

ing and visualizing the network characteristics of the

Internet. The tools of the system can process large

amount of data on network characteristics that were

preliminarily measured and estimated. The tools use

geographic information for analysis and visualization

and enable users to add codes and extend the function-

ality of tools of the system. Users can easily analyze

and visualize the network characteristics of the Inter-

net for various purposes.

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