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VOLUME 7

   ISSUE 7

14 FEBRUARY 2012

Article of the Month   Around the World
 

Structure of the World Wide Web and the Internet

 

During late 1990s, a team of researchers led by Albert-Laszlo Barabasi started working on an interesting question – what is the average distance between two randomly selected web pages in the World Wide Web? Since the Word Wide Web is a huge collection of web pages with links to each other, they wanted to measure the average number of hops (or clicks) needed to navigate from a randomly selected source page to a target page. Given that mapping the complete Web is an impossible task, they started off by writing a simple program (a web crawler) to map pages in their university domain and proceeded to map small sections of the Web. Through some mathematical manipulation, researchers were able to extrapolate the results for the estimated size of the World Wide Web (8 x 108 pages in late 1990s) and concluded that two randomly chosen pages in the Web are 19 links (or hops) apart on average. Although 19 links may appear bit large, this is remarkably a small number of hops between two randomly chosen pages given the sheer size of the World Wide Web.

In order to obtain the above result, researchers modelled the Web as a network of web pages (which formed the nodes) connected by links between them. They expected the resulting network to have a random distribution of links. After all, there are no rules in the Web dictating which page should be linked to whom and a random pattern is naturally expected when a huge number of pages are considered. In such a random network, vast majority of the nodes will have an average number of links while there will be a few nodes with either a very large or very small number of links (In mathematical terms, we say the number of links follow a poisson distribution). However, the researchers were amazed to discover that vast majority of the web pages have very few links pointed at them and there are a small number of “hubs” which attracted a large number of inward links. Barabasi and the team coined the term “scale-free” for this type of networks (In mathematical terms, distribution of the number of links per node obeys a power law in such networks). Numerous studies which followed this discovery have concluded that the Internet – the infrastructure of networks on which the World Wide Web operates – also has a scale free structure.

But how can such organised, non-random structures arise in systems such as the World Wide Web and the Internet which do not undergo any centralised management or control? Barabasi and his team have answered this question as well. They have observed two properties which results in the formation of hubs and scale-free network structures – growth and preferential attachment. Regarding growth, both the Internet and the Web started off with few nodes and grew rapidly as mode nodes were added. In such systems, older nodes will tend to have more links than the newer nodes simply because they had more time (and chances) to attract inward links. According to preferential attachment, a new node will favour linking to a hub rather than a node with few existing links – it is a system of “rich gets richer”. This makes sense in the Web since majority of the pages would have links to hubs, which are popular web pages, while few would post a link to your personal web page, unless you are a celebrity. But what is the significance of studying the structure and dynamics of the World Wide Web and the Internet? Well, let’s leave that question for my next post.

(You can download Barabasi’s papers on the structure and dynamics of the Internet and WWW from the following link: http://www.barabasilab.com/pubs-www.php)

Hasala Peiris (MSc.IT ,CISSP) is a Doctoral Research Student and a Sessional  Academic at Curtin University, Perth, Australia..

 
Teen finds bugs in Google, Facebook, Apple, Microsoft code
by Elinor Mills February 2, 2012 2:53 PM PST
 

"When he's not at school, 15-year-old Cim Stordal spends his time playing the Team Fortress video game, shooting his Airsoft pellet gun, and working in a fish shop in Bergen, Norway. But his real passion is finding bugs in software used by millions of people on the Internet..."

Month in Brief

Facebook Incidents Reported to Sri Lanka CERT|CC in January 2012

 

  Fake + Harassment
  Hacked
  Abuse
  Other

Genderwise

  Female
  Male

Statistics - Sri Lanka CERT|CC

 

Alerts

Linkedin Privacy: An Easy How-to Guide to Protecting Yourself                               

Paul Laudanski | Director of the Cyber Threat Analysis Center, ESET

 

LinkedIn is a social network platform whose specialty is connecting professionals together to build relationships and create business opportunity. Recently the company became publicly traded and grabbed the attention of the world as its initial public stock offering more than doubled on the first day…

   

 
  Notice Board
  Training and Awareness Programmes - February 2012  
 
Date Event Venue
- 15-19 "Dayata Kirula" Exhibition Oyamaduwa, Anuradhapura
- 13-17 ICT Training for teacher in charge of connecting classroom project ICT laboratory of ICT branch
- 17 Distribution of XO laptops for 4 schools in Maho zone under" One Laptop per Child Project"
Ariyawa Primary School, Ehatuwewa
Pothanegama  Primary School, Ehatuwewa
Jayanthipura K.V, Giribawa
Gurulupitigama Primary  School, Giribawa

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