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\begin{document}

             \author[1]{Sandip  Roy}

             \author[2]{Debabrata  Sarddar}

             \author[3]{Rajesh  Bose}

             \affil[1]{  W.B.U.T}

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\date{\small \em Received: 14 December 2013 Accepted: 1 January 2014 Published: 15 January 2014}

\maketitle


\begin{abstract}
        


Space partitioning is the process of dividing a Euclidean space into a non-overlapping regions. Kdimensional tree is such space-partitioning data structure for partitioning a Euclidean plane like the surface of earth. This paper describes a tool-based logically partitioning technique of earth surface using K-dimensional tree to segregate the edge servers over the earth surface into a nonoverlapping regions for the particular Content Delivery Network. Consequently selecting an edge server based on Least Response Time lo ad balancing algorithm is introduced to improve end-user response time and fault tolerance of the host server.

\end{abstract}


\keywords{content delivery network, K-d tree, least response time, load balancing, nearest neighbor search, spatial data structure.}

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\textcolor{GJBlue}{\footnotesize \\ Artificial Intelligence formulated this projection for compatibility purposes from the original article published at Global Journals. However, this technology is currently in beta. \emph{Therefore, kindly ignore odd layouts, missed formulae, text, tables, or figures.}}
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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
ontent Delivery Network (CDN) is a large distributed network of multiple data centers scattered over the earth surface \hyperref[b0]{[1]}  \hyperref[b2]{[3]}. Today CDNs deliver a huge number of internet content including text, scripts and images and also on-demand streaming media files. Content providers pay CDN operators (e.g. Akamai, Mirror Image Internet etc.) for delivering the aforesaid contents to their customer to improve the overall network performance \hyperref[b1]{[2]}.\par
In this paper we have introduced a tool for partitioning earth surface using K-d Tree and also a closest edge server is selected based upon proposed least response time load balancing strategy. II. 
\section[{Background Studies a) Content Delivery Network (CDN)}]{Background Studies a) Content Delivery Network (CDN)}\par
Increasing the global availability of the internet content, improving the page load time and reducing the bandwidth cost CDN edge servers are scattered over the earth surface. When users from different location are requesting for a particular web content which is algorithmically direct to the nearest edge server to achieve the goal. In this paper we have instigated a technique for partitioning earth surface using the K dimensional tree (K-d tree) and select the nearest edge server using least response time load balancing method which is discussed below. 
\section[{b) K-dimensional Tree (K-d tree)}]{b) K-dimensional Tree (K-d tree)}\par
K-d Tree is space partitioning data structure for arranging coordinate points (latitude, longitude) over the earth surface. It can be sub-divided the earth surface into a non-overlapping regions \hyperref[b3]{[4]} [5] \hyperref[b6]{[7]}. In this context we have described an efficient edge server searching technique using K-d tree. 
\section[{c) Least Response Time}]{c) Least Response Time}\par
The Least Response Time is a one of the most popular load balancing technique is used in this context \hyperref[b12]{[13]}  \hyperref[b13]{[14]}. Using the aforesaid load balancing algorithm, to regulate how to dispense load among the edge servers. This paper we have used the network "ping" command to get average response time of the edge servers which are scattered over the earth surface \hyperref[b9]{[10]}. 
\section[{III.}]{III.} 
\section[{Proposed Algorithm}]{Proposed Algorithm}\par
In our proposed algorithm we have prepared an efficient tool for CDN provider which is supervising a CDN to select low latency edge server. The set of edge servers are considered as the set of coordinate points P (e.g. latitude and longitude) scattered over geographical region and here we build a K-d tree using P which is scattered over the earth surface as shown in figure \hyperref[fig_1]{2} and logically partition the edge servers into a nonoverlapping region as like figure 3 \hyperref[b5]{[6]}. Using function kd\textunderscore closestpointsearch, we have found nearest edge servers of the current location of end-user (e.g. Kolkata) \hyperref[b7]{[8]} [9] \hyperref[b10]{[11]}. Then we can calculate accurate network latency using "ping" command over the closest edge servers' IP address to find the minimum average latency time for delivering web content of a particular host server \hyperref[b9]{[10]}. Executing "ping" command we get status( D D D D D D D D )\par
Year 2014 G and result information of the edge server, if the status value is 0 means server is active otherwise 1 signifies the server is dead.\par
Our proposed algorithm is developed using Matlab R2012b which is described below  {\ref [11] [12]}. In figure \hyperref[fig_2]{3}, the black maker is depicted that the current location of end-user and the closest edge server, among different edge servers, is waiting to send the web content to the end user that is our primary challenge.    
\section[{Simulation analysis}]{Simulation analysis}\par
Step 1 : Latitude and Longitude value of different edge servers are assigned in lat and lon array variables, which are enlisted in table \hyperref[tab_1]{1}    Step 2 : The IP Address of different location of edge servers are assigned in ipaddr variables and the IP Address of edge servers along with domain names are listed in table \hyperref[tab_3]{3}.\par
Step 3 : The edge servers are decomposed using K-d tree as shown in figure \hyperref[fig_2]{3}.\par
Step 4 : Using kd\textunderscore closestpointsearch function we have search closest edge server of the current location of end-user and consequently find out the accurate network latency time using "ping" command.\par
Step 5 : The connection is established between least average response time active edge server located at Singapore and end-user from Kolkata for sending the web content as shown in figure \hyperref[fig_3]{4}. 
\section[{V. conclusion}]{V. conclusion}\par
Our proposed tool and simulation results proclaim minimum network latency and minimum packet loss in selection of closest edge server over the earth surface. In this paper we have used K-d tree algorithm for decomposing the earth surface. Usage of kd\textunderscore closestpointsearch method helps us to find the nearest edge server of the end-user. Our proposed tool can be used in wireless network and wired network for delivering the web content efficiently to improve the throughput of total network.  
\section[{Global Journal of Computer Science and Technology}]{Global Journal of Computer Science and Technology}\begin{figure}[htbp]
\noindent\textbf{1}\includegraphics[]{image-2.png}
\caption{\label{fig_0}Figure 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2}\includegraphics[]{image-3.png}
\caption{\label{fig_1}Figure 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3}\includegraphics[]{image-4.png}
\caption{\label{fig_2}Figure 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4}\includegraphics[]{image-5.png}
\caption{\label{fig_3}Figure 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-6.png}
\caption{\label{fig_4}Volume}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.22626970227670753\textwidth}P{0.22626970227670753\textwidth}P{0.23371278458844133\textwidth}P{0.1637478108581436\textwidth}}
\tabcellsep \tabcellsep \tabcellsep Year 2014\\
\tabcellsep \tabcellsep \tabcellsep 15\\
\tabcellsep \tabcellsep \tabcellsep Volume XIV Issue III Version I\\
\tabcellsep \tabcellsep \tabcellsep D D D D D D D D ) G\\
\tabcellsep \tabcellsep \tabcellsep (\\
Location of edge server Kolkata Singapore Colombo London Chicago New Delhi Ankara Islamabad Santiago Mexico Kingston Buenos Aires\tabcellsep Latitude 22.5667°N 1.3000°N 6.9344°N 51.5072°N 41.8819°N 28.6139°N 39.9300°N 33.7167°N 33.4500°S 19.000°N 44.2333°N 34.6033°S\tabcellsep Longitude 88.3667°E 103.8000°E 79.8428°E 0.1275°W 87.6278°W 77.2089°E 32.8600°E 73.0667°E 70.6667°W 99.1333°W 75.6919°W 58.3817°W\tabcellsep Global Journal of Computer Science and Technology\\
Harare\tabcellsep 17.8639°S\tabcellsep 31.0297°E\tabcellsep \\
Cape Town\tabcellsep 33.9253°S\tabcellsep 18.4239°E\tabcellsep \\
Canberra\tabcellsep 35.3075°S\tabcellsep 149.1244°E\tabcellsep \end{longtable} \par
 
\caption{\label{tab_1}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.2325787401574803\textwidth}P{0.19409448818897637\textwidth}P{0.20413385826771652\textwidth}P{0.21919291338582675\textwidth}}
Location of\tabcellsep Latitude\tabcellsep Longitude\tabcellsep Modified\\
Edge\tabcellsep \tabcellsep \tabcellsep Longitude\\
Servers\tabcellsep \tabcellsep \tabcellsep \\
Kolkata\tabcellsep 22.5667\tabcellsep 88.3667\tabcellsep 88.3667\\
Singapore\tabcellsep 1.3000\tabcellsep 103.8000\tabcellsep 103.8000\\
Colombo\tabcellsep 6.9344\tabcellsep 79.8428\tabcellsep 79.8428\\
London\tabcellsep 51.5072\tabcellsep -0.1275\tabcellsep 359.8725\\
Chicago\tabcellsep 41.8819\tabcellsep -87.6278\tabcellsep 272.3722\\
New Delhi\tabcellsep 28.6139\tabcellsep 77.2089\tabcellsep 77.2089\\
Ankara\tabcellsep 39.9300\tabcellsep 32.8600\tabcellsep 32.8600\\
Islamabad\tabcellsep 33.7167\tabcellsep 73.0667\tabcellsep 73.0667\\
Santiago\tabcellsep -33.4500\tabcellsep -70.6667\tabcellsep 289.3333\\
Mexico\tabcellsep 19.0000\tabcellsep -99.1333\tabcellsep 260.8667\\
Kingston\tabcellsep 44.2333\tabcellsep -75.6919\tabcellsep 284.3081\\
Buenos Aires\tabcellsep -34.6033\tabcellsep -58.3817\tabcellsep 301.6183\\
Harare\tabcellsep -17.8639\tabcellsep 31.0297\tabcellsep 31.0297\\
Cape Town\tabcellsep -33.9253\tabcellsep -18.4239\tabcellsep 341.5761\\
Canberra\tabcellsep -35.3075\tabcellsep 149.1244\tabcellsep 149.1244\end{longtable} \par
 
\caption{\label{tab_2}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.1924793388429752\textwidth}P{0.28942148760330577\textwidth}P{0.368099173553719\textwidth}}
Location\tabcellsep IP Address\tabcellsep Domain Name\\
of Edge\tabcellsep \tabcellsep \\
Servers\tabcellsep \tabcellsep \\
Kolkata\tabcellsep 203.197.118.81\tabcellsep www.jaduniv.edu.in\\
Singapore\tabcellsep 137.132.21.27\tabcellsep www.nus.edu.sg\\
Colombo\tabcellsep 192.248.17.88\tabcellsep www.cmb.ac.lk\\
London\tabcellsep 212.113.11.22\tabcellsep www.lse.ac.uk\\
Chicago\tabcellsep 198.101.129.15\tabcellsep www.uchicago.edu\\
New Delhi\tabcellsep 103.27.9.20\tabcellsep www.du.ac.in\\
Ankara\tabcellsep 80.251.40.153\tabcellsep www.ankara.edu.tr\\
Islamabad\tabcellsep 61.5.158.124\tabcellsep www.islamabadairport.co\\
\tabcellsep \tabcellsep m.pk\\
Santiago\tabcellsep 158.170.64.116\tabcellsep www.udesantiago.cl\\
Mexico\tabcellsep 128.123.3.2\tabcellsep www.nmsu.edu\\
Kingston\tabcellsep 130.15.126.136\tabcellsep www.queensu.ca\\
Buenos\tabcellsep 190.224.163.23\tabcellsep www.buenosairesherald.co\\
Aires\tabcellsep 4\tabcellsep m\\
Harare\tabcellsep 196.201.17.237\tabcellsep www.caaz.co.zw\\
Cape\tabcellsep 41.72.141.237\tabcellsep www.capetown.travel\\
Town\tabcellsep \tabcellsep \\
Canberra\tabcellsep 137.92.97.88\tabcellsep www.canberra.edu.au\end{longtable} \par
 
\caption{\label{tab_3}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.2176328502415459\textwidth}P{0.2545893719806763\textwidth}P{0.14782608695652172\textwidth}P{0.22995169082125602\textwidth}}
Location\tabcellsep IP Address\tabcellsep \multicolumn{2}{l}{Status Average}\\
of Edge\tabcellsep \tabcellsep \tabcellsep time(ms)\\
Servers\tabcellsep \tabcellsep \tabcellsep \\
Canberra\tabcellsep 137.92.97.88\tabcellsep Dead\tabcellsep Request timed\\
\tabcellsep \tabcellsep \tabcellsep out\\
Kolkata\tabcellsep 203.197.118.81\tabcellsep Active\tabcellsep 260\\
Colombo\tabcellsep 192.248.17.88\tabcellsep Active\tabcellsep Destinationhost\\
\tabcellsep \tabcellsep \tabcellsep unreachable\\
Singapore\tabcellsep 137.132.21.27\tabcellsep Active\tabcellsep 238\end{longtable} \par
 
\caption{\label{tab_4}Table 4 :}\end{figure}
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\end{document}
