An in-building multi-server cloud system based on shortest Path algorithm depending on the distance and measured Signal strength

IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 1, Ver. I (Jan – Feb. 2015), PP 38-42
www.iosrjournals.org
DOI: 10.9790/0661-17113842 www.iosrjournals.org 38 | Page
An in-building multi-server cloud system based on shortest
Path algorithm depending on the distance and measured
Signal strength
1
Abhirup Bhawal, 2
Anindita Nath, 3
Suchismita Mitra, 4
Puspendu Roy,
5
Pradip Kumar Das
Abstract: In this paper we are proposing a system that will work as a virtual cloud computing environment.
Our system will be suitable for an office for example software development firm. Cloud Computing is an
emerging technology now a days. In cloud computing, the resources are shared within a network using web
server. We have designed a cloud computing environment having multiple upload stations and numerous client
nodes. Most commonly, the cloud computing environment has one server and multiple nodes connected with it.
It server multiple purposes at a time. We have designed a cloud computing environment with decentralized
multiple upload stations. In our system, we have assumed that the client nodes can be mobile and it can change
its location according to time. We have also assumed that, the users will not have a fixed working desk and they
can do their work from any desk they want. They need to log in to the system using their pre-defined user-id and
password and he will get access to the system with all features. Now, once a user will try to upload some data in
the upload stations, our system will intelligently find out the nearest server from the location of the client. The
data will be uploaded in that upload station. As all the upload stations are inter connected, if he or she wants to
retrieve that information later, he or she will be able to do that easily. This concept can also be implemented in
multi-floor office area. We are using Bluetooth as the medium of transmission as it is low power consuming and
less costly than other available standard options.
Keywords: Cloud Computing, Upload Stations, Bluetooth.
I. Introduction
The technologies we are using to design the system are cloud computing, Bluetooth, Ad-Hoc Network.
A brief description of those technologies follow.
Cloud Computing
Cloud Computing is computing in which large groups of remote servers are networked to allow
centralized data storage and online access to computer services and resources. Clouds can be classified as
public, private or hybrid. Cloud computing relies on sharing resources to achieve coherence and economies of
scale, similar to a utility over a network. At the foundation of cloud computing is the broader concept of
converged infrastructure and shared services. The primitive goal of cloud computing environment is to
maximize the use of computing power thus reducing environmental damages as well since less power, air
conditioning, Rackspace etc. The present availability of high-capacity networks, low cost computers and storage
devices as well as the widespread adaptation of hardware virtualization, service-oriented architecture and
autonomic and utility computing have led to growth in cloud computing.
Bluetooth
Bluetooth is a wireless technology standard for exchanging data over short distances and operates in
the 2.4 GHz frequency band without a license for wireless communication. This communication protocol has
primarily been designed for low-power consumption and low cost. This technology can be used for real-time
data transfer usually between 10-100 meters which is reasonable within a small building. The data-transfer rate
of the Bluetooth Technology is quite acceptable i.e. 3-4 Mbps. Moreover, the Bluetooth devices require low
power to work. Thus this is low power consuming and it is less costly. As a result Bluetooth is a low power
consuming and cost efficient wireless medium of transmission.
Ad-Hoc Network
The wireless ad-hoc network is used in our project. It’s basically a decentralized, infrastructure-less
network because it doesn’t rely on a pre-existing infrastructure like the routers or access points. The nodes in
this kind of network is completely dynamic. In this system, each node that participates in data transmission,
dynamically determines the node to whom the data needs to be forwarded.

An in-building multi-server cloud system based on shortest path algorithm depending on…
II. Motivation
Cloud computing is an emerging technology of today’s era. It not only makes any system more
efficient and easy to use and access, but also it reduces the requirements of the client machines. Cloud
computing environment serves two purposes. Firstly, the client nodes don’t need to be highly configured to do
the high computing jobs. If we configure the server highly, it will serve the purpose of processing all the
requests from the client nodes. Secondly, the data storage becomes centralized. As a result the chances of losing
the important data due to accidents or server failures become less. But major disadvantage of this kind of
systems is network limitation. The number of channels in a server is limited this is why, the number of users
who can use the system resources becomes limited and it increases the waiting time eventually. As a solution to
this problem we thought of a cloud computing system where there will be multiple upload stations. Thus, the
number of users who can use the system at a time increases. Implementing multiple upload stations we actually
get another important benefit. In existing cloud computing systems the client nodes needs to be fixed, but in our
case the users can also be movable which will make the work environment more comfortable.
III. Methodology
In our system we have considered that we have multiple upload stations working as servers. Those
upload station has fixed location on the floor and those are interconnected. In the following figure a top-view of
the system is shown. In that figure, the blue circles represent the mobile devices and the green circles represent
the static devices.
Fig. 1 – The top-view of our system
This project can be divided basically in two parts. Firstly, we have designed an application that will be
running in each and every user’s machine. This application will make the user able to upload their data to one of
the upload stations. Secondly, during any upload that will take place, we need to determine the nearest server
from the user’s location. Our area of thrust in this project was to handle multiple upload stations and how those
stations can run independently as well as syncing with each other.
A. User application running in every device
We have designed a platform for an office of software development firm. In that application, each user
has to log in using their user-id and password. After successfully logging into the system, they can access
various features like writing notes, saving them in the upload station, running and compiling source codes. For
implementing those features, we used data structures that will be stored in binary files as we tried to avoid the
burdens in the client nodes as well as the upload stations. For each feature, a particular response is being
transmitted to the upload stations or the servers. The upload station is processing the request and sending back
the proper response to the client node. When a user is being registered, a particular block of memory is allocated
to that user, and all the documents or files he or she will be creating will be stored in that place. Each and every
file in the upload stations are stored in an encrypted way to reduce of chance of data misplacement. We are DES
encryption standard to achieve that. Moreover there are some files those are being used for general purpose, like
storing the user-id and passwords of the users. In DES cryptography system, each file is encrypted with a
randomly generated string of characters. In our system to provide the information those are stored in the upload
stations an extra layer of protection, we are changing the randomly generated key string in a timely manner and
encrypting again. Thus if anyone steals any data, it will be tough for him or her to decipher the actual content of
the file. Apart from that whenever we are transmitting any data we are sending the data after encryption. After
receiving the data in the upload station, the data is decrypted and processed after that. Thus, if someone taps the
data on the fly, he will not be able to understand the actual data. There are two parts in this application, i.e. the
server and the client. Fig. 2 depicts the flow diagram that is happening in the client node.

Fig. 2 the flow diagram of the client part of the application
Step algorithm for client:
Step 1 – The client has to login to the system for using the entire system and facilities thus the system prompts
the user to login first.
Step 2 – The login request is generated and sent to the server.
Step 3 – Server responses to the login request.
Step 4 – If the server grants the login for the user, control is passed to step 5 else it is sent back to the step 1.
Step 5 – The user in the client node gets a home screen containing several options to start the work.
In the same manner the server works in our system. The flow diagram and the step algorithm are
described below.
Fig. 3 – The flow diagram for the server part
Step algorithm for server:
Step 1 – The server is always in listening mode.
Step 2 – Request from the client node is received.
Step 3 – the request is checked whether it is a valid request or not.
Step 4 – If the request is accepted and correct in the specific protocol then continue to step 4 else back to step
1 for receiving the next request.
Step 5 – The received request is passed to the request handler.
Step 6 – The request handler finishes the specified task, and then the processed result is sent back to the client
node from where the request has been received.
Step 7 – The control is again sent back to Step 1.
B. Determine the nearest server based on the user’s location
To determine the nearest upload station node, a response request is sent to all the upload stations. Then,
if the upload station response back within a threshold time, the time is stored. According to the times required
for responding back, we are approximately calculating the distance from the client node to the upload station.
Then those distances are sorted in ascending order to find out the nearest upload station. Once we have selected

the nearest upload station, our system is sending the data to that upload station. Fig. 4 depicts the flow diagram
for selecting the nearest upload station.
Fig. 4 – Flow diagram for selecting the nearest upload station
C. Data structure
The entire building block of the permanent data storage system is data structures like, dictionary, list,
tuples etc. We have chosen to use simple text files to store the data permanently and to use basic data structures
extensively as mentioned earlier. We have used dictionary to store several data which is responsible for the user
to grant access to number of services. A dictionary is a special kind of data-structure of python, which support
the following features. Keys must be immutable, and this key can be number, string, tuple or anything, but, it
cannot be changed after creation, because of hashing. And moreover, the keys must be unique again because of
hashing. There are no restrictions of values in a dictionary, and the keys will be listed in arbitrary order1. For
instance, the file responsible for the users to login to the system looks like this: Here, the username field is a
string, containing the username, and there is a tuple corresponding to the key i.e. the username, and the first
field of the tuple contains the password, and the second field contains the string for the generation of the
cryptographic key which we use to encrypt the data stored by the user. There are several other similar kinds of
files containing other related data. For example, the next screenshot shows the text file containing the list of the
files, a user saved in the system. In this case, we have used a dictionary, where the username has been used as
the key, and there is a list corresponding to each key, containing the name of the files saved by the user. As I
have mentioned in the motivation, we are trying to build a system, which will be low power consuming as well
as cost efficient, we have purposely chosen to use data-structures stored in simple text files, instead of database.
As a result the whole system will not be bulky and will be very suitable for the smaller systems as well as for the
larger systems. Fig. 5 depicts one of the data structure used for our system.
Fig. 5 – Data structure showing the files saved the users
IV. Results
The results and the finding of our project are portrayed in this section. The fig. 6 depicts the user
interface that a user gets whenever he or she is logging into the system.
Fig. 6 – The user interface of the user after logging into the system
The next figure i.e. Fig. 6 depicts the results of the encryption and decryption we are using to protect
the information in the upload stations as well as during transmission.

Fig. 7 – Result showing the encryption that is being used in our system
V. Conclusion And Future Work
Our system is working as per our expectation. The algorithms that was initially sketched upon papers
with pencils using the mathematical formulas and concepts are working in a real life system. Moreover, we are
still working in the system to make it further better. In future we will try to integrate this system with body area
network and wearable system so that it can be used to ease our daily life burdens and tasks that we perform
every day.
Acknowledgement
We sincerely thank Mr. Avranil Tah, Founder of ESL and Mr. Arnab Pal, Techno-Marketing
Consultant of ESL for guiding us during the project. Their help in this project really made our task easy. We
faced many difficulties in that period of time, regarding the transmission of Bluetooth which we ultimately
managed to solve by their intense guidance. Moreover, we want to thank our colleagues and friends for drawing
our attention to the most important and vital overlooked points.

An in-building multi-server cloud system based on shortest Path algorithm depending on the distance and measured Signal strength

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An in-building multi-server cloud system based on shortest Path algorithm depending on the distance and measured Signal strength