International Journal on Advanced Computer Theory and Engineering (IJACTE)
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DATA EXTRACTION FROM WIRELESS SENSOR NETWORK
WITH CLOUD COMPUTING
1
Athira.M.S, 2Madhu.N
M.Tech,4th semester, Asst. Professor,
CSE, AIT, Bangalore
Email ID: athiraratheesh2009@gmail.com, Madhu.N@acharya.ac.in
dependent on monitored environment. Based on the
monitored environment, network size in WSN varies.
For monitoring a small area, fewer nodes are required to
form a network whereas the coverage of a very large
area requires a huge number of sensor nodes. For
monitoring large environment, there is limited
communication between nodes due to obstructions into
the environment, which in turn affects the overall
network topology (or connectivity) [1]. All these
limitations on sensor networks would probably impede
the service performance and quality.
Abstract: WSN have several applications in different
domains.wsn enables the information gathering across the
spectrum of endeavour including environmental
monitoring, home automation, tracking, health care,
business etc. But the gathered information is not used
adequately because of the lack of expertise and storage for
further use. to overcome this problem gathered data is
transformed in to a valuable resource like cloud. a new
framework is proposed for WSN integration with Cloud
computing model, existing WSN will be connected to the
proposed framework. This framework enhances the
wireless sensor applications by integrating sensor networks
with the cloud technology. The integration controller unit
of this proposed framework integrates the sensor networks
and cloud computing. The resultant system offers
reliability, availability and extensibility.
II. CLOUD COMPUTING
Cloud Computing is a technology that uses the internet
and central remote servers to maintain data and
applications. It is a type of computing that relies on
sharing computing resources rather than having local
servers or personal devices to handle applications.
I. INTRODUCTION
Wireless sensor network is used in many fields. Sensors
collect a huge amount of data but this data is not used
adequately because of the lack of storage and expertise.
To overcome this problem we integrate the wireless
sensor networks with cloud technology. Cloud
Computing is principally designed and promoted to be
data centre centric and efficient interaction with the
outside world is an area where improved solutions are
being sought. WSN are designed to collect data in the
real world [6]. There is a possible linkage between WSN
and Cloud Computing and the eventual shift of data into
the cloud and over time into the public domain.
WSN architecture could be either centralized or
distributed. In centralized architecture the central node is
the weak point of the network. If it fails, whole network
collapse. However, distributed architecture provides
failure resistant sensor network. Wireless sensor
networks design constraints are application specific and
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ISSN (Print): 2319-2526, Volume -3, Issue -1, 2014
75
International Journal on Advanced Computer Theory and Engineering (IJACTE)
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IBM report stated that "Cloud is a new consumption and
deliver model for many IT-based services, in which the
user sees only the service, and has no need to know
anything about the technology or implementation" [2].
NIST classify the cloud computing as "Cloud computing
is a model for enabling convenient, on demand network
access to shared pool of configurable computing
resources" [3]. The cloud computing have three
architecture layers mainly Software-as-a-Service SaaS),
Platform-asa-Service (PaaS) and Infrastructure-as-aService (IaaS). SaaS provides board market solutions
where the vendor provides access to hardware and
software products through portal interface [4].PaaS
supplies all the resources required to build an
applications and services completely from the internet
without having to download or install the software. Paas
include application design development, testing and
deployment and hosting.
AS. EN implements Kerberos in order to authenticate
the user with AS. ACDU is used to enforce the policy
rules. It consists of RBAC (Role Based Access Control)
processor and policy storage. It communicates with
ACEU through SS[16]. After successful authentication;
user is given the access to the resources as constrained
by the access policies. Now the user can send the data
request. This request is forwarded to the Request Server
(RS). RS will create a subscription on the basis of this
request and forward this subscription to the Pub/Sub
Broker. The pub/sub Broker compares each subscription
with the published data event in the event queue with the
event matcher. If Pub/Sub Broker finds any subscription
match it will start retrieving data from the DPU and
forward the data to the user via the RS and the Cloud
thread.
This research article presents a framework which
integrates cloud computing and WSN. The objective is
to facilitate the shift of data from WSN to cloud
computing storage so that it may be further utilized in
scientific and economic analysis.
IaaS provides consumers with an opportunity to
consume processing, storage, network, and other
fundamental computing resources. Here the consumer is
able to store data, deploy and run arbitrary software such
as operating systems and applications[5]. The consumer
does not need to control and manage the underlying
infrastructure but has control over the operating system,
applications, storage, and network components.
The propose system suggests that sensor nodes and
Integration Controller (lC) can interact through SOA.
Sensor nodes are considered as service providers and
sink nodes are consumers, they receive information
through Ie. The sensor nodes are deployed into the
application server as service description. It has location
information and provides a service end point, a target
namespace and a transport name. These components
exchange messages in xml format.
A Sensor-Cloud collects and processes information from
several sensor networks, enables information sharing on
big scale, and collaborates with the applications on
cloud among users. It integrates several networks with a
number of sensing applications and cloud computing
platform by allowing applications to be crossdisciplinary that may span over multiple organizations.
[15].
A.
Access Control Enforcement Unit
ACEU is used to authenticate the user and it is consists
of EN and three servers i.e. AS, TGS and SS. The
request received by EN is sent to AS. EN implements
Kerberos in order to authenticate the user with AS.
III. PROPOSED FRAME WORK
OVERVIEW
B.
The major components of the framework are Data
Processing Unit (DPU), Publisher/Subscriber Broker,
Request Subscriber, Identity and Access Management
Unit (lAMU)[18] and Data Repository (DR). The data
that collected by the sensors are passed through a
gateway to the DPU. The DPU that converts the data in
to the storage format and store the data in to the data
repository. DPU which will create a published data
event and send the event to an event queue at the
Pub/Sub Broker .Users will connect to the Cloud
through the secured IAMU (Identity and Access
Management Unit). This will provide both
authentication and access control. The IAMU systems
have two major components: Access Control
Enforcement Unit (ACEU); and Access Control
Decision Unit (ACDU). ACEU is used to authenticate
the user and it consists of Edge Node and three servers
i.e. Authentication Server, Ticket Granting Server and
Service Server. The request received by EN is sent to
Access Control Decision Unit
ACDU is used to enforce the policy rules. It consists of
RBAC processor and policy storage. It communicates
with ACEU through SS. After successful authentication;
user is given the access to the resources as constrained
by the access policies.
C.
Communication flow between User and IAMU.
The description of different messages those have been
exchanged among different servers and edge node (EN)
are left out of the scope of this poster due to the space
constraint .
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ISSN (Print): 2319-2526, Volume -3, Issue -1, 2014
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International Journal on Advanced Computer Theory and Engineering (IJACTE)
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Fig: 2 Sensor-Cloud Integration Framework
IAMU includes Diffie-Hellman, Kerberos, Role Based
Access Control and XML [16]. The main rationale of
this model is first, to provide authentication between
consumer and cloud provider. Second, to provide policy
based access control over the cloud resources.
Consumers
directly
communicate
IAMU
for
authentication and access control. Access Control
Enforcement Unit (ACEU) and Access Control Decision
Unit (ACDU). Edge Node (EN) is used as replacement
of kerberos.

IAMU will authenticate the user and sends ACK if
the authentication is successful.

After successful login the user will send a service
access request.

Cloud will then send the request message to
Request subscriber (RS).

RS will unify the request and create a subscription
on the basis of the request received from Cloud
thread.

Then the RS will send this subscription to the
PUB/SUB Broker.

DPU will continuously send index of the data to
the PUB/SUB broker. This event can happen at any
point.

PUB/SUB broker will store all of the data indexes
in its registry.

Immediately after receiving a subscription request
from RB, Pub/Sub Broker will start EM to find the
matched published data for this particular
subscription.

If Pub/Sub Broker finds any subscription match it
will start retrieving data from the DPU.

Retrieved data will be forwarded to the user via the
RS and the Cloud thread.
Integration of WSN with Cloud Computing will provide
benefits to organisations and the research community.
Organisations will benefit by utilising Cloud storage and
an optimised framework for processing, storage and
retrieval of WSN generation data. The proposed WSN
Cloud Computing framework will provide an optimal
approach to user management, access control, storage
and retrieval of distributed data.
REFERENCES
IV. FLOW OF INTERACTION AMONG
FRAMEWORK COMPONENTS
The user attempts to login by sending login
information.
Cloud thread will identify the service type and
generate a corresponding request message.
V. CONCLUSION
It is actually based on Kerberos with slight
modifications. It also implements Diffie-Hellman public
key [20].


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International Journal on Advanced Computer Theory and Engineering (IJACTE)
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