IRJET- Virtual Network Recognition and Optimization in SDN-Enabled Cloud Environment

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 404
VIRTUAL NETWORK RECOGNITION AND OPTIMIZATION IN SDN-ENABLED CLOUD
ENVIRONMENT
VIVEKANANTHAN S
B.E. Department of CSE, Sri Ramakrishna Engineering College, Coimbatore,
Tamil Nadu, India
YOGESH D
Tamil Nadu, India
NISHANTH K
Tamil Nadu, India
Ms.PAVITHRA
Assistant Professor (Sr.G), Department of CSE, Sri Ramakrishna Engineering College, Coimbatore,
Tamil Nadu, India
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Abstract - In the past decade, mobile devices
and applications have experienced an explosive growth,
and users are expecting higher data rates and better
quality services every year. In this paper, we propose
several ideas to increase the functionality and capacity of
wireless networks using software-defined
networking(SDN) and cloud computing technologies.
Connections between users and services in mobile
networks typically have to pass through a required set of
middle boxes. The complex outing is one of the major
impetus for the SDN paradigm ,which enables flexible
policy-aware routing in the next generation mobile
networks. In addition, the high costs of middleboxes and
limited capabilities of mobile devices call for revolutionary
virtualization technologies enabled by cloud computing.
Based on these, we consider an online routing problem for
mobile networks with SDN and cloud computing. In this
problem, connection requests are given one at a time (as
in a real mobile system),and the objective is to steer traffic
flows to maximize the total amount of traffic accepted over
time, subject to capacity, budget,policy, and quality of
service constraints. A fast log -competitive approximation
algorithm is developed based on time-dependentduals.
Key Words: CLOUD COMPUTING, ENCRYPTED
DOCUMENTS,CONJUCTIVE KEYWORDS
1. INTRODUCTION
MOBILE data is continuing to grow exponentially,
and is taking up a larger portion of total Internet traffic in
recent years. As various portable mobile devices like
smartphones, tablets, and netbooks become more
prevalent, people are using mobile Internet more
frequently and have shifted a large portion of their online
activities, including web surfing, online banking, video
streaming, social networking, and online gaming, from
traditional cable Internet services to their mobile
counterparts.
Such an exponential growth of mobile data, as
well as the vast variety of online activities, imposes a
heavy burden on mobile network service providers. Not
only do these carriers need to upgrade their network
capacities frequently, but they also need to provide
differentiated services and meet the varied QoS
requirements imposed by different mobile Internet
applications.
At present most NE are statically deployed in the
network, and routing paths among these nodes are often
pre-determined. According to 3GPP specifications, mobile
data traffic in current 4G LTE networks is routed in a hop-
by-hop manner, either according to fixed routing tables or
with limited load balancing capabilities. More specifically,
a UE selects an eNodeB according to channel
measurements, the eNodeB selects a Mobility Management
Entity (MME) according to tracking area identification
(TAI), and the MME selects a PGW according to access
point name (APN) and an SGW according to TAI. The PGW
is solely responsible for QoS. It maps traffic flows into
different QoS classes, which are then translated into
DiffServ priorities enforced in a per-hop manner. This
strategy cannot fully utilize the networks to meet
customers’ needs due to its poor flexibilitywhen facing
asymmetric traffic fluctuations, and lacks finegrained
optimization of network resources and end-to-end traffic
steering.
2. RELATED WORK
Network deployments handle changing
application, workload, and policy requirements via the
deployment of specialized network appliances or
“middleboxes”. Today, however, middlebox platforms are
expensive and closed systems, with little or no hooks for

extensibility. Furthermore, they are acquired from
independent vendors and deployed as standalone devices
with little cohesiveness in how the ensemble of
middleboxes is managed. As network requirements
continue to grow in both scale and variety, this bottom-up
approach puts middlebox deployments on a trajectory of
growing device sprawl with corresponding escalation in
capital and management costs.
The concept of Future Networks is based on the
premise that current infrastructures require enhanced
control, service customization, self-organization and
self-management capabilities to meet the new needs in a
connected society, especially of mobile users. In order to
provide a high-performance mobile system, three main
fields must be improved: radio, network, and operation
and management. In particular, operation and
management capabilities are intended to enable
business agility and operational sustainability, where
the addition of new services does not imply an excessive
increase in capital or operational expenditures. In this
context, a set of key-enabled technologies have emerged
in order to aid in this field. Concepts such as Software
Defined Network (SDN), Network Function
Virtualization (NFV) and Self-Organized Networks (SON)
are pushing traditional systems towards the next 5G
network generation.This paper presents an overview of
the current status of these promising technologies and
ongoing works to fulfill the operational and
management requirements of mobile infrastructures.
This work also details the use cases and the challenges,
taking into account not only SDN, NFV, cloud computing
and SON but also other paradigms
Background. To ensure the required quality of
experience and optimal use of network operator's
resources in the current conditions telecommunication
operator can deploy services using the concept of Network
Functions Virtualization (NFV), that has fundamental
differences from traditional dedicated hardware. To
achieve the expected benefits of NFV, physical resources
must be used effectively. This requires effective algorithms
to determine onto which physical resources network
functions are allocated. Objective. The aim of the paper is
to improve the efficiency of mobile network through
optimal resource allocation in hybrid data center
environment. Methods. Analysis of all known publications
devoted to virtualization of network functions of mobile
network has shown the modeling approach to resource
allocation and also has shown the absence of decisions on
important issues of this process (performance of
functional blocks, heterogeneous environment). Results.
An analytical approach to model and investigate the
resource allocation of network functions on a
telecommunication operator’s network is proposed.
Conclusions. To model the resource allocation for
virtualized network functions a technique of virtual
network embedding can be used, while changing the
constraints in which you can get the results for a variety of
deployment scenarios. In such way, adding a number of
constraints to the classical formulation of the problem, we
can take into account the performance of the network
functions and heterogeneity (hybridity) of the deployment
environment.
3. OVERVIEW OF PROPOSED SYSTEM
In proposed system, proposed algorithms only
work for the single constraint scenario, while only a few
can be extended to support multiple constraints as well.
For example, in addition to meeting end-to-end latency
requirements, sometimes we may want to ensure that the
selectedhosts are close enough to the users as well, so as
to improve the user experience during cellular handover
or computation handoff.Primal-dual algorithm, and then
informs the home network of the competitor charge and
the actual network latency.Per-hop shortest-path routing.
This is the baseline algorithm in which all links are given a
uniform unit length, and the scheduler iteratively finds the
closest (in terms of the number of links) next-hop NE in a
hop-by-hop manner and connects these segments up to
construct an end-to-end path.Both network latencies and
path length are considered, and our objective is to
minimize the end-to-end path length under network
latency constraints.
LIST OF MODULES
 Authentication
 Network Creation
 File Sender
 SDN Controller
 Server
a) Authentication
In computer security, logging in (or
logging on or signing in or signing on) is the
process by which an individual gains access to a
computer system by identifying and
authenticating themselves. The user credentials
are typically some form of "username" and a
matching "password", and these credentials
themselves are sometimes referred to as a login,
(or a logon or a sign-in or a sign-on).In practice,
modern secure systems also often require a
second factor for extra security.

b) Network Creation
The Network creation process will be created
by the cloud service provider.In Data
communication, a physical network node may
either be a data terminal equipment (DTE) such
as a router, a Gateway, Datacenter, Firewall or a
server. Another important one is to these network
want to connect with the SDN controller. Each
SDN controller has the separate specification like
RAM, ROM, OS, etc.
c) File Sender
If any user wants to store their files in the
cloud for that we want to pass our data through the
network. So first we want to select our file which one
we want to upload. User sends this data to the server
to store their file, in between the file will be first
received by the router. The router will be received
their files and all the details and then it will be resend
to the SDN controller.
d) SDN Controller
The SDN-Controller will receive the files from
the router.SDN controller work is to split the files into
packets according to their file size. The splitted
packets only will be send to the router because the file
files will be easily transferred to the server. At the
same time network congestion and traffic will be
reduce.
e) Server
Server receives the splitted packets by the
router. After receiving the server the files will be
merge all the packets and store into a single file only.
If the user want to view the files, the server will be
send the file. The server received the request from the
user then only they can send their files to the router.
After that the SDN controller receive the file from the
router then only they split their files again send to the
router and then only file will be received by the user.
4. SOFTWARE SPECIFICATION
J2ME
Sun Microsystems defines J2ME as "a highly optimized
Java run-time environment targeting a wide range of
consumer products, including pagers, cellular phones,
screen-phones, digital set-top boxes and car navigation
systems." Announced in June 1999 at the Java One
Developer Conference, J2ME brings the cross-platform
functionality of the Java language to smaller devices,
allowing mobile wireless devices to share applications.
With J2ME, Sun has adapted the Java platform for
consumer products that incorporate or are based on small
computing devices.
General J2ME architecture
J2ME uses configurations and profiles to
customize the Java Runtime Environment (JRE). As a
complete JRE, J2ME is comprised of a configuration, which
determines the JVM used, and a profile, which defines the
application by adding domain-specific classes. The
configuration defines the basic run-time environment as a
set of core classes and a specific JVM that run on specific
types of devices. We'll discuss configurations in detail in
the profile defines the application; specifically, it adds
domain-specific classes to the J2ME configuration to
define certain uses for devices. We'll cover profiles in
depth in the following graphic depicts the relationship
between the different virtual machines, configurations,
and profiles. It also draws a parallel with the J2SE API and
its Java virtual machine. While the J2SE virtual machine is
generally referred to as a JVM, the J2ME virtual machines,
KVM and CVM, are subsets of JVM. Both KVM and CVM can
be thought of as a kind of Java virtual machine -- it's just
that they are shrunken versions of the J2SE JVM and are
specific to J2ME.
5. CONCLUSION
The infrastructure inefficiencies
androuting inflexibilities in currentmobile networks, and
proposean SDN-based architecture with cloud computing
to addressthe potential bottlenecks and challenges of next
generationmobile networking. In order to enable policy-
aware routingand provide QoS guarantee, we formulate a
multi-commodityflow problem with side constraints, and
follow the primaldualapproach to obtain a log-competitive
solutionusing a fastonline approximation algorithm.
Extensive simulations havebeen performed to investigate
the impact of various parameterson the network
performances. These results also show that ouralgorithm

significantly outperforms prevalent heuristics dueto end-
to-end optimization, congestion/budget awareness,
andprimal-dual approximation.
Despite years of work on SDN, the
technology is still in its infancy. In this section, we
highlight several active areas of investigation, including
creating better SDN infrastructure, applying SDN in new
settings, and expanding the scope of SDN beyond network
switches.
6. REFERENCES
[1] V. Sekaret al., “Design and implementation of a
consolidated middlebox architecture,” in Proc. NSDI, 2012,
pp. 323–336..
[2] P. Demestichaset al., “5G on the horizon: Key
challenges for the radioaccess network,” IEEE Veh.
Technol. Mag., vol. 8, no. 3, pp. 47–53, Sep. 2013.
[3] A. Bastaet al., “Applying NFV and SDN to LTE mobile
core gateways,the functions placement problem,” in Proc.
ACM Workshop All Things Cellular, 2014, pp. 33–38.
[4] M. Satyanarayanan, P. Bahl, R. Caceres, and N. Davies,
“The case for VM-based cloudlets in mobile computing,”
IEEE Pervasive Comput., vol. 8, no. 4, pp. 14–23, Oct./Dec.
2009.
[5] WilliamGrosso, “JAVA”, O'Reilly Media, Inc.; 1 edition,
2001
[6] John Zukowski, “Definitive Guide to Swing for Java
2”,1999
[7] Roger S.Pressman, “SOFTWARE ENGINEERING –A
PRACTIONERS APPROACH “, Tata McGraw Hill Publishing
Company, 1997.
[8] JAVA 2 Platform, standard Edition, V 1.3.1 API
Specification
[9] Java RMI: Remote method Invocation(Paperback) Troy
Bryan Downing
[10] Mark Grand and Jonathan Knudsen, “Java
Fundamental Classes Reference”, Tata McGrawHill
Publishing Company Limited, 1st Edition, May 1997.

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