Iaetsd scalable mobile presence cloud with

Scalable Mobile Presence Cloud with
Communication Security
N.Tejesh1
D.Prasanth2
1
PG Student, M.Tech. Computer Science and Engineering,
Audisankara College of Engineering & Technology, Gudur.A.P, India
Tej578@gmail.com
2
Assistant Professor, Department of CSE,
Audisankara College of Engineering & Technology, Gudur.A.P, India
sumyoan@gmail.com
Abstract- Within Portable existence services is often a
vital portion of a new social networking applications
on account of mobile user’s existence details such as
global setting method place, circle address, along
with online/offline rank are usually constantly
apprise to help user’s online close friends. A mobile
ubiquity companies can be an critical component
impair processing environments, for your reason that
maintains the up-to-date report on existence data
connected with mobile consumer. In the event that
existence improvements happen usually the amount
of announcements written by existence server may
cause scalability issue along with close friend number
look for issue with large-scale mobile existence
companies. For you to triumph over the particular
scalability issue recommended an efficient along with
ascendable server buildings termed existence impair.
It sets up the particular existence server straight into
quorum centered server-server buildings regarding
useful looking. If a mobile consumer ties together a
new circle or perhaps net, existence impair lookups
the particular existence data. Additionally, it
achieves modest regular look for latency from the led
look for protocol along with one-hop caching
approach.
keywords—Social networks, mobile presence services, distributed
presence servers, cloud computing.
I. INTRODUCTION
The Presence [1] entitled applications such as Face-book,
Twitter etc., which is produced by mobile devices and cloud
computing [2] nature due to the prevalence of internet
[3].Way the members are engaged with their buddies on
internet are changed by the social network services [4]. In
order to interact with buddies across great distance
participants can dispense the live event immediately using
their mobile device. Mobile user’s presence information
details will be maintained by mobile presence service [5]. In
cloud computing environment mobile presence service is a
vital component of social network application. Because of the
ubiquity of the Internet, mobile devices and cloud computing
environments can provide presence-enabled applications, i.e.,
social network applications/services, worldwide. Face book,
Twitter Foursquare Google Latitude, buddy cloud and Mobile
Instant Messaging (MIM) are examples of presence-enabled
applications that have grown rapidly in the last decade. Social
network services are changing the ways in which participants
engage with their friends on the Internet. They exploit the
information about the status of participants including their
appearances and activities to interact with their friends.
Moreover, because of the wide availability of mobile devices
(e.g., Smartphone’s) that utilize wireless mobile network
technologies, social network services enable participants to
share live experiences instantly across great distances.
Presence information tells the detail about mobile user’s
availability, activity and machine capacity. Service does
binding of user id to his/her current presence information
details. Each individual mobile user has a buddy list which
includes details of whom he/she wants to interact with in
social network services. When a user does shipment from one
level to other, this change is instinctively transmitted to each
individual on the buddy list. Server cluster technology
increases the search speed and decrease the report time. For
example in social network application mobile user logs in
through his/her mobile device, the mobile presence services
searches and reveals each of them about user’s friend list such
as instant messaging system [6]. Potential of presence cloud
[5] [7] can be examined by using search cost and search
satisfaction without impaired neither of them. When a user
arrives presence server provoke a number of messages is
search cost. Time it takes to examine the arrival of user’s
buddy list is search satisfaction. To help the users who are
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present worldwide, the services enhanced by Google [3] [8]
and Facebook [3] are proliferated among many servers.
Presence server used in large scale social network services to
ameliorate the coherence of mobile presence services. In this
section, examine the existing server architecture for buddy list
in large scale geographical information Centre. Overloading
of buddy search message on presence server leads to
scalability problem. Presence cloud disseminates many users’
information details among many presence servers on the
internet, which is used as a building block of mobile presence
services. For efficient buddy list search there is no single point
collapse, since servers in presence cloud are organized in
quorum [9] based server to server architecture to gain small
search delay using directed buddy search algorithm.
Caching procedure is used to reduce buddy list search. The
potential of three architectures such as presence cloud, mesh
[10] based scheme and distributed hash table [11] are
examined in terms of search response time and friend
notification time. Presence information tells the detail about
mobile user’s availability, activity and machine capacity.
Service does binding of user id to his/her current presence
information details. Each individual mobile user has a buddy
list which includes details of whom he/she wants to interact
with in social network services. When a user does shipment
from one level to other, this change is instinctively transmitted
to each individual on the buddy list. Server cluster technology
increases the search speed and decrease the report time. For
example in social network application mobile user logs in
through his/her mobile device, the mobile presence services
searches and reveals each of them about user’s friend list such
as instant messaging system [6]. Potential of presence cloud
[5] [7] can be examined by using search cost and search
satisfaction without impaired neither of them. When a user
arrives presence server provoke a number of messages is
search cost. Time it takes to examine the arrival of user’s
buddy list is search satisfaction. To help the users who are
present worldwide, the services enhanced by Google [3] [8]
and Facebook [3] are proliferated among many servers.
Presence server used in large scale social network services to
ameliorate the coherence of mobile presence services. In this
section, examine the existing server architecture for buddy list
in large scale geographical information Centre. Overloading
of buddy search message on presence server leads to
scalability problem. Presence cloud disseminates many users’
information details among many presence servers on the
internet, which is used as a building block of mobile presence
services. For efficient buddy list search there is no single point
collapse, since servers in presence cloud are organized in
quorum [9] based server to server architecture to gain small
search delay using directed buddy search algorithm. Caching
procedure is used to reduce buddy list search. The potential of
three architectures such as presence cloud, mesh [10] based
scheme and distributed hash table [11] are examined in terms
of search response time and friend notification time.
II. RELEATED WORK
The rationale behind the design of Presence Cloud is to
distribute the information of millions of users among
thousands of presence server’s on the Internet. To avoid single
point of failure, no single presence server is supposed to
maintain service-wide global information about all users.
Presence Cloud organizes presence servers into a quorum
based server-to-server architecture to facilitate efficient buddy
list searching. It also leverages the server overlay and a
directed buddy search algorithm to achieve small constant
search latency and employs an active caching strategy that
substantially reduces the number of messages generated by
each search for a list of buddies. We analyze the performance
complexity of Presence Cloud and two other architectures, a
Mesh based scheme and a Distributed Hash Table (DHT)-
based scheme. Through simulations, we also compare the
performance of the three approaches in terms servers on the
Internet. The design of Presence Cloud, a scalable server-to-
server architecture that can be used as a building block for
mobile presence services. The rationale behind the design of
Presence Cloud is to distribute the information of millions of
users among thousands of presence servers on the Internet. To
avoid single point of failure, no single presence server is
supposed to maintain service-wide global information about
all users. Presence Cloud organizes presence servers into a
quorum-based server-to-server architecture to facilitate
efficient buddy list searching.
Fig1. Presence Cloud Architecture
Presence servers which are present in presence cloud, where
these presence servers are arranged in quorum based server to
server architecture and also load on servers are balance in
presence cloud sever overlay. All these presence server keeps
caches for buddies in order to increase query speed is one hop
caching approach. Finding small constant search delay results
in directed buddy search by decreasing network traffic using
one hop search strategy. Architecture of presence cloud which
is the proposed work is shown in Figure1, Using 3G or Wi-Fi
services mobile user access the internet and make a data link
to the presence cloud. Using secure hash algorithm mobile
users are intent to one of the presence servers. To transfer
presence information details, the mobile user is authenticated
to the mobile presence services and also opens a TCP link.
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Once path is set up, the mobile user request for the friend list
to the presence server which is present in presence cloud. And
finally the request is responded by the presence cloud after
completing an efficient search of buddy’s presence
information. Analyze the performance complexity of Presence
Cloud and two other architectures, a Mesh based scheme and
a Distributed Hash Table (DHT)-based scheme. Through
simulations, we also compare the performance of the three
approaches in terms of the number of messages generated and
the search satisfaction which we use to denote the search
response time and the buddy notification time. The results
demonstrate that Presence- Cloud achieves major performance
gains in terms of reducing the number of messages without
sacrificing search satisfaction. Thus, Presence Cloud can
support a large-scale social network service distributed among
thousands of servers on the internet. Presence Cloud is among
the pioneering architecture for mobile presence services. To
the best of our knowledge, this is the first work that explicitly
designs a presence server architecture that significantly
outperforms those based distributed hash tables. Presence
Cloud can also be utilized by Internet social network
applications and services that need to replicate or search for
mutable and dynamic data among distributed presence servers.
The contribution is that analyzes the scalability problems of
distributed presence server architectures, and defines a new
problem called the buddy-list search problem. Through our
mathematical formulation, the scalability problem in the
distributed server architectures of mobile presence services is
analyzed. Finally, we analyze the performance complexity of
Presence Cloud and different designs of distributed
architectures, and evaluate them empirically to demonstrate
the advantages of Presence Cloud. Server architectures of
existing presence services, and introduce the buddy-list search
problem in distributed presence Architectures in large-scale
geographically data centers.
III. PRESENCE CLOUD
The past few years has seen a veritable frenzy of research
activity in Internet-scale object searching field, with many
designed protocols and proposed algorithms. Most of the
previous algorithms are used to address the fixed object
searching problem in distributed systems for different
intentions. However, people are nomadic, the mobile presence
information is more mutable and dynamic; anew design of
mobile presence services is needed to address the buddy-list
search problem, especially for the demand of mobile social
network applications. Presence Cloud is used to construct and
maintain distributed server architecture and can be used to
efficiently query the system for buddy list searches. Presence
Cloud consists of three main components that are run across a
set of presence servers. In the design of Presence Cloud, the
ideas of P2P systems and present a particular design for
mobile presence services has been refined. Presence Cloud
server overlay: It organizes presence servers based on the
concept of grid quorum system. So, the server overlay of
Presence Cloud has a balanced load property and a two-hop
diameter node degrees, where n is the number of presence
servers. One-hop caching strategy: It is used to reduce the
number of transmitted messages and accelerate query speed.
All presence servers maintain caches for the buddies offered
by their immediate neighbors Directed buddy search: It is
based on the directed search strategy. Presence Cloud ensures
an one-hop search, it yields a small constant search latency on
average. The primary abstraction exported by our Presence
Cloud issued scalable server architecture for Mobile presence
services, and can be used to efficiently search the desired
buddy lists. We illustrated a simple overview of Presence
Cloud in Fig. 1. In the mobile Internet, a mobile user can
access the Internet and make a data connection to Presence
Cloud via 3G or Wifi services. After the mobile user joins and
authenticates himself/herself to the mobile presence service,
the mobile user is determinately directed to one of Presence
Servers in the Presence Cloud by using the Secure Hash
Algorithm, such as SHA-1. The mobile user opens a TCP
connection to the Presence Server (PSnode) for control
message transmission, particularly for the presence
information. After the control channel is
established, the mobile user sends a request to the connected
PSnode for his/her buddy list searching. Our Presence
Cloudshall do an efficient searching operation and return the
presence information of the desired buddies to the mobile
user.
IV. EVOLUTION
A cost analysis of the communication cost of Presence Cloud
in terms of the number of messages required to search the
buddy information of a mobile user. Note that how to reduce
the number of inter server communication messages is the
most important metric in mobile presence service issues. The
buddy-list search problem can be solved by a brute-force
search algorithm, which simply searches all the PS nodes in
the mobile presence service. In a simple mesh-based design,
the algorithm replicates all the presence information at each
PS node; hence its search cost, denote by QMesh, is only one
message. On the other hand, the system needs n _ 1 messages
to replicate a user’s presence information to all PS nodes,
where n is the number of PS nodes. The communication cost
of searching buddies and replicating presence information can
be formulated as Mcost = QMesh +RMesh, where RMesh is
the communication cost of replicating presence information to
all PS nodes. Accordingly, we have Mcost = O(n). In the
analysis of Presence Cloud, we assume that the mobile users
are distributed equally among all the PS nodes, which is the
worst case of the performance of Presence- Cloud. Here, the
search cost of Presence Cloud is denoted as Qp, which is
messages for both searching buddy lists and replicating
presence information. Because search message and replica
message can be combined into one single message, the
communication cost of replicating, Rp (0). It is straight
forward to know that the communication cost of searching
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buddies and replicating presence information in Presence
Cloud is Pcost .However, in Presence Cloud, a PS node not
only searches a buddy list and replicates presence information,
but also notifies users in the buddy list about the new presence
event. Let b be the maximum number of buddies of a mobile
user. Thus, the worst case is when none of the buddies are
registered with the PS nodes reached by the search messages
and each user on the buddy list is located on different PS
nodes.
V. CONCLUSION
In this paper In large scale social network services mobile
presence services is supported by the scalable server
architecture called as presence cloud. A scalable server
architecture that supports mobile presence services in large-
scale social network services. Presence Cloud achieves low
search latency and enhances the performance of mobile
presence services. Total number of buddy search messages
increases substantially with the user arrival rate and the
number of presence servers. The growth of social network
applications and mobile device computing capacity to explore
the user satisfaction both on mobile presence services or
mobile devices. Presence Cloud could certificate the presence
server every time when the presence server joins to Presence
Cloud. The results of that Presence Cloud achieve
performance gains in the search cost without compromising
search satisfaction.
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Iaetsd scalable mobile presence cloud with

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