presence cloud

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Department of Computer Science & EngineeringShri Sant Gajanan Maharaj College of Engineering

Shegaon (444203)

“Presence Cloud based solution for on demand data in wireless computing devices”

Guided by :Prof. N. M. Kandoi

Submitted by: Ms. Monali D. Akhare

27/10/2015“Presence Cloud based solution for on demand data in wireless computing devices”

Seminar on


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OVERVIEW

27/10/2015

Abstract

Existing System Analysis of Problem

Proposed System Introduction -Presence Cloud server overlay

-One hop caching -Directed buddy search

Hardware System Configuration Software System Configuration Applications Conclusion & References


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• Social network services are growing and many people are sharing digital resources

in order to facilitate, enhance or improve collaborative work.

• It is essential because it maintains each mobile user’s presence information, such as current status (online/offline), GPS location and network address.

• If presence updates occur frequently, enormous number of message distributed by servers may lead to scalability problem.

ABSTRACT

Cloud

Server-side Virtual World Compute Power


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• Most of the previous algorithms are used to address fixed object searching problem in distributed system for different intentions.

• To address this problem , Chi-Jen et la, [1]in 2013 propose an efficient and scalable server architecture which is called Presence Cloud.

• The performance can be analysed in terms of search cost and search satisfaction level. Implementation Flowchart


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• 3 popular commercial IM systems are :

AIM

Microsoft MSN

Yahoo! Messenger.

EXISTING SYSTEM


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• They leverage some form of Centralized clusters which are used to provide presence services.

• Storing the presence is one of the most messaging traffic in these instant messaging system.

Overview of IM traffic


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• All these IM services use central server architecture leads to scalability problem at server side.

• So to address the problem, Presence Cloud organizes presence servers into a quorum-based server-to- server architecture for efficient presence searching.


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• Mobile ubiquity services is important element of cloud computing environments.

• If presence updates occur often number of messages distributed by presence server lead to scalability problem & buddy list search problem in large-scale mobile presence services.

• To overcome scalability problem proposed an efficient and ascendable server architecture called Presence Cloud.

• When a mobile user joins a network or internet, presence cloud searches presence information achieves small constant search latency by the Directed search algorithm and One-hop caching strategy.

ANALYSIS OF PROBLEM


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• Aim of proposed system is to design an architecture of disseminate server for coherence request to system for buddy list search.

• In this project work a scalable server architecture which provides services to ‘n’ number of users is presented.

• Presenting a precise design by improving thought of peer to peer system while designing presence cloud.

• P2P reduces the maintenance costs and failures in server based deployment.

• Presence Cloud is based on grid quorum based system the clients are organized in DHT & size of Presence server node is O√m

PROPOSED SYSTEM INTRODUCTION


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• There are 3 elements in presence cloud which run across presence servers such as presence cloud server overlay, one hop caching approach, and directed buddy search .

Overview of Presence Cloud


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Presence cloud server overlay

• This construction algorithm organizes ps nodes in to server – to – server overlay.

• It provides a good low diameter property.• It ensure that a ps node needs only two hops.

Presence Cloud Server Overlay


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One hop caching

• To improve efficiency, presence cloud requires a caching strategy.

• In Presence Cloud, each PS node maintains a user list of presence information of the attached users.

• The cache is updated when neighbors establishes a connection to it and it updated periodically with it neighbors.

• Therefore, when any PS node receives a query, it can respond not only with its own user list but also matches in the user lists offered by all of its neighbors.


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Directed buddy search

• Minimizing the searching response time is important in presence services.

• By organizing PS nodes into server-to-server overlay network, we can efficiently respond to the queries and can reduce network traffic.

• By capitalizing one–hop caching, that it maintains user list of neighbors, we can improve response time by increasing the chances of finding buddies.

• Clearly, this mechanism reduces both network traffic and response time.

Buddy list searching in Presence Cloud.


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• Presence servers present in presence cloud, 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


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• Objective of this paper is to propose an on demand QoS routing algorithm.

• Since the requirements for various applications may vary time to time, the approach for QoS routing may not be proactive.

• The proposed approach has two phases namely:-route discovery phase -route maintenance phase

• This is first work that explicitly design a presence server architecture that significantly outperforms those based distributed hash table.


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Performance Metrics

• Performance Metrics Within the context of the model, we measure the performance of server architectures using the following three metrics:

-Total searching messages

-Average searching messages per-arrived user

-Average searching latency


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Number Description Alternatives (If available)

1 PC with 100 GB hard-disk and 2 GB RAM

Not-Applicable

2 PCs in Network

HARDWARE System Configuration


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Number Description Alternatives(If available)

1 Windows 7/8/XP/linux with MS-office

Not Applicable

2 Java(1.6), Java 1.5,

3 Eclipse 3.3 Neat Bean 7.4

4 Android Mobile

5 Tomcat server 7

6 Mysql Database Server 5.5

SOFTWARE System Configuration


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APPLICATIONS

• Server overlay and a directed buddy search algorithm are used to achieve small constant search latency.

• The design of scalable server-to-server architecture 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.


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In this paper, we have presented Presence Cloud, a scalable server

architecture that supports mobile presence services in large-scale social network.

We have shown that Presence Cloud achieves low search latency and enhances the performance of mobile presence services.

In addition, we discussed scalability problem in server and introduced buddy-list search problem.

Through a simple mathematical model, we show that total number of buddy search messages increases substantially with user arrival rate and number of presence servers.

The results of simulations demonstrate that Presence Cloud achieves major performance gains in terms of the search cost and search satisfaction.

CONCLUSION


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REFERENCES

[1] Chi-Jen Wu, Jan-Ming Ho, Member, IEEE, and Ming-Syan Chen, Fellow, IEEE on “A Scalable Server Architecture for Mobile Presence Services in Social Network Applications”, 2013.

[2] R.B. Jennings, E.M. Nahum, D.P. Olshefski, D. Saha, Z.-Y.Shae, and C. Waters, “A Study of Internet Instant Messaging and Chat Protocols,” IEEE Network, vol. 20, no. 6, pp. 16-21, July/Aug.2006.

[3] Z. Xiao, L. Guo, and J. Tracey, “Understanding Instant Messaging Traffic Characteristics,” Proc. IEEE 27th Int’l Conf. Distributed Computing Systems (ICDCS), 2007.

[4] C. Chi, R. Hao, D. Wang, and Z.-Z. Cao, “IMS Presence Server:Traffic Analysis and Performance Modelling,” Proc. IEEE Int’lConf. Network Protocols (ICNP), 2008.

[5] Instant Messaging and Presence Protocol IETF Working Group,http://www.ietf.org/html.charters/impp-charter.html, 2014.

[6] Extensible Messaging and Presence Protocol IETF Working Group,http://www.ietf.org/html.charters/xmpp-charter.html,2012.

[7] http://www.jabber.org, 2012.


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[8] A. Houri, S. Parameswar, E. Aoki, V. Singh, and H. Schulzrinne, “Scaling Requirements for Presence in SIP/SIMPLE,” IETF Internet draft, 2009.

[9] S.A. Baset, G. Gupta, and H. Schulzrinne, “OpenVoIP: An Open Peer-to-Peer VoIP and IM System,” Proc. ACM SIGCOMM, 2008.

[10] Open Mobile Alliance, “OMA Instant Messaging and PresenceService,” 2005[11] W.-E. Chen, Y.-B.Lin, and R.-H. Liou, “A Weakly ConsistentScheme for IMS Presence

Service,” IEEE Trans. Wireless Comm.,vol. 8, no. 7, pp. 3815-3821, July 2009.[12] N. Banerjee, A. Acharya, and S.K. Das, “Seamless SIP-BasedMobility for Multimedia

Applications,” IEEE Network, vol. 20,[13] Kundan Singh and Henning Schulzrinne Department of Computer Science, Columbia

University {kns10,hgs}@cs.columbia.edu, “SIPPEER : A session iniiation protocol (SIP)-baed peer-to-peer internet telephony cllient adaptor” .

[14] Michael Piatek, Tomas Isdal, Arvind Krishnamurthy , and Thomas Anderson “One hop Reputations for Peer to Peer FileSharing Workloads”.

[15] Brent Hecht, Jaime Teevan , Meredith Ringel Morris, and Dan Liebling, “SearchBuddies: Bringing Search Engines into theConversation”, 2012


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Thank You !!!