Server Architectures of Existing Presence Services

Server Architectures of Existing battlefront aidIn this section, we describe the system model, and the seem hassle. Formally, we assume the geographically coverd posture bonifaces to take a server to-server track interlock, G = (V,E), where V is the plenty of the Presence Server (PS) nodes, and E is a collection of ordered pairs of V . Each PS node ni V represents a Presence Server and an element of E is a pair (ni,nj) E with ni,nj V . Beca utilization the pair is ordered, (nj,ni) E is not equivalent to (ni,nj) E. So, the moulding (ni,nj) is called an outgoing edge of ni, and an incoming edge of nj. The server overlay enables its PS nodes to communicate with virtuosoness an separate by forwarding messages through other PS nodes in the server overlay. Also, we denote a set of the busy enjoymentrs in a battlefront service as U = u1,,ui,,um, where 1 i m and m is the number of peregrine users. A energetic user ui connects with one PS node for essay other users nominal head tuition, and to notify the other winding users of his/her arrival. Moreover, we define a sidekick count as following. Buddy list, Bi = b1,b2,,bk of user ui U, is defined as a subset of U, where 0 i Bj implies uj Bi.For example, given a diligent user up is in the blood brother list of a mobile user uq, the mobile user uq likewise appear in the crony list of the mobile user up. Note that to simplify the analysis of the Buddy-List Search conundrum, we assume that chum relation is a symmetric. However, in the blueprint of Presence Cloud, the relation of buddies mint be uni afterwardsal because the attend operationof PresenceCloud can retrieve the aim of a mobile user by given the ID of the mobile user.Problem Statement Search ProblemWhen a mobile user ui changes his/her forepart status, the charge service tryes nominal head information of mobile users in buddy list Bi of ai and notifies each of them of the heading of ai and in addition notifies ai o f these online buddies. The Search Problem is then defined as conniving a server architecture of front service such that the cost of searching and notification in communication and storage atomic number 18 taked.1.2 pauperizationBecause of the increasing of the meshing, mobile devices and calumniate computing environments can leave behind front line-enabled applications, i.e., fond net applications/ function, worldwide. Facebook , Twitter, Foursquare, Google Latitude , buddycloud and Mobile Instant pass on (MIM) , are examples of presence-enabled applications that render grown rapidly in the last decade. Social network run are changing the ways in which They exploit the information most the status of participants including their appearances and activities to interact with their friends. The huge availability of mobile devices (e.g., Smartphones) that utilize piano tuner mobile network technologies, tender network go enable participants to fate presence experience s minutely across great distances. For example, Facebook receives more than 75 meg shared items every month and Twitter receives more than 60 one thousand million tweets each day. In the future, mobile devices will become more normal than today, sensing and media capture devices. Hence, we believe it is useful and fond network services will be the next generation of mobile Internet applications.A mobile presence service is an important component of well-disposed network services in cloud computing environments. The key function of a mobile presence service is to maintain an present list of presence information of all mobile users. The presence information includes details about(predicate) a mobile clients or user location, availability, activity, device capability, and their choices. The service must also bind the this clients ID to his/her current presence information, as well as retrieve and subscribe to changes in the presence information of the users friends. In social n etwork services, each mobile user has a friend list, typically called a buddy list, which contains the contact information of other users that he/she wants to communicate with. The mobile users status is cognize automatically to each person on the buddy list whenever he/she moves from one location to the other. For example, when a mobile user logs into a social network application, such as an Instant Messaging system, through his/her mobile device, the mobile presence service searches for and notifies everyone on the users buddy list. To maximize a mobile presence services search speed and minimize the notification time, most presence services use server cluster engine room. Currently, more than 400 million people use social network services on the Internet. Given the growth of social network applications and mobile network capacity, it is expected that the number of mobile presence service users will increase substantially in the near future. Thus, a ascendable mobile presence s ervice is deemed essential for future Internet applications.In the last decade, many Internet services have been deployed in distributed paradigms as well as cloud computing applications. For example, the services essential by Google and Facebook are spread among as many distributed servers as assertable to throw the huge number of users worldwide. Thus, we explore the relationship between distributed presence servers and server network topologies on the Internet, and propose an streamlined and scalable server-to-server overlay architecture called PresenceCloud to improve the scalability of mobile presence services for great(p)-scale social network services.First, we examine the server architectures of breathing presence services, and introduce the search problem in distributed presence architectures in large-scale geographically information centers. The search problem is a scalability problem that occurs when a distributed presence service is overloaded with buddy search mes sages.Then, we discuss the architecture of PresenceCloud, a scalable server-to-server architecture that can be used as a build block for mobile presence services. The rationale behind the architecture of PresenceCloud 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 all the information about all users. PresenceCloud arranges presence servers into a quorum-based server-to-server architecture to facilitate efficient searching. It also leverages the server overlay and a directed buddy search algorithm to achieve small constant search latency and employs an ready caching strategy that substantially reduces the number of messages generated by each search for a list of searching process. We analyze the performance of PresenceCloud and two other architectures, a Mesh-based scheme and a Distributed Hash Table based scheme. Through simulations, we al so 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 PresenceCloud achieves major performance gains in terms of trim down the number of messages to reduce network craft without sacrificing search satisfaction. Thus, PresenceCloud can project a large-scale applications distributed among thousands of servers on the Internet.The contribution of this paper is threefold. First, PresenceCloud is among the imporatanta architecture for mobile presence services. To the best of our knowledge, this is the first work that shown the architecture of presence cloud that significantly best than those based distributed hash tables. PresenceCloud can also be utilized by Internet social network applications and services that conduct to replicate or search for mutable and dynamic data among distributed presence servers. The second contribution is that we analyze the scalability problems of distributed presenceserver architectures, and define a new problem called the buddy-list search problem. Through our mathematical formula, the scalability problem in the distributed server architectures of mobile presence services is analyzed. Finally, we analyze the performance complexity of Presence- Cloud and disparate designs of distributed architectures, and evaluate to prove the applications of PresenceCloud. 1.3 Existing SystemIn this section, we describe the former research on presence services, and look into the presence service of existing systems. Well known commercial Instant Messaging systems has many form of centralized clusters to provide presence services. Jennings III et al. presented a taxonomy of diverse features and functions back up by the three most popular Instant Messaging systems and rube Messenger. The authors also provided an overview of the system architectures and observed that the systems use client-server-based architectures. Skype, a popular part over Internet Protocol application, utilizes the Global Index (GI) technology to provide a presence service for clients and people. Global Index is a multi-tiered network architecture where each node maintains full knowledge of all for sale clients connected to it. Since Skype is not an open protocol, it is difficult to determine how GI technology is used for presence services. Moreover, Xiao et al. analyzed the commerce of MSN and AIM system. They found that the presence information is one of most network traffic in instant messaging systems. In, authors shown that the largest message traffic in existing presence services is buddy NOTIFY messages.1.4 Limitations of Existing SystemThis system allows makes congestion in the network.It is not applicable for large scale network.It increases the search latency.1.5 Proposed SystemRecently, on that point is an increase amount of interest in how to design a peer- to-peer session Initiation Protocol. P2P drink has been developed to remove the the disadvantages of centralized server, reduce costs, and prevent loses overdue to failures in server-based SIP deployment. To maintain presence information, P2PSIP clients are organized in a Distributed Hash Tables system, rather than in a centralized server. However, the presence service architectures of rabbit on and P2PSIP are distributed,the buddy-list search problem we defined later also could relate such distributed systems.It is noted that few papers in discuss about the scalability issues of the distributed presence server architecture. Saint Andre observed the traffic generated as a result of presence information between users of inter-domains that support the XMPP. Houri et al. Show that the amount of presence traffic in round-eyed can be extremely high, and they analyze the effect of a large presence system on the memory CPU loading. Those works in study related problems and developing an initial set of guidelines for optimizing inter-domain presence traffic and present a DHT-based presence server architecture.Recently, presence services are also developed in the mobile services. For example, 3GPP has defined the integration of presence service into its specification in UMTS. It is based on SIP protocol, and uses transparent to manage presence information. Recently, some mobile devices also support mobile presence services. For example, the Instant Messaging and Presence Services (IMPS) was developed by the Wireless Village consortium and was united into Open Mobile shackle (OMA) IMPS in 2005. In, Chen et al. proposed a weakly consistent scheme to reduce the number of updating messages in mobile presence services of IP Multimedia Subsystem (IMS). However, it also suffers scalability problem since it uses a central SIP server to perform presence update of mobile users. In, authors presented the server scalability and distributed management issues in IMS-based pre sence service.CHAPTER 2 LITERATURE SURVEYChapter 2Literature abide by2.1 IntroductionIn this section, we describe previous researches on presence services, and survey the presence service of existing systems2.2 Related Paper Discussions2.2.1 human action A study of internet instant messaging and chat protocols family 2006 condition R. B. Jennings, E. M. Nahum, D. P. Olshefski, D. Saha, Z.-Y. Shae, interpretationWell known commercial Instant Messaging systems has some form of centralized clusters to maintain presence services. Jennings III presented a taxonomy of different features and functions supported by the three most popular Instant Messaging systems, AIM, Microsoft MSN and Yahoo Messenger. The authors also provided a description of the system architectures and analized that the systems use client-server-based architectures.2.2.2 statute title Understanding instant messaging traffic characteristics Year 2007Author Z. Xiao, L. Guo, and J. TraceyDescriptionXiao analyzed the t raffic of MSN and AIM system. They observed and got that the presence information is one of most messaging traffic in instant messaging systems2.2.3 Title Ims presence server Traffic analysis and performance modellingYear 2008Author C. Chi, R. Hao, D. Wang, and Z.-Z. Cao,DescriptionIn this, authors shown that the huge message traffic in existing presence services is searching the locations ,buddies etc.2.2.4 Title Peer-to-peer internet telephony using sipYear2009Author K. Singh and H. SchulzrinneDescription instanter a days, there is an increase amount of interest in how to design a peer-to-peer Session Initiation Protocol . Peer to Peer SIP has been developed to remove the centralized server, reduce maintenance costs, and prevent disadvantages in server-based SIP deployment. To maintain presence information, P2PSIP clients are arranged in a DHT system, rather than in a centralized server. However, the presence service architectures of Jabber and P2PSIP are distributed, the search p roblem we defined later also could affect such distributed systems.