The churn rate of a peer-to-peer system places direct limitations on the rate at which messages can be effectively communicated to a group of peers. These limitations are independent of the topology and message transmission latency. In this paper we consider a peer-to-peer network, based on the Engset model, where peers arrive and depart independently at random. We show how the arrival and departure rates directly limit the capacity for message streams to be broadcast to all other peers, by deriving mean field models that accurately describe the system behavior. Our models cover the unit and more general k buffer cases, i.e. where a peer can buffer at most k messages at any one time, and we give results for both single and multi-source message streams. We define coverage rate as peer-messages per unit time, i.e. the rate at which a number of peers receive messages, and show that the coverage rate is limited by the churn rate and buffer size. Our theory introduces an Instantaneous Message Exchange (IME) model and provides a template for further analysis of more complicated systems. Using the IME model, and assuming random processes, we have obtained very accurate equations of the system dynamics in a variety of interesting cases, that allow us to tune a peer-to-peer system. It remains to be seen if we can maintain this accuracy for general processes and when applying a non-instantaneous model.
Other closely related work such as in @cite_4 looks at the rate of file transmission in a file sharing system that is based on epidemics. The use of epidemics for large scale communication is also reviewed in @cite_0 . The probabilistic multicast technique in @cite_2 attempts to increase the probability that peers receive messages for which they are interested and to decrease the probability that peers receive messages for which they are not interested. Hence it introduces a notion of membership which is not too different to being online offline. Autonomous Gossiping presented in @cite_5 provides further examples of using epidemics for selective information dissemination.
@cite_0 @cite_5 @cite_4 @cite_2
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Building very large computing systems is extremely challenging, given the lack of robust scalable communication technologies. This threatens a new generation of mission-critical but very large computing systems. Fortunately, a new generation of "gossip-based" or epidemic communication primitives can overcome a number of these scalability problems, offering robustness and reliability even in the most demanding settings. Epidemic protocols emulate the spread of an infection in a crowded population, and are both reliable and stable under forms of stress that will disable most traditional protocols. This paper describes some of the common problems that arise in scalable group communication systems and how epidemic techniques have been used to successfully address these problems. We introduce autonomous gossiping (A G), a new genre epidemic algorithm for selective dissemination of information in contrast to previous usage of epidemic algorithms which flood the whole network. A G is a paradigm which suits well in a mobile ad-hoc networking (MANET) environment because it does not require any infrastructure or middleware like multicast tree and (un)subscription maintenance for publish subscribe, but uses ecological and economic principles in a self-organizing manner in order to achieve any arbitrary selectivity (flexible casting). The trade-off of using a stateless self-organizing mechanism like A G is that it does not guarantee completeness deterministically as is one of the original objectives of alternate selective dissemination schemes like publish subscribe. We argue that such incompleteness is not a problem in many non-critical real-life civilian application scenarios and realistic node mobility patterns, where the overhead of infrastructure maintenance may outweigh the benefits of completeness, more over, at present there exists no mechanism to realize publish subscribe or other paradigms for selective dissemination in MANET environments. Peer-to-peer applications have become highly popular in today's pervasive environments due to the spread of different file sharing platforms. In such a multiclient environment, if users have mobility characteristics, asymmetry in communication causes a degradation of reliability. This work proposes an approach based on the advantages of epidemic selective resource placement through mobile Infostations. Epidemic placement policy combines the strengths of both proactive multicast group establishment and hybrid Infostation concept. With epidemic selective placement we face the flooding problem locally (in geographic region landscape) and enable end to end reliability by forwarding requested packets to epidemically 'selected' mobile users in the network on a recursive basis. The selection of users is performed based on their remaining capacity, weakness of their signal and other explained mobility limitations. Examination through simulation is performed for the response and reliability offered by epidemic placement policy which reveals the robustness and reliability in file sharing among mobile peers.