170 research outputs found

    Hybrid Dissemination: Adding Determinism to Probabilistic Multicasting in Large-Scale P2P Systems

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    Abstract. Epidemic protocols have demonstrated remarkable scalability and robustness in disseminating information on internet-scale, dynamic P2P systems. However, popular instances of such protocols suffer from a number of significant drawbacks, such as increased message overhead in push-based systems, or low dissemination speed in pull-based ones. In this paper we study push-based epidemic dissemination algorithms, in terms of hit ratio, communication overhead, dissemination speed, and resilience to failures and node churn. We devise a hybrid push-based dissemination algorithm, combining probabilistic with deterministic properties, which limits message overhead to an order of magnitude lower than that of the purely probabilistic dissemination model, while retaining strong probabilistic guarantees for complete dissemination of messages. Our extensive experimentation shows that our proposed algorithm outperforms that model both in static and dynamic network scenarios, as well as in the face of large-scale catastrophic failures. Moreover, the proposed algorithm distributes the dissemination load uniformly on all participating nodes. Keywords: Epidemic/Gossip protocols, Information Dissemination, Peer-to-Peer

    Autonomous Gossiping: A self-organizing epidemic algorithm for selective information dissemination in mobile ad-hoc networks

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    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 its selectivity. The trade-off of using an infrastructure-less 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. A/G's reliance and hence vulnerability on cooperation of mobile nodes is also much less as compared to other possible schemes using routing information, since it does not expect node philanthropy for forwarding/carrying information, but only cooperation to the extent that nodes already carrying the information pass it on to other suitable ones. Thus autonomous gossiping is expected to be a light-weight infrastructure-less information dissemination service for MANETs, and hence support any-to-many communication (flexible casting) without the need to establish and maintain separate routing information (e.g., multicast trees)

    NEEM: network-friendly epidemic multicast

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    Epidemic, or probabilistic, multicast protocols have emerged as a viable mechanism to circumvent the scalabil- ity problems of reliable multicast protocols. However, most existing epidemic approaches use connectionless transport protocols to exchange messages and rely on the intrinsic robustness of the epidemic dissemination to mask network omissions. Unfortunately, such an approach is not network- friendly, since the epidemic protocol makes no effort to re- duce the load imposed on the network when the system is congested. In this paper, we propose a novel epidemic protocol whose main characteristic is to be network-friendly. This property is achieved by relying on connection-oriented transport connections, such as TCP/IP, to support the com- munication among peers. Since during congestion mes- sages accumulate in the border of the network, the pro- tocol uses an innovative buffer management scheme, that combines different selection techniques to discard messages upon overflow. This technique improves the quality of the information delivered to the application during periods of network congestion. The protocol has been implemented and the benefits of the approach are illustrated using a com- bination of experimental and simulation results

    Resource-Aware Multimedia Content Delivery: A Gambling Approach

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    In this paper, we propose a resource-aware solution to achieving reliable and scalable stream diffusion in a probabilistic model, i.e. where communication links and processes are subject to message losses and crashes, respectively. Our solution is resource-aware in the sense that it limits the memory consumption, by strictly scoping the knowledge each process has about the system, and the bandwidth available to each process, by assigning a fixed quota of messages to each process. We describe our approach as gambling in the sense that it consists in accepting to give up on a few processes sometimes, in the hope of better serving all processes most of the time. That is, our solution deliberately takes the risk not to reach some processes in some executions, in order to reach every process in most executions. The underlying stream diffusion algorithm is based on a tree-construction technique that dynamically distributes the load of forwarding stream packets among processes, based on their respective available bandwidths. Simulations show that this approach pays off when compared to traditional gossiping, when the latter faces identical bandwidth constraint

    On Data Dissemination for Large-Scale Complex Critical Infrastructures

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    Middleware plays a key role for the achievement of the mission of future largescalecomplexcriticalinfrastructures, envisioned as federations of several heterogeneous systems over Internet. However, available approaches for datadissemination result still inadequate, since they are unable to scale and to jointly assure given QoS properties. In addition, the best-effort delivery strategy of Internet and the occurrence of node failures further exacerbate the correct and timely delivery of data, if the middleware is not equipped with means for tolerating such failures. This paper presents a peer-to-peer approach for resilient and scalable datadissemination over large-scalecomplexcriticalinfrastructures. The approach is based on the adoption of epidemic dissemination algorithms between peer groups, combined with the semi-active replication of group leaders to tolerate failures and assure the resilient delivery of data, despite the increasing scale and heterogeneity of the federated system. The effectiveness of the approach is shown by means of extensive simulation experiments, based on Stochastic Activity Networks
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