Decentralising a service-oriented architecture

Šácha, Jan; Biskupski, Bartosz; Dahlem, Dominik; Cunningham, Robert E.; Meier, René; Dowling, Jim; Haahr, Mads

doi:10.1007/s12083-009-0062-6

Cited by 9 publications

(3 citation statements)

References 45 publications

(68 reference statements)

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“…The idea of locating higher capacity peers closer to the source than lower capacity peers is similar to the idea of gradient overlays, recently presented in [19], [20]. There are several main differences between these studies and ours.…”

Section: Related Workmentioning

confidence: 83%

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Quality-aware membership management for layered peer-to-peer streaming

Nguyen

Eliassen

Welzl

2011

2011 IEEE Consumer Communications and Networking Conference (CCNC)

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With the standardization of SVC, the scalable extension of H.264/AVC, layered peer-to-peer streaming has attracted more and more attention as it offers adaptability to network fluctuations and heterogeneous end users. Although overlay construction is important for system performance, not much effort has been spent on unstructured overlay construction for layered peer-to-peer streaming. Related work concentrates on layered streaming algorithms, and assumes that a list of peers for data exchange, called neighbors, is provided by traditional membership management protocols, e.g., SCAMP. Our previous studies have demonstrated that a random overlay is not good enough for layered peer-to-peer streaming. In this paper, we propose a new membership management protocol, based on peer sampling services. The protocol is quality-aware as it constructs the overlay so that (1) high capacity peers will be located at good positions in the overlay, e.g., close to the server, and (2) peers having similar capacity are likely to connect to each other. Both features are necessary to maximize bandwidth utilization of peers and to mitigate layer bottlenecks. With implementation of the protocol in PeerSim, we evaluate important graph properties of the overlay, constructed by the proposed protocol, to understand how it evolves during the streaming session with peer churn. Evaluation results show that the overlay is (1) scalable: it is stable with different sizes, from hundreds up to 10000 peers; and (2) robust: the good features are maintained or recovered fast under a high peer churn rate, and it only becomes disconnected when more than 86% of the peers are removed from the network.

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Section: Related Workmentioning

confidence: 83%

“…al. [19] does not target P2P streaming applications. It elects super peers with highest utility to discover globally similar neighbors, while lower utility peers have mostly random neighbors.…”

Section: Related Workmentioning

confidence: 99%

Quality-aware membership management for layered peer-to-peer streaming

Nguyen

Eliassen

Welzl

2011

2011 IEEE Consumer Communications and Networking Conference (CCNC)

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“…For the similar view, nodes prefer neighbors with closer utility values, while for the gradient view, nodes prefer nodes with higher, but closer, utility values. Together these preference functions build a topology where gradient paths of increasing utilities emerge in the system [12], see figure 1.…”

Section: Introductionmentioning

confidence: 99%

Converging an overlay network to a Gradient topology

Terelius

Shi

Dowling³

et al. 2011

IEEE Conference on Decision and Control and European Control Conference

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In this paper, we investigate the topology convergence problem for the gossip-based Gradient overlay network. In an overlay network where each node has a local utility value, a Gradient overlay network is characterized by the properties that each node has a set of neighbors containing higher utility values, such that paths of increasing utilities emerge in the network topology. The Gradient overlay network is built using gossiping and a preference function that samples from nodes using a uniform random peer sampling service. We analyze it using tools from matrix analysis, and we prove both the necessary and sufficient conditions for convergence to a complete gradient structure, as well as estimating the convergence time. Finally, we show in simulations the potential of the Gradient overlay, by building a more efficient livestreaming peer-to-peer (P2P) system than one built using uniform random peer sampling.

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