Corona: A Stabilizing Deterministic Message-Passing Skip List

Nor, Rizal Mohd; Nesterenko, Mikhail; Scheideler, Christian

doi:10.1007/978-3-642-24550-3_27

Cited by 16 publications

(12 citation statements)

References 19 publications

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“…Recently, also a self-stabilizing variant of the popular Chord network was presented [15]. Moreover, in [18], the authors propose a self-stabilizing algorithm for skip list construction. The algorithm operates in a low atomicity message-passing asynchronous system model, which is the model we also adapt in our work.…”

Section: B Self-stabilizationmentioning

confidence: 99%

“…We assume the following model for the overlay network which is similar to the model presented in [18] by Nor et al, but modified in some aspects to allow us to distinguish different edges and to form more complex networks than lists. The overlay network consists of N nodes or processes.…”

Section: A Network Modelmentioning

confidence: 99%

“…For the execution of actions we assume weak fairness meaning that if an action is enabled in all but finitely many states of the computation then this action is executed infinitely often. As in [18] we focus on programs that comply with the compare-store-send program model, in which programs do not manipulate the internals of the nodes' identifiers. Additionally we need further computations like additions and randomization to implement the move-and-forget mechanism presented in [4], but still these operations are not on the identifiers such that the presented programs are still compare-store-send programs.…”

Section: B Computational Modelmentioning

confidence: 99%

“…Our approach is based on a process called linearization, which has been used to form a sorted list in various papers [19] [18]. The basic idea of this process is that each node p maintains two variables r and l where r stores an identifier greater than p and l an identifier smaller than p. If the value of p.r is not defined, i.e.…”

Section: A Linearizationmentioning

confidence: 99%

“…We slightly modify the proof for the linearization problem given in [18]. To show the theorem we prove a set of lemmas from which the theorem follows.…”

Section: Phase 2: Linearizationmentioning

confidence: 99%

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A Self-Stabilization Process for Small-World Networks

Kniesburges

Koutsopoulos

Scheideler

2012

2012 IEEE 26th International Parallel and Distributed Processing Symposium

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Abstract-Small-world networks have received significant attention because of their potential as models for the interaction networks of complex systems. Specifically, neither random networks nor regular lattices seem to be an adequate framework within which to study real-world complex systems such as chemical-reaction networks, neural networks, food webs, social networks, scientific-collaboration networks, and computer networks. Small-world networks provide some desired properties like an expected polylogarithmic distance between two processes in the network, which allows routing in polylogarithmic hops by simple greedy routing, and robustness against attacks or failures. By these properties, small-world networks are possible solutions for large overlay networks comparable to structured overlay networks like CAN, Pastry, Chord, which also provide polylogarithmic routing, but due to their uniform structure, structured overlay networks are more vulnerable to attacks or failures. In this paper we bring together a randomized process converging to a small-world network and a self-stabilization process so that a small-world network is formed out of any weakly connected initial state. To the best of our knowledge this is the first distributed self-stabilization process for building a small-world network.

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Section: B Self-stabilizationmentioning

confidence: 99%

Section: A Network Modelmentioning

confidence: 99%

Section: B Computational Modelmentioning

confidence: 99%

Section: A Linearizationmentioning

confidence: 99%

“…We slightly modify the proof for the linearization problem given in [18]. To show the theorem we prove a set of lemmas from which the theorem follows.…”

Section: Phase 2: Linearizationmentioning

confidence: 99%

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A Self-Stabilization Process for Small-World Networks

Kniesburges

Koutsopoulos

Scheideler

2012

2012 IEEE 26th International Parallel and Distributed Processing Symposium

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Churn Possibilities and Impossibilities

2019

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Churn is processes joining or leaving the peer-to-peer overlay network. We study handling of various churn variants. Cooperative churn requires leaving processes to participate in the churn algorithm while adversarial churn allows the processes to just quit. Infinite churn considers unbounded number of churning processes throughout a single computation. Unlimited churn does not place a bound on the number of concurrently churning processes. Fair churn handling requires that each churn request is eventually satisfied. A local solution involves only a limited part of the network in handing a churn request. We prove that it is impossible to handle adversarial unlimited churn. We sketch a global solution to all variants of cooperative churn and focus on local churn handling. We prove that a local fair solution to infinite churn, whether limited or unlimited, is impossible. On the constructive side, we present an algorithm that maintains a linear topology and handles the least restrictive unfair churn: infinite and unlimited. We extend this solution to a 1-2 skip list, describe enhancements for generalized skip lists and skip graphs.

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