The state of peer-to-peer network simulators

Identification of influential nodes is an important step in understanding and controlling the dynamics of information, traffic and spreading processes in networks. As a result, a number of centrality measures have been proposed and used across different application domains. At the heart of many of these measures, lies an assumption describing the manner in which traffic (of information, social actors, particles, etc.) flows through the network. For example, some measures only count shortest paths while others consider random walks. This paper considers a spreading process in which a resource necessary for transit is partially consumed along the way while being refilled at special nodes on the network. Examples include fuel consumption of vehicles together with refueling stations, information loss during dissemination with error correcting nodes, and consumption of ammunition of military troops while moving. We propose generalizations of the well-known measures of betweenness, random walk betweenness, and Katz centralities to take such a spreading process with consumable resources into account. In order to validate the results, experiments on real-world networks are carried out by developing simulations based on well-known models such as Susceptible-Infected-Recovered and congestion with respect to particle hopping from vehicular flow theory. The simulation-based models are shown to be highly correlated to the proposed centrality measures. Reproducibility: Our code, and experiments are available at https://github.com/hmwesigwa/soc centrality

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“…The proposed centrality measures in the following sections are based on computing the feasible walks in the network. 6…”

Section: Graph Modelmentioning

confidence: 99%

Centralities for networks with consumable resources

Ushijima‐Mwesigwa

Khan²,

Chowdhury³

et al. 2019

Net Sci

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“…On the other hand, like many other authors [4], [10], [17], [20], [24], [29], we consider simulations a more practical tool for conducting comprehensive evaluation campaigns on large-scale systems such as cooperative systems. The use of simulations allows for a perfect control over the experimental conditions, high reproducibility, faster execution time, and the possibility of simulating millions of nodes on a single host [2]. These features come at the price of a high level of abstraction, which can introduce some bias in the experimental results [12].…”

Section: Related Workmentioning

confidence: 99%

“…For the purpose of these experiments, a designer can rely on frameworks for developing and evaluating real distributed systems [16], [19] or simulations of such systems [2], [27]. However, existing frameworks do not provide any specific support for modelling and injecting selfishness, which has to be done manually.…”

Section: Introductionmentioning

confidence: 99%

Analysing Selfishness Flooding with SEINE

Cota

Mokhtar

Gianini

et al. 2017

2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)

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Selfishness is one of the key problems that confronts developers of cooperative distributed systems (e.g., filesharing networks, voluntary computing). It has the potential to severely degrade system performance and to lead to instability and failures. Current techniques for understanding the impact of selfish behaviours and designing effective countermeasures remain manual and time-consuming, requiring multi-domain expertise. To overcome these difficulties, we propose SEINE, a simulation framework for rapid modelling and evaluation of selfish behaviours in a cooperative system. SEINE relies on a domain-specific language (SEINE-L) for specifying selfishness scenarios, and provides semi-automatic support for their implementation and study in a state-of-the-art simulator. We show in this paper that (1) SEINE-L is expressive enough to specify fifteen selfishness scenarios taken from the literature, (2) SEINE is accurate in predicting the impact of selfishness compared to real experiments, and (3) SEINE substantially reduces the development effort compared to traditional manual approaches.

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“…When using a P2P simulator, the evaluation will gain an advantage in terms of high scalability (up to one million). However, the reputable simulators that enable a large number of peers have been rely on abstracted networking model [32]. A question will still remain from the result derived by those simulators, i.e.…”

Section: Environmentmentioning

confidence: 99%