DynamoGraph: extending the Pregel paradigm for large-scale temporal graph processing

Steinbauer, Matthias; Kotsis, Gabriele

doi:10.1504/ijguc.2016.077491

Cited by 13 publications

(2 citation statements)

References 24 publications

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“…Future work will be to consider the directions of interpersonal communication like sender and receiver in e-mail communication and to examine a mixed index of temporal regularity and temporal duration of interpersonal communication. Another remaining issue is to examine the computational complexity and the scalability of our method, which would be improved by distributed approaches like the one proposed in Steinbauer and Kotsis (2016).…”

Section: Discussionmentioning

confidence: 99%

Weighted network graph for interpersonal communication with temporal regularity

2017

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Over the last decade, interpersonal communication has attracted more attention from researchers than before. Although the volume of data generated through various communication devices and tools could be enormous, the recent decrease in storage cost enables us to record and store it. The analysis of interpersonal communication is useful to estimate influence in social relationships among people, to detect communities, and to recommend potential friends for users on social networking services. A network graph, which is a mathematical model that represents people as nodes and past opportunities of interpersonal communication as edges, works in such analysis. However, when the capacity of the number of edges recordable in a graph database is limited, or when only a limited number of edges is used for high-speed analysis, it is still unclear which edges should be prioritized and utilized in the analysis. Previous studies suggested that edges in network graphs can be weighted on the basis of the aggregated duration of connections, the number of connections, or the connection time. However, temporal regularity in interpersonal communication has not been well considered in the previous studies. Therefore, in this paper, we propose an edge weighting method for network graphs from interpersonal communication that determines edge weighs on the basis of the scores obtained from the spectral analysis technique. The spectral analysis technique is utilized to numerically deal with temporal regularity and frequency of interpersonal communication. An examination using real records verifies that by using our edge weighting method, link prediction works better under a condition of the limited number of edges usable for the analysis. We also deeply analyze and present the distributions of the frequencies that characterize interpersonal communication.

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Section: Discussionmentioning

confidence: 99%

Weighted network graph for interpersonal communication with temporal regularity

2017

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“…Furthermore, initially when the unverified transactions are entered into the system, the representation of the system can be treated as a temporal graph. One can further improve the temporal graph by the Pregel-based approach in [8].…”

Section: Asti Protocolmentioning

confidence: 99%

A Hybrid Adaptive Transaction Injection Protocol and Its Optimization for Verification-Based Decentralized System

et al. 2019

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Latency is a critical issue that impacts the performance of decentralized systems. Recently we designed various protocols to regulate the injection rate of unverified transactions into the system to improve system performance. Each of the protocols is designed to address issues related to some particular network traffic syndrome. In this work, we first provide the review of our prior protocols. We then provide a hybrid scheme that combines our transaction injection protocols and provides an optimal linear combination of the protocols based on the syndromes in the network. The goal is to speed up the verification process of systems that rely on only one single basic protocol. The underlying basic protocols are Periodic Injection of Transaction via Evaluation Corridor (PITEC), Probabilistic Injection of Transactions (PIT), and Adaptive Semi-synchronous Transaction Injection (ASTI).

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