Gtna

Abstract

Concise and reliable graph-theoretic analysis of complex networks today is a cumbersome task, consisting essentially of the adaptation of intricate libraries for each specific problem instance. The growing number of complex metrics that have been proposed in the last years, which mainly gain significance due to the increasing computational capabilities at hand, have led to important new insights in the field. However, they have solely been implemented as single algorithms, each specialized for the purpose of calculating exactly the targeted metric for a selected type of network graph. A comprehensive, extensible tool for the concise evaluation of graphs is currently not available. For this purpose we introduce the Graph-Theoretic Network Analyzer (GTNA), an efficient, Java-based toolkit for the comprehensive analysis of complex network graphs. GTNA, while already including the main metrics that are used to analyze the complex networks in computer science today, is simple to extend through a well defined plugin interface for metrics, network descriptions and network generator models. Throughout the paper we present the design and simple extensibility of GTNA, as well as the network models and metrics that are already implemented and give examples of its scalability and performance.

Improving transaction succeed ratio in payment channel networks via enhanced node connectivity and balanced channel capacity

“…However, in our scheme, we select landmark intermediate nodes through public fundraising for CBS (in Section 3). We use GTNA 8 to map the network topology, and there is a random value $$r$$ for each node in the obtained graph. The random value $$r$$ will determine whether to join the CBS and which Community to enter in the case to join the CBS.…”

“…A typical solution is the Payment Channel Network (PCN), 1,4–6 which enables plenty of payments without requiring to access the blockchain, other than to initialize and close each channel. Lightning network 7,8 and Raiden network are the offline payment networks built by Bitcoin and Ethereum, respectively with the help of PCN. The key insight of PCN is to put the transaction into the off‐chain network and employ the routing algorithm to find the appropriate payment path for the transaction.…”

Growing a Web of Trust

“…We implemented all models in GTNA, a framework for the graph-theoretic analysis of network snapshots [22]2. We generated 20 instances for each model, parameter set, and size and averaged their graph-theoretic properties.…”

Can We Use Your Router, Please?

“…To analyze different graph theoretical properties of our constructed city mesh networks we used the Graph-Theoretic Network Analyzer (GTNA) (Schiller, Bradler, Schweizer, Mühlhäuser, & Strufe, 2010). We found that networks constructed using all routers would show good performance and high resiliency to node failures.…”