On the Impact of Attachment Strategies for Payment Channel Networks

Lange, Kimberly; Rohrer, Elias; Tschorsch, Florian

doi:10.48550/arxiv.2102.09256

Cited by 3 publications

(6 citation statements)

References 26 publications

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“…The fact that with publicly known balance values in 19 out of 20 payment pairs the amount that can be delivered is as high as the local limits of the payment pair is in stark contradiction to the currently observed and reported [3,6,10,13] success rates. In fact, these are declining heavily with amounts larger than 100, 000 satoshi (1 BTC = 100,000,000 sat) for which the delivery should be almost always possible.…”

Section: Flows On a Known Balance Graphcontrasting

confidence: 59%

“…Similarly, the receiving destination node d could tell the sending node about the state of its local channels and this knowledge could also be incorporated into the graph by creating edges with 0 log probabilities and decreased capacities. 6 In Figure 1 we have demonstrated that for about 95% of all payment pairs the amount that can be delivered through the network is actually limited by the local outbound capacity of the sender and the local inbound capacity of the receiving node which yields another motivation for this information to be shared.…”

Section: Payment Algorithmmentioning

confidence: 98%

“…Currently the sender node mitigates this uncertainty by entering a trial-anderror loop for delivering payments. However, past experiments have demonstrated that payments are often failing, in particular when the amounts to be delivered are increasing [3,6,10,13].…”

Section: Introductionmentioning

confidence: 99%

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Optimally Reliable & Cheap Payment Flows on the Lightning Network

Pickhardt,

Richter

2021

Preprint

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Today, payment paths in Bitcoin's Lightning Network are found by searching for shortest paths on the fee graph. We enhance this approach in two dimensions. Firstly, we take into account the probability of a payment actually being possible due to the unknown balance distributions in the channels. Secondly, we use minimum cost flows as a proper generalization of shortest paths to multi-part payments (MPP).In particular we show that under plausible assumptions about the balance distributions we can find the most likely MPP for any given set of senders, recipients and amounts by solving for a (generalized) integer minimum cost flow with a separable and convex cost function. Polynomial time exact algorithms as well as approximations are known for this optimization problem.We present a round-based algorithm of min-cost flow computations for delivering large payment amounts over the Lightning Network. This algorithm works by updating the probability distributions with the information gained from both successful and unsuccessful paths on prior rounds. In all our experiments a single digit number of rounds sufficed to deliver payments of sizes that were close to the total local balance of the sender. Early experiments indicate that our approach increases the size of payments that can be reliably delivered by several orders of magnitude compared to the current state of the art.We observe that finding the cheapest multi-part payments is an NP-hard problem considering the current fee structure and propose dropping the base fee to make it a linear min-cost flow problem. Finally, we discuss possibilities for maximizing the probability while at the same time minimizing the fees of a flow. While this turns out to be a hard problem in general as well -even in the single path case -it appears to be surprisingly tractable in practice.

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Section: Flows On a Known Balance Graphcontrasting

confidence: 59%

Section: Payment Algorithmmentioning

confidence: 98%

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Optimally Reliable & Cheap Payment Flows on the Lightning Network

Pickhardt,

Richter

2021

Preprint

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“…Current research on the Lightning Network focuses on three aspects: topological properties [15,19,20,[23][24][25][26][27][28], security [9,14,[29][30][31][32][33][34][35], and routing methods [11,12,17,[36][37][38][39]. Although all the above studies are very important aspects of Lightning Network, they are strictly dependent on the underlying topological network.…”

Section: Related Workmentioning

confidence: 99%

Can Lightning Network’s Autopilot Function Use BA Model as the Underlying Network?

et al. 2022

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By extending micropayment channel technology and building a transaction network, the Lightning Network solves inefficient bitcoin transactions. Currently, more than 1,000 Bitcoins have been deposited in the Lightning Network. In designing the Lightning Network routing protocol, simulating its transactions, and evaluating the network robustness, researchers have almost always used the Barabasi Albert Model as a substrate network. In particular, as the network grows in size, it becomes particularly important to automatically establish links for the network of joined nodes—the autopilot function—and it becomes a crucial question whether the Barabasi Albert Model as the underlying network for the autopilot function conforms to the real topology of the Lightning Network. In this paper, we construct the temporal network of Lightning Network and compare the topological properties of Lightning Network with those of Barabasi Albert Model of the same scale in detail. Lightning Network has a large gap with Barabasi Albert Model in terms of assortativity and network diameter. We found that nodes tend to connect to nodes with greater Closeness Centrality in terms of node preference connectivity. Our findings suggest that using the Barabasi Albert Model as the underlying network for the autopilot function is not a reasonable choice.

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“…Outro desafio de segurança enfrentado pela Rede Relâmpago é a alta concentração de renda e conectividade, o que a torna vulnerável a ataques direcionados aos nós de maior grau [Rohrer et al 2019, Seres et al 2020]. Lange et al verificam o impacto de políticas de preferência de conexão na Rede Relâmpago do ponto de vista individual e global [Lange et al 2021]. Os autores verificam que a conexão aos nós mais centrais produz um benefício do ponto de vista individual, recebendo mais tarifas de pagamentos.…”

Section: Conclusão E Perspectivas Futurasunclassified

Redes de Canais de Pagamento: Provendo Escalabilidade para Pagamentos em Criptomoedas

Camilo¹,

Rebello²,

Airam³

et al. 2022

Minicursos Do XL Simpósio Brasileiro De Redes De Computadores E Sistemas Distribuídos

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Blockchain revolutionized the transfer of assets in the 21st century and enabled the creation and wide adoption of cryptocurrencies. Despite the great success of cryptocurrencies, consensus protocols' low performance makes their adoption as a daily payment method infeasible. Other factors that inhibit the advancement of cryptocurrencies as an alternative payment method are the high confirmation latency and the high value of fees. Thus, the Payment Channel Network (PCN) technology presents a fast and secure solution to the blockchain scalability problem. Payment channel networks introduce a new way of transacting, displaying high transaction throughput by minimizing the number of transactions recorded at the blockchain. This chapter addresses the payment channel networks technology to provide an efficient and agile cryptocurrencies transfer. We present a hands-on activity that uses PCNsim, a modular simulator of payment channel networks developed by GTA (Grupo de Teleinformática e Automação). The goal of this chapter is to demonstrate the key concepts of payment channel networks and associate these concepts with research challenges in computer networks and information security. It is expected that, by the end of the chapter, the readers will master the fundamentals of payment channel networks and develop skills to identify their advantages and disadvantages critically. Moreover, readers are expected to understand the challenges related to privacy and routing and be on the cutting-edge of the technology to foster high-level research in the area.

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On the Impact of Attachment Strategies for Payment Channel Networks

Cited by 3 publications

References 26 publications

Optimally Reliable & Cheap Payment Flows on the Lightning Network

Optimally Reliable & Cheap Payment Flows on the Lightning Network

Can Lightning Network’s Autopilot Function Use BA Model as the Underlying Network?

Redes de Canais de Pagamento: Provendo Escalabilidade para Pagamentos em Criptomoedas

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