Lightning Network Economics: Topology

References

• Bartolucci S, Caccioli F, Vivo P (2020) A percolation model for the emergence of the bitcoin lightning network. Sci. Rep. 10(1):4488.Crossref, Google Scholar
• Baumol WJ (1952) The transactions demand for cash: An inventory theoretic approach. Quart. J. Econom. 66(4):545–556.Crossref, Google Scholar
• Bhattacharya S, Sinha S, Roy S (2020) Impact of structural properties on network structure for online social networks. Procedia Comput. Sci. 167:1200–1209.Crossref, Google Scholar
• Brânzei S, Segal-Halevi E, Zohar A (2022) How to charge lightning: The economics of bitcoin transaction channels. Domínguez-García A, Raginsky M, eds. 2022 58th Annual Allerton Conf. Comm. Control, Comput. (Allerton 2022) (Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ), 453–460.Google Scholar
• Coase RH (1960) The problem of social cost. J. Law Econom. 3(1):1–44.Crossref, Google Scholar
• Decker C (2023) Lightning network research—Topology datasets. Accessed September 19, 2023, http://dx.doi.org/10.5281/zenodo.4088530.Google Scholar
• Ersoy O, Roos S, Erkin Z (2020) How to profit from payments channels. Bonneau J, Heninger N, eds. 24th Internat. Conf. Financial Cryptography Data Security, FC 2020 (Springer, Berlin), 284–303.Google Scholar
• Grunspan C, Lehéricy G, Pérez-Marco R (2020) Ant routing scalability for the lightning network. Preprint, submitted February 20, https://arxiv.org/abs/2002.01374.Google Scholar
• Guasoni P, Huberman G, Shikhelman C (2024) Lightning network economics: Channels. Management Sci. 70(6):3827–3840.Link, Google Scholar
• Harris J, Zohar A (2020) Flood & loot: A systemic attack on the lightning network. Meiklejohn S, Shelat A, eds. AFT ’20: Proc. 2nd ACM Conf. Adv. Financial Tech. (Association for Computing Machinery, New York), 202–213.Google Scholar
• Kappos G, Yousaf H, Piotrowska A, Kanjalkar S, Delgado-Segura S, Miller A, Meiklejohn S (2021) An empirical analysis of privacy in the lightning network. Borisov N, Diaz C, eds. 25th Internat. Conf. Financial Cryptography Data Security, FC 2021 (Springer, Berlin), 167–186.Google Scholar
• Karp RM (1972) Reducibility among combinatorial problems. Miller RE, Thatcher JW, eds. Complexity of Computer Computations (Plenum Press, New York), 85–103.Crossref, Google Scholar
• Kőnig D (1931) Gráfok és mátrixok. Matematikai és Fizikai Lapok 38, 116–119.Google Scholar
• Korte B, Vygen J (2011) Combinatorial Optimization, vol. 1 (Springer, Berlin).Google Scholar
• Lee S, Kim H (2020) On the robustness of lightning network in bitcoin. Pervasive Mobile Comput. 61:101108.Crossref, Google Scholar
• Lin JH, Primicerio K, Squartini T, Decker C, Tessone CJ (2020) Lightning network: A second path toward centralisation of the bitcoin economy. New J. Phys. 22(8):083022.Crossref, Google Scholar
• Martinazzi S, Flori A (2020) The evolving topology of the lightning network: Centralization, efficiency, robustness, synchronization, and anonymity. PLoS One 15(1):e0225966.Crossref, Google Scholar
• Miller MH, Orr D (1966) A model of the demand for money by firms. Quart. J. Econom. 80(3):413–435.Crossref, Google Scholar
• Papadis N, Tassiulas L (2020) Blockchain-based payment channel networks: Challenges and recent advances. IEEE Access 8:227596–227609.Crossref, Google Scholar
• Papadis N, Tassiulas L (2022) Payment channel networks: Single-hop scheduling for throughput maximization. Mao S, ed. 41st IEEE Conf. Comput. Comm., INFOCOM 2022 (Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ), 900–909.Google Scholar
• Papadis N, Tassiulas L (2023) Deep reinforcement learning-based rebalancing policies for profit maximization of relay nodes in payment channel networks. Pardalos P, Kotsireas I, Knottenbelt WJ, Leonardos S, eds. Mathematical Research for Blockchain Economy. MARBLE 2023, Lecture Notes in Operations Research (Springer, Cham, Switzerland), 1–27.Google Scholar
• Pickhardt R, Nowostawski M (2020) Imbalance measure and proactive channel rebalancing algorithm for the lightning network. Plataniotis K, ed. 2nd IEEE Internat. Conf. Blockchain Cryptocurrency, ICBC 2020 (Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ), 1–5.Google Scholar
• Poon J, Dryja T (2015) The bitcoin lightning network: Scalable off-chain instant payments. Satoshi Nakamoto Institute, Austin, TX.Google Scholar
• Rohrer E, Tschorsch F (2020) Counting down thunder: Timing attacks on privacy in payment channel networks. Meiklejohn S, Shelat A, eds. AFT ’20: Proc. 2nd ACM Conf. Adv. Financial Tech. (Association for Computing Machinery, New York), 214–227.Google Scholar
• Rohrer E, Malliaris J, Tschorsch F (2019) Discharged payment channels: Quantifying the lightning network’s resilience to topology-based attacks. Plataniotis K, ed. 4th IEEE Eur. Sympos. Security Privacy Workshops, EUROS PW 2019 (Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ), 347–356.Google Scholar
• Roos S, Moreno-Sanchez P, Kate A, Goldberg I (2017) Settling payments fast and private: Efficient decentralized routing for path-based transactions. Preprint, submitted September 18, https://arxiv.org/abs/1709.05748.Google Scholar
• Sali Y, Zohar A (2020) Optimizing off-chain payment networks in cryptocurrencies. Preprint, submitted July 18, https://arxiv.org/abs/2007.09410.Google Scholar
• Seres IA, Gulyás L, Nagy DA, Burcsi P (2020) Topological analysis of bitcoin’s lightning network. Mathematical Research for Blockchain Economy (Springer, Berlin), 1–12.Crossref, Google Scholar
• Sguanci C, Sidiropoulos A (2023) Mass exit attacks on the lightning network. Mnaouer B, Stiller, Karray, eds. 2023 IEEE Internat. Conf. Blockchain Cryptocurrency (ICBC) (Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ), 1–3.Google Scholar
• Shikhelman C, Tikhomirov S (2022) Unjamming lightning: A systematic approach. Cryptology ePrint Archive.Google Scholar
• Sivaraman V, Venkatakrishnan SB, Ruan K, Negi P, Yang L, Mittal R, Fanti G, Alizadeh M (2020) High throughput cryptocurrency routing in payment channel networks. Bhagwan, Porter, eds. 17th USENIX Sympos. Networked Systems Design Implementation (Association for Computing Machinery, New York), 777–796.Google Scholar
• Tang W, Wang W, Fanti G, Oh S (2020) Privacy-utility tradeoffs in routing cryptocurrency over payment channel networks. Chaintreau, Golubchik, Zhang, eds. Proc. ACM Measurement Anal. Comput. Systems, vol. 4, issue 2 (Association for Computing Machinery, New York), 29:1–29:39.Google Scholar
• Tobin J (1956) The interest-elasticity of transactions demand for cash. Rev. Econom. Statist. 38(3):241–247.Crossref, Google Scholar
• Varma SM, Maguluri ST (2021) Throughput optimal routing in blockchain-based payment systems. IEEE Trans. Control Network Systems 8(4):1859–1868.Crossref, Google Scholar
• Wang P, Xu H, Jin X, Wang T (2019) Flash: Efficient dynamic routing for offchain networks. Mohaisen, Zhang, eds. 15th Internat. Conf. Emerging Networking Experiments Tech. (CoNEXT ’19) (Association for Computing Machinery, New York), 370–381.Google Scholar
• Wilson RJ (1979) Introduction to Graph Theory (Pearson Education India, Chennai, India).Google Scholar
• Yu R, Xue G, Kilari VT, Yang D, Tang J (2018) Coinexpress: A fast payment routing mechanism in blockchain-based payment channel networks. 27th Internat. Conf. Comput. Comm. Networks (IEEE, Piscataway, NJ), 1–9.Google Scholar
• Zhang X, Tang S, Zhao Y, Wang G, Zheng H, Zhao B (2017) Cold hard e-cash: Friends and vendors in the Venmo digital payments system. Zhang, Tang, Zhao, Wang, Zheng, Zhao, eds. Proc. Eleventh Internat. AAAI Conf. Web Social Media (ICWSM 2017) (PKP Publishing Services Network, Burnaby, BC), 387–396.Google Scholar