Online Payment Network Design

Online Admission Control and Rebalancing in Payment Channel Networks

Payment channel networks (PCNs) are a promising technology to improve the scalability of cryptocurrencies. PCNs, however, face the challenge that the frequent usage of certain routes may deplete channels in one direction, and hence prevent further transactions. In order to reap the full potential of PCNs, recharging and rebalancing mechanisms are required to provision channels, as well as an admission control logic to decide which transactions to reject in case capacity is insufficient. This paper presents a formal model of this optimisation problem. In particular, we consider an online algori…

一种用于在线预算可行拍卖的竞争性发布价格机制

A Competitive Posted-Price Mechanism for Online Budget-Feasible Auctions

本文针对在线预算可行拍卖中代理成本私密且按随机顺序到达的问题，提出一种基于OPT估计在线测试与自适应搜索的随机化发布价格机制，实现了常数竞争比，解决了EC 2012提出的开放问题。

Payment Network Design with Fees

Payment channels are the most prominent solution to the blockchain scalability problem. We introduce the problem of network design with fees for payment channels from the perspective of a Payment Service Provider (PSP). Given a set of transactions, we examine the optimal graph structure and fee assignment to maximize the PSP's profit. A customer prefers to route transactions through the PSP's network if the cheapest path from sender to receiver is financially interesting, i.e., if the path costs less than the blockchain fee. When the graph structure is a tree, and the PSP facilitates all trans…

Algorithmic Blockchain Channel Design

Payment networks, also known as channels, are a most promising solution to the throughput problem of cryptocurrencies. In this paper we study the design of capital-efficient payment networks, offline as well as online variants. We want to know how to compute an efficient payment network topology, how capital should be assigned to the individual edges, and how to decide which transactions to accept. Towards this end, we present a flurry of interesting results, basic but generally applicable insights on the one hand, and hardness results and approximation algorithms on the other hand.

具有严格投资回报率（ROS）约束的在线竞价算法

Online Bidding Algorithms with Strict Return on Spend (ROS) Constraint

本文研究严格ROSC约束下的自动竞价问题，证明即使i.i.d.环境下在线算法也无法实现次线性遗憾，并给出价值恒定时对数最优遗憾的算法。

Online Assignment of Heterogeneous Tasks in Crowdsourcing Markets

We investigate the problem of heterogeneous task assignment in crowdsourcing markets from the point of view of the requester, who has a collection of tasks. Workers arrive online one by one, and each declare a set of feasible tasks they can solve, and desired payment for each feasible task. The requester must decide on the fly which task (if any) to assign to the worker, while assigning workers only to feasible tasks. The goal is to maximize the number of assigned tasks with a fixed overall budget. We provide an online algorithm for this problem and prove an upper bound on the competitive rati…