Papers for

blockchain network designers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Multiple proposers choose locations to minimize network delays

On the Geographic Incentives of Multiple Concurrent Proposers

Abstract: We study whether systems with multiple concurrent proposers (MCP) incentivize the geographic decentralization of proposers. In our model, concurrent proposers strategically choose their locations to maximize their captured market share of users, who decide where to send transactions by comparing each proposer's time to inclusion. The time to inclusion between a user and a proposer consists of two terms: the distance between them, and the distance between the proposer and her nearest quorum of attesters, the latter of which we term the quorum radius. We formally prove that proposers' quorum radii are the determinant of their incentives: proposers optimally choose where to locate in order to minimize their quorum radii. We obtain as a result co-location when proposers also serve as attesters, but geographic diversity when these roles are separate. We also examine pre-confirmations and faster intervalidator connections, showing that they attenuate the influence of the quorum radius and further destabilize co-location incentives.

Sun 27 SeptComputer Science and Game Theory
The gist
This paper looks at how multiple entities that propose new blocks in a network decide where to operate based on geography. Users pick which proposer to send their transactions to by considering how quickly their transactions will be included, which depends on both the physical distance to the proposer and the proposer's connection to other validators. The authors show that proposers try to position themselves to minimize the distance to their closest group of validators, which affects their reach and efficiency. When proposers also act as validators, they tend to group together, but if these roles are separate, they spread out geographically. Additional system features can reduce the impact of these distances and make proposer clustering less stable.
Open → 2609.33958v1

Bitcoin network forms robust structure through peer table sharing

How Bitcoin Forms Its Network: Peer-Table Sampling and Structural Properties

Abstract: The global structure of P2P networks underlying modern cryptocurrencies is hidden by design: each node only knows its neighbors and maintains a local \textit{peer table} of IP addresses. The peer table of a node can be seen as the node's ``local view'' of the set of nodes currently in the network: it is constantly updated with information collected from the neighbors and it is used by the node to establish new connections when needed. The maintenance rules of the nodes' peer tables determine the global structure of the network and its evolution. Even though the global structure is unknown to any node of the network as well as to any external observer, the rules for the exchange of information between neighbors are compatible with the design and use of network \textit{crawlers} that can query the nodes and extract some information about their peer tables. In this paper we first analyze the data we crawled from nodes of the Bitcoin and Dogecoin P2P networks, to collect information about the distribution of IP addresses in the peer tables and to estimate the evolution of network size and churn rate; we then use the estimates to set up the parameters for a simulation of the Bitcoin network and we analyze the evolution of the network structure that we get from the simulation. Overall, our results show that Bitcoin's peer-table maintenance rules induce non-uniform, heavy-tailed visibility patterns while nevertheless generating a well-connected and structurally robust network.

Mon 7 SeptNetworking and Internet ArchitectureSocial and Information Networks
The gist
Bitcoin nodes only know about a limited set of other nodes through what they call peer tables. These tables help nodes decide who to connect with next, shaping the entire network. The authors studied Bitcoin and Dogecoin networks by gathering data from these tables, then simulated Bitcoin’s network growth. They found that despite uneven information sharing, the network stays well connected and strong against problems.
Open → 2609.07609v1