Controlling Transaction Rate in Tangle Ledger: A Principal Agent Problem Approach

Abstract

Tangle is a distributed ledger technology that stores data as a directed acyclic graph (DAG). Unlike blockchain, Tangle does not require dedicated miners for its operation. This makes Tangle suitable for Internet of Things (IoT) applications. To prevent congestion and spamming, distributed ledgers have a built-in transaction rate control mechanism. This is typically achieved by increasing or decreasing the proof of work (PoW) difficulty level; unfortunately, this simplistic mechanism gives an unfair advantage to users with high computational power. This paper proposes a principal-agent problem (PAP) framework from microeconomics to control the transaction rate in Tangle. With users as the agents and the transaction rate controller as the principal, we design a truth-telling mechanism to assign PoW difficulty levels to agents as a function of their computational power. The solution of the PAP is achieved by compensating a higher PoW difficulty level with a larger weight/reputation for the transaction. The solution of PAP is obtained by solving a mixed-integer optimization problem. Moreover, we show that the decision variables have useful structures: the optimal solution of the PAP increases with the computational power of the agents. We also show that the optimal PoW increases with the number of agents. The structural result reduces the search space of the mixed-integer program and enables efficient computation of the optimal mechanism. Finally, via numerical examples, we illustrate the transaction rate control mechanism and study its impact on the dynamics of Tangle.