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. Distributed ledgers have a built-in transaction rate control mechanism to prevent congestion and spamming; this is typically achieved by increasing or decreasing the proof of work (PoW) difficulty level based on the number of users. Unfortunately, this simplistic mechanism gives an unfair advantage to users with high computing power. This paper proposes a principal-agent problem (PAP) framework from microeconomics to control the transaction rate in Tangle. With users as 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 computing power. The solution of the PAP is achieved by compensating a higher PoW difficulty level with a larger weight/reputation for the transaction. The mechanism has two benefits, (1) the security of Tangle is increased as agents are incentivized to perform difficult PoW, and (2) the rate of new transactions is moderated in Tangle. The solution of PAP is obtained by solving a mixed-integer optimization problem. We show that the optimal solution of the PAP increases with the computing power of agents. The structural results reduce the search space of the mixed-integer program and enable 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.

翻译：Tangle是一种分布式账本技术，它将数据存储为有向无环图（DAG）。与区块链不同，Tangle无需专门矿工即可运行，因此适用于物联网（IoT）应用场景。分布式账本内置交易速率控制机制以防止拥塞和垃圾信息攻击，通常通过根据用户数量调整工作量证明（PoW）难度级别来实现。然而，这种简单机制会赋予高计算能力用户不公平的优势。本文提出基于微观经济学的委托代理问题（PAP）框架来控制Tangle中的交易速率。将用户视为代理人，交易速率控制器视为委托人，我们设计了一种真相揭示机制，根据代理人的计算能力为其分配PoW难度级别。PAP的解通过用更高的权重/信誉补偿更难的PoW难度级别实现。该机制具有两大优势：（1）通过激励代理人执行高难度PoW提升Tangle安全性；（2）有效调节Tangle中新增交易速率。PAP的解通过求解混合整数优化问题获得。我们证明PAP的最优解随代理人计算能力的提升而增大。结构化结果缩小了混合整数规划问题的搜索空间，实现了最优机制的高效计算。最后，通过数值算例演示了交易速率控制机制，并研究了其对Tangle动态特性的影响。