Tangless: Optimizing Cost and Transaction Rate in IOTA by Using Lyapunov Optimization Theory

【Author】 Chen, Yinfeng; Guo, Yu; Bie, Rongfang

【Source】2022 18TH INTERNATIONAL CONFERENCE ON MOBILITY, SENSING AND NETWORKING, MSN

【影响因子】

【Abstract】IOTA has emerged as a promising and feeless decentralized computing paradigm for developing blockchain-based Internet of Things (IoT) applications with high-performance transaction rates and incremental scalability. To support micropayments of IoT devices, IOTA has abandoned the original blockchain reward mechanism while IOTA nodes voluntarily contribute resources to maintain network stability. However, removing the mining rewards results in the resource cost of generating IOTA ledgers (known as the Tangle) being borne only by IOTA nodes. With the continuous expansion of the IOTA network, cost consumption is increasing. Thus, the inability to effectively reduce the cost of Tangle generation would lead to people being reluctant to dedicate resources to IOTA for maintaining the network robustness. In this paper, for the first time, we present a full-fledged transaction cost optimization scheme for IOTA, called Tangless, which can assist IOTA nodes in effectively reducing the Tangle generation cost while maintaining the strong robustness of the IOTA network. By using our proposed scheme, each IOTA node can effectively formulate the threshold of transaction approval rate in real time, maintaining the stability of the IOTA network with the optimal computational cost. We harness Lyapunov optimization theory to design a computational optimization algorithm for minimizing the total cost of nodes in IOTA. Then, we resort to large deviations theory to devise an optimized transaction rate control algorithm to further eliminate orphan Tangles that waste computational costs. Comprehensive theoretical analysis and simulation experiments confirm the effectiveness and practicability of our proposed scheme.

【Keywords】IOTA; Tangle; Lyapunov optimization theory

【发表时间】2022

【收录时间】2023-06-12

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