TY - GEN
T1 - Collaborative Block Mining and Edge Task Offloading in MEC-Assisted Blockchain Networks
T2 - 2023 IEEE Global Communications Conference, GLOBECOM 2023
AU - Ye, Licheng
AU - Luo, Jingjing
AU - Jiang, Changkun
AU - Gao, Lin
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Mobile edge computing (MEC) is a promising technology for improving the efficiency and security of mobile blockchain networks, by allowing miners with limited computing resources to offload the computation-intensive mining tasks to edge computing servers that are proximate to them. Collaborative block mining can further improve the mining efficiency and increase the miner profit, by enabling multiple miners to pool their computation resources and transaction data together to mine new blocks collaboratively. Thus, an MEC-assisted collaborative blockchain network can leverage the advantages of both technologies, offering superior efficiency, security, and scalability for blockchains. While existing research in this area mainly focused on the single-coalition collaboration mode where each miner can only join one collaborative coalition, this work explores a more comprehensive multi-coalition collaboration mode, which allows each miner to join multiple collaborative coalitions. To analyze the miner behavior in such a scenario, we formulate a novel two-layer sequential game, consisting of a coalition formation game as the first-layer and an edge resource competition game (among the formed coalitions) as the second layer. Specifically, in the first layer, each miner acts as a game player and selects multiple coalitions to join, leading to an overlapping coalition formation (OCF) game among miners. In the second layer, each established coalition acts as a game player and decides the amount of edge computing resource to invest, leading to an edge resource competition (ERC) game among coalitions. We derive the closed-form Nash equilibrium for the ERC game, and propose an iterative algorithm that converges to a stable coalition structure for the OCF game. Simulation results show that the proposed multi-coalition collaboration mode can improve the system efficiency by 34.1% 54.3%, compared to the single-coalition collaboration mode.
AB - Mobile edge computing (MEC) is a promising technology for improving the efficiency and security of mobile blockchain networks, by allowing miners with limited computing resources to offload the computation-intensive mining tasks to edge computing servers that are proximate to them. Collaborative block mining can further improve the mining efficiency and increase the miner profit, by enabling multiple miners to pool their computation resources and transaction data together to mine new blocks collaboratively. Thus, an MEC-assisted collaborative blockchain network can leverage the advantages of both technologies, offering superior efficiency, security, and scalability for blockchains. While existing research in this area mainly focused on the single-coalition collaboration mode where each miner can only join one collaborative coalition, this work explores a more comprehensive multi-coalition collaboration mode, which allows each miner to join multiple collaborative coalitions. To analyze the miner behavior in such a scenario, we formulate a novel two-layer sequential game, consisting of a coalition formation game as the first-layer and an edge resource competition game (among the formed coalitions) as the second layer. Specifically, in the first layer, each miner acts as a game player and selects multiple coalitions to join, leading to an overlapping coalition formation (OCF) game among miners. In the second layer, each established coalition acts as a game player and decides the amount of edge computing resource to invest, leading to an edge resource competition (ERC) game among coalitions. We derive the closed-form Nash equilibrium for the ERC game, and propose an iterative algorithm that converges to a stable coalition structure for the OCF game. Simulation results show that the proposed multi-coalition collaboration mode can improve the system efficiency by 34.1% 54.3%, compared to the single-coalition collaboration mode.
UR - https://www.scopus.com/pages/publications/85187344864
U2 - 10.1109/GLOBECOM54140.2023.10437385
DO - 10.1109/GLOBECOM54140.2023.10437385
M3 - 会议稿件
AN - SCOPUS:85187344864
T3 - Proceedings - IEEE Global Communications Conference, GLOBECOM
SP - 4638
EP - 4643
BT - GLOBECOM 2023 - 2023 IEEE Global Communications Conference
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 December 2023 through 8 December 2023
ER -