Reliability and Confidentiality Co-Verification for Parallel Applications in Distributed Systems

Xie, Guoqi; Yang, Kehua; Luo, Haibo; Li, Renfa; Hu, Shiyan

doi:10.1109/tpds.2021.3049780

Cited by 13 publications

(2 citation statements)

References 32 publications

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“…where 𝛾 is the adjustment coefficient related to the weight coefficient and cost coefficients. Substituting Equation ( 14) into Equation (7), and the optimal values 𝜆 e 𝜏 =𝜆 e * can be obtained.…”

Section: Event-triggered Fully Distributed Algorithmmentioning

confidence: 99%

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Attack‐resilient event‐triggered distributed control strategy of microgrid based on multi‐objective optimization

Liu,

Wang,

Liu

et al. 2023

IET Generation Trans & Dist

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As an important form of renewable energy utilization, microgrid (MG) is considered to be the main bearing form of distributed generation in the future. One of the most concerning issues in the operation of MG is how to realize its economic dispatch (ED). Nowadays, distributed algorithms have been increasingly used to solve the economic dispatch problem of MG. However, the MG based on the distributed optimization architecture must bear higher cyber-attack risks. To address this issue, this paper investigates the distributed robust ED problem of MG. Firstly, a multi-objective dispatch model of MG using a linear weighted sum (LWS) algorithm is developed, which considers the environmental and economic costs. On this basis, an event-triggered fully distributed algorithm is proposed, which can effectively reduce communication times. Furthermore, an attack resilient strategy against false data injection (FDI) attacks is implemented in the proposed fully distributed algorithm, which has strong robustness against various colluding attacks and non-colluding attacks, and can eliminate incorrect measurement of incremental cost and power generation data. Finally, the effectiveness of the proposed distributed control strategy is demonstrated through case studies in this paper.

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Section: Event-triggered Fully Distributed Algorithmmentioning

confidence: 99%

“…However, centralized algorithms usually suffer from low computing efficiency, poor privacy, and high communication cost [1][2][3][4][5]. Due to the robustness [6], scalability, and privacy [7], the research on distributed algorithms for solving the ED problem has received extensive attention [3][4][5][6][7][8][9][10][11]. Ref.…”

Section: Introductionmentioning

confidence: 99%