Analisis Banker’s Algorithm untuk Penghindaran Deadlock Berbasis Simulasi Kuantitatif Multiskenario
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Christian Bastanta Sembiring Meliala
*
Universitas Pamulang, Tangerang Selatan,
Indonesia
- Teti Desyani Universitas Pamulang, Tangerang Selatan, Indonesia
- Moch Ibba Ali Yassin Universitas Pamulang, Tangerang Selatan, Indonesia
- Aldiansyah Sastrawinata Universitas Pamulang, Tangerang Selatan, Indonesia
- Mikael Surya Saputra Universitas Pamulang, Tangerang Selatan, Indonesia
- Brian Aidil Rizkita Universitas Pamulang, Tangerang Selatan, Indonesia
- Rizki Arohman Maulana Universitas Pamulang, Tangerang Selatan, Indonesia (*) Corresponding Author
Abstract
Deadlock represents a critical threat in operating system resource management, as it has the potential to bring all computational processes to a complete halt. This study examines the effectiveness, efficiency, and constraints of the Banker's Algorithm as a deadlock avoidance mechanism through a multi-scenario quantitative simulation. The data were derived from simulations involving three core components: the resource allocation matrix (Allocation), the maximum process requirement declaration (Max), and the resource availability vector (Available), within a system configuration consisting of five processes and three resource types. The findings demonstrate that the Banker’s Algorithm accurately distinguishes between safe and unsafe states through its two primary mechanisms: the Safety Algorithm and the Resource-Request Algorithm. With Available set to [3, 3, 2], the algorithm successfully identified the safe execution sequence ⟨P1, P3, P4, P0, P2⟩, ensuring all processes could complete without deadlock risk. When Available was reduced to [2, 1, 0], the system entered an unsafe state in which no process could initiate execution. Through multi-scenario simulations, the critical transition threshold from a safe to an unsafe state was identified at approximately 83% resource utilization. In terms of efficiency, the O(n²×m) time complexity makes the algorithm well-suited for small to medium-scale systems, though it may become a performance bottleneck in large-scale cloud computing environments. This study produces a quantitative evaluation framework that can serve as a reference for implementing the Banker’s Algorithm in modern operating systems.
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Copyright (c) 2026 Christian Bastanta Sembiring Meliala, Teti Desyani, Moch Ibba Ali Yassin, Aldiansyah Sastrawinata, Mikael Surya Saputra, Brian Aidil Rizkita, Rizki Arohman Maulana
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