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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Ilmiah FIFO JURNAL MEDIA INFORMATIKA BUDIDARMA SINTECH (Science and Information Technology) Journal Martabe : Jurnal Pengabdian Kepada Masyarakat Journal of Information Systems and Informatics Abdimasku : Jurnal Pengabdian Masyarakat Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Journal of Intelligent Software Systems
Bagas Triaji
Universitas Teknologi Digital Indonesia, Yogyakarta
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Industrial & Manufacturing Engineering Social Sciences

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Empirical Evaluation of Decentralized Genomic Data Computation Using Bacalhau and IPFS Bagas Triaji; Badiyanto Badiyanto; Justivan Intifadhah Afif
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1311

Abstract

Large-scale genomic analysis typically relies on centralized infrastructures, creating conflicts between collaborative needs and data sovereignty regulations. This study solves this dilemma by evaluating a decentralized architecture designed to facilitate secure, inter-institutional genomic computation without moving raw data. We integrated Bacalhau for orchestration and IPFS Cluster with CRDT consensus for storage, employing AES-256 encryption. A quantitative evaluation was conducted on AWS using five t3.medium nodes to simulate a resource-constrained hospital network. We tested three scenarios: a centralized baseline (SSH+SCP), an ideal decentralized workflow, and a "chaos" scenario involving active network fault injection. While the centralized baseline was the fastest (Mean=37.69s), the decentralized architecture incurred a manageable ~30% overhead under ideal conditions (Mean=49.22s, SD=1.58s). Critically, under chaos fault injection, although execution time increased to 90.67s (SD=17.84s), the system achieved a superior 100% job completion rate compared to the fragile baseline. This research quantifies the trade-off between execution speed and system resilience in a healthcare context. We demonstrate that this architecture prioritizes data sovereignty and high availability over raw speed, offering a proven model for privacy-critical Decentralized Science (DeSci) collaborations.
Co-Authors Aloysius Agus Subagyo Andriyani, Widyastuti Asyahri Hadi Nasyuha Azanuddin Azanuddin Badiyanto Badiyanto Bambang Purnomosidi Dwi Putranto Cucut Hariz Pratomo Dessyana, Faras Faizal Makhrus Fallo, Trisno Febriyanti Angelia Ginting Ibnu Rusydi Ita Mariami Justivan Intifadhah Afif Laksana, Herdian Aji Leswanto, Tomi Muhammad Agung Nugroho Ratna Setyowati, Putri Rifai, Muhammad Arif Rikie Kartadie Sausani, Afifah Totok Suprawoto Yohanni Syahra