SIFAT-SIFAT ROLLBACK RECOVERY MENGGUNAKAN UNCOORDINATED CHECKPOINTING BERBASIS CAUSALITY STRENGTH
DOI:
https://doi.org/10.20956/jmsk.v15i2.5716Keywords:
Causality Strength, Domino Effect, Rollback Recovery, Uncoordinated CheckpointingAbstract
Abstract
Fault tolerance approach is the most popular computing application on computer devices in which depends on checkpoint uncoordinated. This alternative approach is based on checkpoint uncoordinated and logging message requiring all records, imposing works, memories and overhead becomes significant to communication. Recent studies have found that many applications on computer are send-determinism which can possibly design a new fault tolerance protocol. Thus, this research uses checkpoint uncoordinated protocol based causality strength, a send-determinism feature to record one part of the messages without restarting the process systematically when the error occurs. By drawing the protocol and proving its validity are required as the effective methods of this research. With this alternative approach, the protocol can functionally work where the only small portion of the message is recorded and domino effect does not occur.
Keywords : Causality Strength, Domino Effect, Rollback Recovery, Uncoordinated Checkpointing
Abstrak
Pendekatan toleransi kesalahan yang paling populer untuk aplikasi komputasi pada perangkat komputer bergantung pada checkpoint uncoordinated. Alternatif pendekatan tersebut berdasarkan pada checkpoint uncoordinated dan logging pesan mengharuskan pencatatan semua pesan, memaksakan pekerjaan memori/penyimpanan tinggi dan overhead yang signifikan pada komunikasi. Baru-baru ini telah diamati bahwa banyak aplikasi pada komputer bersifat send-determinism yang memungkinkan untuk mendesain protokol toleransi kesalahan baru. Sehingga penelitian ini menggunakan protokol checkpoint uncoordinated berbasis causality strength yang bersifat send-determinism yang hanya mencatat satu bagian dari pesan dan tidak perlu me-restart secara sistematis semua proses ketika kegagalan terjadi. Untuk menunjukkan bahwa penelitian ini berjalan sesuai dengan metode yang digunakan yaitu dengan menggambarkan protokol dan membuktikan kebenarannya. Dengan menggunakan pendekatan tersebut, dapat ditunjukkan bahwa protokol ini benar-benar berhasil dimana hanya mencatat sebagian kecil dari pesan dan tidak terjadi efek domino.
Kata kunci : Causality Strength, Efek Domino, Rollback Recovery, Uncoordinated CheckpointingReferences
. Chakarat S., Neeraj M., and Vijay K. Garg., 1999. A lightweight Algorithm for Causal Pesan Ordering in Mobile Computing Systems. Departement Electrical and Computer Engineering.
. Guermouche, Amina, et al., 2011. "Uncoordinated checkpointing without domino effect for send-deterministic mpi applications." Parallel & Distributed Processing Symposium (IPDPS), 2011 IEEE International. IEEE.
. L. Lamport., 1978. Time, clock and the ordering of event in a distributed system. Communications of the ACM, 21 (7):558 - 565.
Leonardo Fialho_, Dolores Rexachs and Emilio Luque. 2007. Defining the Checkpoint Interval for Uncoordinated Checkpointing Protocols. Department of Computer Architecture and Operating System, University Autonoma of Barcelona, Spain.
. S. Veerapandi, S. Gavaskar, StD, dan A. Sumithra, StD., 2017. A Hybrid Fault Tolerance System for Distributed Environment using Check Point Mechanism and Replication. Research Scholar School of information Technology Madurai Kamaraj University.
. Shwethashree A, dan Swathi D V., 2017. A Brief Review Of Approaches For Fault Tolerance In Distributed Systems. Institute of Technology and Management, Ballari, Karnataka, India.
. Yoshida, Takaichi., 2001. Pesan ordering based on the strength of a causal relation. In: Information Networking, Proceedings. 15th International Conference on. IEEE. p. 915-920.
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