A Failure Detector for Crash Recovery Systems in Cloud
Author(s) -
Bharati Sinha,
Awadhesh Kumar Singh,
Poonam Saini
Publication year - 2019
Publication title -
international journal of information technology and computer science
Language(s) - English
Resource type - Journals
eISSN - 2074-9015
pISSN - 2074-9007
DOI - 10.5815/ijitcs.2019.07.02
Subject(s) - computer science , cloud computing , scalability , crash , fault tolerance , cloudsim , virtual machine , latency (audio) , distributed computing , replication (statistics) , overhead (engineering) , elasticity (physics) , operating system , telecommunications , statistics , materials science , mathematics , composite material
Cloud computing has offered remarkable scalability and elasticity to distributed computing paradigm. It provides implicit fault tolerance through virtual machine (VM) migration. However, VM migration needs heavy replication and incurs storage overhead as well as loss of computation. In early cloud infrastructure, these factors were ignorable due to light load conditions; however, nowadays due to exploding task population, they trigger considerable performance degradation in cloud. Therefore, fault detection and recovery is gaining attention in cloud research community. The Failure Detectors (FDs) are modules employed at the nodes to perform fault detection. The paper proposes a failure detector to handle crash recoverable nodes and the system recovery is performed by a designated checkpoint in the event of failure. We use Machine Repairman model to estimate the recovery latency. The simulation experiments have been carried out using CloudSim plus.
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