Open Access

ARTICLE

Fault-Tolerant Communication Induced Checkpointing and Recovery Protocol Using IoT

by Neha Malhotra^1,2,*, Manju Bala³

1 I.K.Gujral Punjab Technical University, Kapurthala, 144603, India
2 Lovely Professional University, Phagwara, 144411, India
3 Khalsa College of Engineering and Technology, Amritsar, 143001, India

* Corresponding Author: Neha Malhotra. Email:

(This article belongs to the Special Issue: Intelligence 4.0: Concepts and Advances in Computational Intelligence)

Intelligent Automation & Soft Computing 2021, 30(3), 945-960. https://doi.org/10.32604/iasc.2021.019082

Received 01 April 2021; Accepted 14 May 2021; Issue published 20 August 2021

Abstract

In mobile computing systems, nodes in the network take checkpoints to survive failures. Certain characteristics of mobile computing systems such as mobility, low bandwidth, disconnection, low power consumption, and limited memory make these systems more prone to failures. In this paper, a novel minimum process communication-induced checkpointing algorithm that makes full use of the computation ability and implementation of effective stable storage in a mobile computing system is proposed. The said approach initiates by taking spontaneous checkpoints by each node in phase 1 using a logistic function that is specifically used to estimate the time interval between two checkpoints and saves them locally. In phase 2, each node takes checkpoints in a coordinated manner using the Takagi–Sugeno (T–S) fuzzy system, which generates results based on the interpretation of 39 rules specifically incorporated in the system to avoid unnecessary and irrelevant checkpoints. Finally, the permanent checkpoints are stored on IoT(Internet of things) to reduce the storage capacity of the system. Quantitative analysis and experimental simulation prove that the proposed scheme outperforms other communication-induced checkpointing schemes in terms of the minimum number of processes required to take the checkpoints and communication cost. Simulation results prove that the checkpointing process becomes faster as compared to the existing techniques due to a decrease in the latency wrt to the number of nodes and storage of permanent checkpoints on IoT. With the advent of network partitioning in the proposed system, the average computation loss has also reduced as the rollback recovery takes place in a particular partition only, not in the entire network. The overall approach makes a mobile distributed computing system fault tolerant while non-blocking of the processes during the checkpointing process.

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Keywords

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