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Dynamic Data Replication and Scheduling Using Fuzzy-CSO Algorithm for IoT-Clouds

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Abstract

Data replication and task scheduling are two strategies to enhance the performance of data-intensive applications. One of the main issues in the Internet of Things (IoT)-Cloud scenario is uploading data from the sensor gateways and replicating it across multiple cloud data centres (DCs) for high availability. To avoid such problems, there is a need to adaptively determine the number of replicas and their optimum locations. Although data replication ensures availability and reliability, keeping many copies of each data will increase storage space use. To overcome this problem, a minimal number of replicas need to be maintained for these files. Most of the existing works consider the system as non-faulty, but in real-time, various faults may occur at every data centre (DC). Hence, the main objectives of this research work are to adaptively determine the number of replicas and their optimum locations, as well as to design a fault-tolerant scheduling algorithm for IoT-based Cloud. This paper deals with the design of dynamic data replication and scheduling framework using the Hybrid Fuzzy-CSO algorithm for the IoT-Cloud. It uses the Cat Swarm Optimization (CSO) algorithm to find the optimal locations for replications. The fitness function is derived from the distance between the main DC and the other DCs. A Fuzzy logic decision model was designed to determine the optimal number of replicas. During task scheduling, data replication was performed in the selected replication points and scheduled accordingly. The experimental results have indicated that the proposed Fuzzy-CSO framework attains minimum data transfer time, minimum response delay, and higher bandwidth utilization than the existing algorithms.

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Abbreviations

IoT:

Internet of Things

GW:

Gateway

DC:

Data center

CSO:

Cat swarm optimization

FLD:

Fuzzy logic decision

CC:

Cloud computing

DR:

Data replication

QoS:

Quality of service

PSO:

Particle swarm optimization

FOP:

Fault occurrence probability

TEC:

Total energy cost

TSC:

Total storage capacity

ABO:

Artificial butterfly optimization

VM:

Virtual machine

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  1. Department of Electrical and Electronics Engineering, College of Engineering, Anna University, Chennai, 600025, India

    M. Saranya & R. Ramesh

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  1. M. Saranya
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Saranya, M., Ramesh, R. Dynamic Data Replication and Scheduling Using Fuzzy-CSO Algorithm for IoT-Clouds. J. Electr. Eng. Technol. 18, 3897–3909 (2023). https://doi.org/10.1007/s42835-023-01474-3

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