A Multi-Population Genetic Algorithm for Adaptive QoS-Aware Service
Composition in Fog-IoT Healthcare Environment
Idir Aoudia1, Saber Benharzallah2, Laid Kahloul1, and Okba
Kazar1
1LINFI Laboratory, Biskra University,
Algeria
2 LAMIE Laboratory, Computer Sciences department, Batna 2 University, Algeria
Abstract: The growth of Internet of Thing (IoT) implies
the availability of a very large number of services which may be similar or the
same, managing the Quality of Service (QoS) helps to differentiate one service
from another. The service composition provides the ability to perform complex
activities by combining the functionality of several services within a single
process. Very few works have presented an adaptive service composition solution
managing QoS attributes, moreover in the field of healthcare, which is one of
the most difficult and delicate as it concerns the precious human life.In this
paper, we will present an adaptive QoS-Aware Service Composition Approach (P-MPGA)
based on multi-population genetic algorithm in Fog-IoT healthcare environment.
To enhance Cloud-IoT architecture, we introduce a Fog-IoT 5-layared
architecture. Secondly, we implement a QoS-Aware Multi-Population Genetic
Algorithm (P-MPGA), we considered 12 QoS dimensions, i.e., Availability (A),
Cost (C), Documentation (D), Location (L), Memory Resources (M), Precision (P),
Reliability (R), Response time (Rt), Reputation (Rp), Security (S), Service
Classification (Sc), Success rate (Sr), Throughput (T). Our P-MPGA algorithm
implements a smart selection method which allows us to select the right
service. Also, P-MPGA implements a monitoring system that monitors services to
manage dynamic change of IoT environments. Experimental results show the
excellent results of P-MPGA in terms of execution time, average fitness values
and execution time / best fitness value ratio despite
the increase in population. P-MPGA
can quickly achieve a composite service satisfying user’s QoS needs, which
makes it suitable for a large scale IoT environment.
Keywords: IoT, service composition, adaptability, context; QoS,
Fog-IoT computing, Healthcare.
Received February 20, 2021; accepted March 7, 2021
https://doi.org/10.34028/iajit/18/3A/10