
A Multi Agent Based Dynamic Resource Allocation in Fog-Cloud Computing Environment
Author(s) -
Ismail Zaharaddeen Yakubu,
Lele Muhammed,
Zainab Aliyu Musa,
Zakari Idris Matinja,
Ilya Musa Adamu
Publication year - 2021
Publication title -
trends in sciences
Language(s) - English
Resource type - Journals
ISSN - 2774-0226
DOI - 10.48048/tis.2021.413
Subject(s) - computer science , cloud computing , provisioning , distributed computing , edge computing , cloudsim , fog computing , computer network , quality of service , utility computing , virtual machine , enhanced data rates for gsm evolution , cloud computing security , operating system , telecommunications
Cloud high latency limitation has necessitated the introduction of Fog computing paradigm that extends computing infrastructures in the cloud data centers to the edge network. Extended cloud resources provide processing, storage and network services to time sensitive request associated to the Internet of Things (IoT) services in network edge. The rapid increase in adoption of IoT devices, variations in user requirements, limited processing and storage capacity of fog resources and problem of fog resources over saturation has made provisioning and allotment of computing resources in fog environment a formidable task. Satisfying application and request deadline is the most substantial challenge compared to other dynamic variations in parameters of client requirements. To curtail these issues, the integrated fog-cloud computing environment and efficient resource selection method is highly required. This paper proposed an agent based dynamic resource allocation that employs the use of host agent to analyze the QoSrequirements of application and request and select a suitable execution layer. The host agent forwards the application request to a layer agent which is responsible for the allocation of best resource that satisfies the requirement of the application request. Host agent and layers agents maintains resource information tables for matching of task and computing resources. CloudSim toolkit functionalities were extended to simulate a realistic fog environment where the proposed method is evaluated. The experimental results proved that the proposed method performs better in terms of processing time, latency and percentage QoS delivery.
HIGHLIGHTS
The distance between the cloud infrastructure and the edge IoT devices makes the cloud not too competent for some IoT applications, especially the sensitive ones
To minimize the latency in the cloud and ensure prompt response to user requests, Fog computing, which extends the cloud services to edge network was introduced
The proliferation in adoption of IoT devices and fog resource limitations has made resource scheduling in fog computing a tedious one
GRAPHICAL ABSTRACT