P-ACOHONEYBEE: A Novel Load Balancer for Cloud Computing Using Mathematical Approach
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Date
2022-04-12
Journal Title
Journal ISSN
Volume Title
Publisher
Computers, Materials & Continua
Abstract
Cloud computing is a collection of disparate resources or services,
a web of massive infrastructures, which is aimed at achieving maximum
utilization with higher availability at a minimized cost. One of the most
attractive applications for cloud computing is the concept of distributed
information processing. Security, privacy, energy saving, reliability and load
balancing are the major challenges facing cloud computing and most informa tion technology innovations. Load balancing is the process of redistributing
workload among all nodes in a network; to improve resource utilization and
job response time, while avoiding overloading some nodes when other nodes
are underloaded or idle is a major challenge. Thus, this research aims to
design a novel load balancing systems in a cloud computing environment.
The research is based on the modification of the existing approaches, namely;
particle swarm optimization (PSO), honeybee, and ant colony optimization
(ACO) with mathematical expression to form a novel approach called P ACOHONEYBEE. The experiments were conducted on response time and
throughput. The results of the response time of honeybee, PSO, SASOS,
round-robin, PSO-ACO, and P-ACOHONEYBEE are: 2791, 2780, 2784,
2767, 2727, and 2599 (ms) respectively. The outcome of throughput of hon eybee, PSO, SASOS, round-robin, PSO-ACO, and P-ACOHONEYBEE are:
7451, 7425, 7398, 7357, 7387 and 7482 (bps) respectively. It is observed
that P-ACOHONEYBEE approach produces the lowest response time, high
throughput and overall improved performance for the 10 nodes. The research
has helped in managing the imbalance drawback by maximizing throughput,
and reducing response time with scalability and reliability.
Description
Keywords
ACO, cloud computing, load balancing, swarm intelligence, PSO, P-ACOHONEYBE, honeybee swarm