Dynamic Resource Allocation in Cloud Computing Based on Software-Defined Networking Framework
release_byyczl5ndzakfkx22qkql3js6u
by
Arwa Mohamed,
Mosab Hamdan,
Ahmed Abdelazizb,
Sharief F. Babiker
Abstract
cloud computing has become more powerful with the inclusion of software-defined networking (SDN) in its environment. In Cloud Data Centers (CDCs), an important research issue is how to forecast and allocate resources efficiently whilst achieving Quality of Service (QoS) of users request with minimal overall power consumption; taking into account the frequent changes in resource requirements. In this paper, we propose a Supervisor Controller-based Software-Defined Cloud Data Center (SC-boSD-CDC) framework for dynamic resource allocation and prediction of cloud computing-based SDN. In this proposed module, Genetic Algorithm (GA) is proposed to deal with the multi-objective problem of dynamically forecasting the utilization of resources in both compute nodes and links bandwidth of network as well as energy consumption in the Cloud Data Center (CDC). Furthermore, a Virtual Machines (VMs) placement algorithm is also proposed to allocate computing resources and routing algorithms to choose the proper bandwidth links between switches; resulting in increased CPU and memory utilization and reduction in overall power consumption.
In application/xml+jats
format
Archived Files and Locations
application/pdf
429.5 kB
file_pqzoxosnijaudor5mzd7r47a5q
|
readersinsight.net (publisher) web.archive.org (webarchive) |
article-journal
Stage
published
Date 2020-10-31
access all versions, variants, and formats of this works (eg, pre-prints)
Crossref Metadata (via API)
Worldcat
SHERPA/RoMEO (journal policies)
wikidata.org
CORE.ac.uk
Semantic Scholar
Google Scholar