Software-Defined Networks for Resource Allocation in Cloud Computing: A Survey

Arwa Mohamed *, Mosab Hamdan*, Suleman Khan, Ahmed Abdelaziz, Sharief f. Babiker, Muhammad Imran*, M. N. Marsono*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

Cloud computing has a shared set of resources, including physical servers, networks, storage, and user applications. Resource allocation is a critical issue for cloud computing, especially in Infrastructure-as-a-Service (IaaS). The decision-making process in the cloud computing network is non-trivial as it is handled by switches and routers. Moreover, the network concept drifts resulting from changing user demands are among the problems affecting cloud computing. The cloud data center needs agile and elastic network control functions with control of computing resources to ensure proper virtual machine (VM) operations, traffic performance, and energy conservation. Software-Defined Network (SDN) proffers new opportunities to blueprint resource management to handle cloud services allocation while dynamically updating traffic requirements of running VMs. The inclusion of an SDN for managing the infrastructure in a cloud data center better empowers cloud computing, making it easier to allocate resources. In this survey, we discuss and survey resource allocation in cloud computing based on SDN. It is noted that various related studies did not contain all the required requirements. This study is intended to enhance resource allocation mechanisms that involve both cloud computing and SDN domains. Consequently, we analyze resource allocation mechanisms utilized by various researchers; we categorize and evaluate them based on the measured parameters and the problems presented. This survey also contributes to a better understanding of the core of current research that will allow researchers to obtain further information about the possible cloud computing strategies relevant to IaaS resource allocation.
Original languageEnglish
Article number108151
Pages (from-to)1-22
Number of pages22
JournalComputer Networks
Volume195
Early online date14 May 2021
DOIs
Publication statusPublished - 4 Aug 2021

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