RETRACTED ARTICLE: Efficient optimal resource allocation for profit maximization in software defined network approach to improve quality of service in cloud environments

Software-defined networking (SDR) technology is an approach to network management that enables dynamic, programmatically efficient network configuration in order to improve network performance and monitoring making it more like cloud computing than traditional network management. Cloud Resource sche...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of ambient intelligence and humanized computing 2021-06, Vol.12 (6), p.6241-6250
Hauptverfasser: Divya, R., Jayanthi, V. E.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Software-defined networking (SDR) technology is an approach to network management that enables dynamic, programmatically efficient network configuration in order to improve network performance and monitoring making it more like cloud computing than traditional network management. Cloud Resource scheduling is used to schedule the workload-based customer request. Here, cost effective resources allocation is introduced based on arriving request and cluster allocation. The profit maximizing scheme aims is to provide probabilistic guarantee against the resource overloading and migration. In this work, proposed software defined approach namely Modified Heuristic Search (MHS) Algorithm is proposed to achieve the cost-effective resources allocation in distributing computing environment to improve the Quality of Service in Cloud environment and its applications. To achieve the profit maximization, Cost Effective Reliable Resource allocation (CERRA) algorithm is utilized to measure the effective cluster selection in MHSA which includes a fitness function for selecting the arriving cloud requests to earn profit. Speed, transfer rate and energy are measured and compared with the existing method to analysis the resource allocation system.
ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-020-02192-8