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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 4/2017

04.08.2016

K-Level with Buddy Memory Allocation (BMA) Approach for Parallel Workload Scheduling

verfasst von: A. Kousalya, R. Radhakrishnan

Erschienen in: Wireless Personal Communications | Ausgabe 4/2017

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Abstract

Utilizing the entire resources in the cloud is not possible, because of complex application. To manage the execution of such a difficult types of application, the parallel processing mechanism that tries to solve this problem while running the complex application. The volume of each node is divided into n number of Virtual Machines (VM) by using the virtualization technology. In this paper we propose a scheduling mechanism that partitions the computing capacity of each node in the data centers using the K-Level mechanism with Buddy Memory Allocation. The K-Level Task Allocation algorithm is used to schedule the parallel jobs in each node of K-level VMs which makes the resource utilization in an efficient manner.
Vorheriger Artikel A Hybrid Swarm Optimization for Energy Efficient Clustering in Multi-hop Wireless Sensor Network
Nächster Artikel Multi-Swarm Particle Swarm Optimization for Energy-Effective Clustering in Wireless Sensor Networks

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Metadaten
Titel
K-Level with Buddy Memory Allocation (BMA) Approach for Parallel Workload Scheduling
verfasst von
A. Kousalya
R. Radhakrishnan
Publikationsdatum
04.08.2016
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 4/2017
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-016-3563-7

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