A survey on resource allocation strategies in cloud

被引：0

作者：

Chenni Kumaran J. ^{[1
]}

Aramudhan M. ^{[2
]}

机构：

[1] Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu

[2] Department of Information Technology, Perunthalaivar Kamarajar Institute of Engineering and Technology, Karaikal, Tamil Nadu

来源：

International Journal of Reasoning-based Intelligent Systems | 2018年 / 10卷 / 3-4期

关键词：

Cloud computing; Cloud services; RA; Resource allocation;

D O I：

10.1504/IJRIS.2018.096229

中图分类号：

学科分类号：

摘要：

Cloud computing has turned into age innovation that has tremendous possibilities in endeavours and markets. Cloud can make it conceivable to get to applications and related information from any place. Organisations can lease assets from cloud for capacity and other computational purposes so that their framework cost can be lessened fundamentally. Facilitate they can make utilisation of vast access to applications, in view of pay-as-you-go display. Henceforth, there is no requirement for getting licenses for individual items. In this paper, different asset portion methodologies and their difficulties are talked about in detail. It is trusted that this paper would profit both cloud clients and analysts in defeating the difficulties confronted. Copyright © 2018 Inderscience Enterprises Ltd.

引用

页码：328 / 336

页数：8

共 14 条

[1]

Chenni Kumaran J., Aramudhan M., Resource allocation utilizing enthalpy based krill herd optimization algorithm in cloud computing, International Journal of Advance Research, Ideas and Innovations in Technology, 3, 4, pp. 117-124, (2017)

[2]

Huang K.-C., Lai K.-P., Processor allocation policies for reducing resource fragmentation in multi cluster grid and cloud environments, International Computer Symposium (ICS2010), pp. 971-976, (2010)

[3]

Keahey, Et al., Sky computing, Internet Computing, 13, 5, pp. 43-51, (2009)

[4]

Kim K.H., Et al., Power-aware provisioning of cloud resources for real time services, International Workshop on Middlleware for Grids and Clouds and E-Science, pp. 1-6, (2009)

[5]

Kolte S.A., Ajmire P.E., A survey – Cloud computing, International Journal of Advanced Research in Computer and Communication Engineering, 5, 4, pp. 1068-1071, (2016)

[6]

Kumar K., Et al., Resource allocation for real time tasks using cloud computing, Proceedings of 20th International Conference on Computer Communications and Networks (ICCCN), (2011)

[7]

Li C., Li L., Resource allocation in cloud computing: Model and algorithm, Int. J. Web and Grid Services, 9, 2, pp. 193-211, (2013)

[8]

Li J., Qiu M., Niu J.-W., Chen Y., Ming Z., Adaptive resource allocation for pre-empt able jobs in cloud systems, 10th International Conference on Intelligent System Design and Application, (2011)

[9]

Melendez J.O., Majumdar S., Matchmaking with limited knowledge of resources on clouds and grids, International Symposium on Performance Evaluation of Computer & Telecommunication Systems, pp. 102-110, (2010)

[10]

Varatharajan R., Manogaran G., Priyan M.K., Sundarasekar R., Wearable sensor devices for early detection of Alzheimer disease using dynamic time warping algorithm, Cluster Comput, (2017)

← 1 2 →