Distributed Service Level Agreement-Driven Dynamic Cloud Resource Management

2015 ◽  
pp. 517-527
Author(s):  
M. K. Gayatri ◽  
G. S. Anandha Mala
Keyword(s):  
Resource Management ◽  
Service Level Agreement ◽  
Service Level ◽  
Cloud Resource Management ◽  
Cloud Resource ◽  
Distributed Service

scholarly journals SLAMMP Framework for Cloud Resource Management and Its Impact on Healthcare Computational Techniques

2021 ◽  
Vol 12 (2) ◽  
pp. 1-31
Author(s):  
Vivek Kumar Prasad ◽  
Madhuri D. Bhavsar
Keyword(s):  
Short Term Memory ◽  
Service Level Agreement ◽  
Cost Effective ◽  
Service Level ◽  
Healthcare Sector ◽  
Computational Techniques ◽  
Healthcare Organizations ◽  
Cloud Resource Management ◽  
Cloud Resource ◽  
Cloud Users

Technology such as cloud computing(CC) is constantly evolving and being adopted by the industries to manage their data and tasks. CC provides the resources for managing the tasks of the cloud users. The acceptance of the CC in healthcare industries is proven to be more cost-effective and convenient. CC manager has to manage the resources to provide services to the end-users of the healthcare sector. The SLAMMP framework discussed here shows how the resources are managed by using the concept of reinforcement learning (RL) and LSTM (long short-term memory) for monitoring and prediction of the cloud resources for healthcare organizations. The task(s) pattern and anti-pattern scenarios have been observed using HMM (hidden Markov model). These patterns will tune the SLA parameters (service level agreement) using blockchain-based smart contracts (SC). The result discussed here indicates that the variations in the cloud resource demand will be handled carefully using the SLAMMP framework. From the result obtained, it is identified that SLAMMP performs well with the parameter used here.

Towards Industry 4.0 Through Cloud Resource Management

2021 ◽  
pp. 263-282
Author(s):  
Minakshi Sharma ◽  
Rajneesh Kumar ◽  
Anurag Jain ◽  
Bhupesh Kumar Dewangan ◽  
Jung-Sup Um ◽  
...  
Keyword(s):  
Resource Management ◽  
Industry 4.0 ◽  
Cloud Resource Management ◽  
Cloud Resource

Mobile Cloud Resource Management

2016 ◽  
pp. 1747-1773
Author(s):  
Konstantinos Katzis
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Mobile Cloud Computing ◽  
Finite Energy ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Seamless Integration ◽  
Cloud Resource Management ◽  
Cloud Resource ◽  
Management Techniques

Providing mobile cloud services requires seamless integration between various platforms to offer mobile users optimum performance. To achieve this, many fundamental problems such as bandwidth availability and reliability, resource scarceness, and finite energy must be addressed before rolling out such services. This chapter aims to explore technological challenges for mobile cloud computing in the area of resource management focusing on both parts of the infrastructure: mobile devices and cloud networks. Starting with introducing mobile cloud computing, it then stresses the importance of resource management in the operation of mobile cloud services presenting various types of resources available for cloud computing. Furthermore, it examines the various types of resource management techniques available for mobile clouds. Finally, future directions in the field of resource management for mobile cloud computing environment are presented.

scholarly journals Model-driven cloud resource management with OCCIware

2019 ◽  
Vol 99 ◽  
pp. 260-277 ◽  
Author(s):  
Faiez Zalila ◽  
Stéphanie Challita ◽  
Philippe Merle
Keyword(s):  
Resource Management ◽  
Cloud Resource Management ◽  
Model Driven ◽  
Cloud Resource

Cloud resource management using 3Vs of Internet of Big data streams

Computing ◽  
2019 ◽  
Vol 102 (6) ◽  
pp. 1463-1485 ◽  
Author(s):  
Navroop Kaur ◽  
Sandeep K. Sood ◽  
Prabal Verma
Keyword(s):  
Big Data ◽  
Resource Management ◽  
Data Streams ◽  
Cloud Resource Management ◽  
Cloud Resource ◽  
Big Data Streams

Non-linear analysis of bursty workloads using dual metrics for better cloud resource management

2019 ◽  
Vol 10 (12) ◽  
pp. 4977-4992 ◽  
Author(s):  
Mahesh Balaji ◽  
Ch. Aswani Kumar ◽  
G. Subrahmanya V. R. K. Rao
Keyword(s):  
Resource Management ◽  
Linear Analysis ◽  
Cloud Resource Management ◽  
Cloud Resource ◽  
Non Linear
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