A Model Driven Framework for Portable Cloud Services

<p>Cloud services have become more popular among users these days. Automatic resource provisioning for cloud services is one of the important challenges in cloud environments. In the cloud computing environment, resource providers shall offer required resources to users automatically without any limitations. It means whenever a user needs more resources, the required resources should be dedicated to the users without any problems. On the other hand, if resources are more than user’s needs extra resources should be turn off temporarily and turn back on whenever they needed. In this paper, we propose an automatic resource provisioning approach based on reinforcement learning for auto-scaling resources according to Markov Decision Process (MDP). Simulation Results show that the rate of Service Level Agreement (SLA) violation and stability that the proposed approach better performance compared to the similar approaches.</p>

Section: Performance Evaluationmentioning

confidence: 99%

An Effiecient Approach for Resource Auto-Scaling in Cloud Environments

Asgari

Ghobaei‐Arani

Jabbehdari

2016

“…We even can establish a private cloud with Ubuntu Enterprise Cloud to offer immediacy and elasticity in the infrastructure of web applications [5]. In summary, both of the numbers of cloud applications and providers have kept gradually increasing for a couple of years [6,7]. As a result, computing resource scheduling and performance managing have been one of the most important aspects of cloud computing [8,9].…”

Section: Introductionmentioning

confidence: 99%

Dynamic control and Resource management for Mission Critical Multi-tier Applications in Cloud Data Center

Sahoo

Goswami

2016

The multi-tier architecture style has become an industry standard in modern data centers with each tier providing certain functionality. To avoid congestion and to adhere the SLA under fluctuating workload and unpredictable failures of Mission Critical Multi-tier applications hosted in the cloud, we need a Dynamic admission control policy, such that the requests must be processed from the first tier to the last without any delay. This paper presents the least strict admission control policy, which will induce the maximal throughput, for a two-tier system with parallel servers. We propose an optimization model to minimize the total number of virtual machines for computing resources in each tier by dynamically varying the mean service rate of the VMs. Some performance indicators and computational results showing the effect of model parameters are presented. This model is also applicable to priority as well as real-time based applications in Cloud based environment.

Decision Making Analysis of Video Streaming Algorithm for Private Cloud Computing Infrastructure

Syamsuddin¹,

Nur²,

Nirwana³

et al. 2017

The issue on how to effectively deliver video streaming contents over cloud computing infrastructures is tackled in this study. Basically, quality of service of video streaming is strongly influenced by bandwidth, jitter and data loss problems. A number of intelligent video streaming algorithms are proposed by using different techniques to deal with such issues. This study aims to propose and demonstrate a novel decision making analysis which combines ISO 9126 (international standard for software engineering) and Analytic Hierarchy Process to help experts selecting the best video streaming algorithm for the case of private cloud computing infrastructure. The given case study concluded that Scalable Streaming algorithm is the best algorithm to be implemented for delivering high quality of service of video streaming over the private cloud computing infrastructure.