Resource Scheduling Techniques in Cloud Computing Environment : A Survey

2018 ◽  
pp. 64-68
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey
Keyword(s):  
Cloud Computing ◽  
Time Management ◽  
Large Scale ◽  
Service Level Agreement ◽  
Service Level ◽  
Resource Provisioning ◽  
Network Access ◽  
Configurable Computing ◽  
Dynamic Resource Provisioning

Cloud Computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, applications and services) that can be rapidly provisioned and released. Resource Provisioning means the selection, deployment, and run-time management of software (e.g., database server management systems, load balancers) and hardware resources (e.g., CPU, storage, and network) for ensuring guaranteed performance for applications. Resource Provisioning is an important and challenging problem in the large-scale distributed systems such as Cloud computing environments. There are many resource provisioning techniques, both static and dynamic each one having its own advantages and also some challenges. These resource provisioning techniques used must meet Quality of Service (QoS) parameters like availability, throughput, response time, security, reliability etc., and thereby avoiding Service Level Agreement (SLA) violation. In this paper, survey on Static and Dynamic Resource Provisioning Techniques is made.

Examining of Data Security, Privacy, and Reliability for Cloud and Internet of Things Integration

2018 ◽  
pp. 57-90
Author(s):  
Marcus Tanque
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Security ◽  
Service Level Agreement ◽  
Service Level ◽  
Resource Provisioning ◽  
Security Issues ◽  
Support Organizations ◽  
Day To Day Operations

Converging Cloud computing with Internet of Things transformed organizations' traditional technologies. This chapter examines the intersection of cloud computing and internet of things in consort with how these solutions often interact on the internet. Vendors develop CloudIoT capabilities to support organizations' day-to-day operations. IoT is a combined platform encompassing physical and virtual nodes. IoT objects comprise device-to-device data sharing, machine-to-machine provisioning, sensors, actuators, and processors. These systems may be deployed as hardware components and applications software. This chapter also emphasizes data security, reliability, resource provisioning, service-level agreement, quality of service, IoT, privacy, and device integration. This chapter also highlights operational benefits and/or security issues affecting CC and IoT technologies.

scholarly journals Review of the quality of service scheduling mechanisms in cloud

2018 ◽  
Vol 7 (3) ◽  
pp. 1677 ◽  
Author(s):  
K R RemeshBabu ◽  
Philip Samuel
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Service Level Agreement ◽  
Scheduling Algorithms ◽  
Service Level ◽  
Future Research ◽  
Efficient Management ◽  
Future Research Directions ◽  
Scheduling Mechanisms

Cloud computing provides on demand access to a large pool of heterogeneous computational and storage resources to users over the internet. Optimal scheduling mechanisms are needed for the efficient management of these heterogeneous resources. The optimal scheduler can improve the Quality of Services (QoS) as well as maintaining efficiency and fairness among these tasks. In large scale distributed systems, the performance of these scheduling algorithms is crucial for better efficiency. Now the cloud customers are charged based upon the amount of resources they are consumed or held in reserve. Comparing these scheduling algorithms from different perspectives is needed for further improvement. This paper provides a comparative study about different resource allocation, load balancing and virtual machine consolidation algorithms in cloud computing. These algorithms have been evaluated in terms of their ability to provide QoS for the tasks and Service Level Agreement (SLA) guarantee amongst the jobs served. This study identifies current and future research directions in this area for QoS enabled cloud scheduling.  

Robust Multi-Dimensional Trust Computing Mechanism for Cloud Computing

2014 ◽  
Vol 69 (2) ◽  
Author(s):  
Mohamed Firdhous ◽  
Osman Ghazali ◽  
Suhaidi Hassan
Keyword(s):  
Cloud Computing ◽  
Service Level Agreement ◽  
Service Level ◽  
Resource Provisioning ◽  
The Internet ◽  
Cloud Systems ◽  
Multi Level ◽  
Multiple Qos ◽  
Trust Computing

Cloud computing has become the most promising way of purchasing computing resources over the Internet. The main advantage of .cloud computing is its economic advantages over the traditional computing resource provisioning. For cloud computing to become acceptable to wider audience, it is necessary to maintain the quality of service (QoS) commitments specified in the service level agreement. In this paper, the authors propose a robust multi-level trust computing mechanism that can be used to track the performance of cloud systems using multiple QoS attributes. In addition, tests carried out show that the proposed mechanism is more robust than the ones published in the literature.

scholarly journals Triangulation Resource Provisioning for Web Applications in Cloud Computing: A Profit-Aware Approach

2019 ◽  
Vol 20 (2) ◽  
pp. 207-222
Author(s):  
Parminder Singh ◽  
Pooja Gupta ◽  
Kiran Jyoti
Keyword(s):  
Web Applications ◽  
User Behavior ◽  
Service Level Agreement ◽  
Service Level ◽  
End Users ◽  
Resource Provisioning ◽  
Selection Policy ◽  
Dynamic Resource Provisioning ◽  
Resource Aware

The elasticity feature of cloud attracts the application providers to host the application in a cloud environment. The dynamic resource provisioning arranges the resources on-demand according to the application workload. The over-utilization and under-utilization of resources can be prevented with autonomic resource provisioning. In literature, the Service Level Agreement (SLA) based, load-aware, resource-aware and user-behavior aware solutions have been proposed. The solutions are rigid for a particular metric which provides benefit either to end users or to the application providers. In this article, we proposed a Triangulation Resource Provisioning (TRP) technique with a profit-aware surplus VM selection policy. This policy ensures the fair resource utilization in hourly billing cycle while giving the Quality of Service (QoS) to the end-users. The proposed technique used time series workload forecasting, CPU utilization and response time in the analysis phase. The experiment results show that the TRP resource provisioning technique is a profit-aware approach for the application providers and ensure the QoS to the end-users.

Optimal Management of Cloud Centers with Different Arrival Modes for Cloud Computing Environment

2012 ◽  
Vol 2 (3) ◽  
pp. 86-97
Author(s):  
Veena Goswami ◽  
Sudhansu Shekhar Patra ◽  
G. B. Mund
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Finite Buffer ◽  
Web Browser ◽  
Computing Paradigm ◽  
Computing Services ◽  
Multi Server

Cloud computing is a new computing paradigm in which information and computing services can be accessed from a Web browser by clients. Understanding of the characteristics of computer service performance has become critical for service applications in cloud computing. For the commercial success of this new computing paradigm, the ability to deliver guaranteed Quality of Services (QoS) is crucial. Based on the Service level agreement, the requests are processed in the cloud centers in different modes. This paper analyzes a finite-buffer multi-server queuing system where client requests have two arrival modes. It is assumed that each arrival mode is serviced by one or more Virtual machines, and both the modes have equal probabilities of receiving service. Various performance measures are obtained and optimal cost policy is presented with numerical results. The genetic algorithm is employed to search the optimal values of various parameters for the system.

scholarly journals Service Level Agreement Violation Preventive Task Scheduling for Quality of Service Delivery in Cloud Computing Environment

2020 ◽  
Vol 178 ◽  
pp. 375-385
Author(s):  
Ismail Zahraddeen Yakubu ◽  
Zainab Aliyu Musa ◽  
Lele Muhammed ◽  
Badamasi Ja’afaru ◽  
Fatima Shittu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Service Delivery ◽  
Task Scheduling ◽  
Service Level Agreement ◽  
Service Level ◽  
Computing Environment ◽  
Cloud Computing Environment

Dynamic Management of Resources in Cloud Computing

2020 ◽  
Vol 8 (1) ◽  
pp. 65-81 ◽  
Author(s):  
Pradeep Kumar Tiwari ◽  
Sandeep Joshi
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Service Level Agreement ◽  
Service Level ◽  
Poor Quality ◽  
Migration Time ◽  
Load Imbalance ◽  
Management Of Resources ◽  
And Migration

It has already been proven that VMs are over-utilized in the initial stages and are underutilized in the later stages. Due to the random utilization of the CPU, resources are sometimes heavily loaded whereas other resources are idle. Load imbalance causes service level agreement (SLA) violations resulting in poor quality of service (QoS) aided by the imperfect management of resources. An effective load balancing mechanism helps to achieve balanced utilization, which maximizes the throughput, availability, and reliability and reduces the response and migration time. The proposed algorithm can effectively minimize the response and the migration time and maximize reliability, and throughput. This research also helps to understand the load balancing policies and analysis of other research works.

scholarly journals Research on Cloud Computing Resources Provisioning Based on Reinforcement Learning

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Zhiping Peng ◽  
Delong Cui ◽  
Jinglong Zuo ◽  
Weiwei Lin
Keyword(s):  
Cloud Computing ◽  
Reinforcement Learning ◽  
Resource Management ◽  
Queuing Theory ◽  
Service Level Agreement ◽  
Service Level ◽  
Resource Provisioning ◽  
Utilization Rate ◽  
Sequential Decision ◽  
Distributed Resources

As one of the core issues for cloud computing, resource management adopts virtualization technology to shield the underlying resource heterogeneity and complexity which makes the massive distributed resources form a unified giant resource pool. It can achieve efficient resource provisioning by using the rational implementing resource management methods and techniques. Therefore, how to manage cloud computing resources effectively becomes a challenging research topic. By analyzing the executing progress of a user job in the cloud computing environment, we proposed a novel resource provisioning scheme based on the reinforcement learning and queuing theory in this study. With the introduction of the concepts of Segmentation Service Level Agreement (SSLA) and Utilization Unit Time Cost (UUTC), we viewed the resource provisioning problem in cloud computing as a sequential decision issue, and then we designed a novel optimization object function and employed reinforcement learning to solve it. Experiment results not only demonstrated the effectiveness of the proposed scheme, but also proved to outperform the common methods of resource utilization rate in terms of SLA collision avoidance and user costs.

Quality of Services and Optimal Management of Cloud Centers with Different Arrival Modes

2014 ◽  
pp. 185-198
Author(s):  
V. Goswami ◽  
S. S. Patra ◽  
G. B. Mund
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Quality Of Services ◽  
Finite Buffer ◽  
Optimal Management ◽  
It Industry ◽  
Computing Paradigm

In Cloud Computing, the virtualization of IT infrastructure enables consolidation and pooling of IT resources so they are shared over diverse applications to offset the limitation of shrinking resources and growing business needs. Cloud Computing is a way to increase the capacity or add capabilities dynamically without investing in new infrastructure, training new personnel, or licensing new software. It extends Information Technology's existing capabilities. In the last few years, cloud computing has grown from being a promising business concept to one of the fast growing segments of the IT industry. For the commercial success of this new computing paradigm, the ability to deliver guaranteed Quality of Services is crucial. Based on the Service Level Agreement, the requests are processed in the cloud centers in different modes. This chapter deals with Quality of Services and optimal management of cloud centers with different arrival modes. For this purpose, the authors consider a finite-buffer multi-server queuing system where client requests have different arrival modes. It is assumed that each arrival mode is serviced by one or more virtual machines, and different modes have equal probabilities of receiving services. Various performance measures are obtained and optimal cost policy is presented with numerical results. A genetic algorithm is employed to search optimal values of various parameters for the system.

Cloud Security Data Critical Review

2020 ◽  
Vol 17 (9) ◽  
pp. 4715-4717
Author(s):  
A. A. Prokin
Keyword(s):  
Cloud Computing ◽  
Mobile Communications ◽  
Critical Review ◽  
Network Architecture ◽  
Large Scale ◽  
Public Access ◽  
Network Access ◽  
Configurable Computing ◽  
On Demand ◽  
Suitable System

Cloud computing is a model for providing convenient network access on demand to some common fund of configurable computing resources. These calculations are flexible, scalable, and inexpensive, but have large-scale sharing of services among multiple users. The broad coverage of the idea of cloud computing has led to significant changes, both in public access systems and in mobile communications, which prompted advanced researchers to provide suitable system protocols and network architecture. In cloud computing, there are two main problems: access control and security. Therefore, the security of both services and users is a significant problem that stands in the way of using and trust in cloud computing.

Sign in / Sign up

Export Citation Format

Share Document