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.

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.

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.

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.

scholarly journals Uncertainty Aware Resource Provisioning Framework for Cloud Using Expected 3-SARSA Learning Agent: NSS and FNSS Based Approach

2019 ◽  
Vol 19 (3) ◽  
pp. 94-117
Author(s):  
K. Bhargavi ◽  
B. Sathish Babu
Keyword(s):  
Quality Of Service ◽  
Service Level Agreement ◽  
Service Level ◽  
Resource Provisioning ◽  
Soft Set ◽  
Learning Agent ◽  
Optimal Resource ◽  
Auto Scaling ◽  
Heterogeneous Workloads

Abstract Efficiently provisioning the resources in a large computing domain like cloud is challenging due to uncertainty in resource demands and computation ability of the cloud resources. Inefficient provisioning of the resources leads to several issues in terms of the drop in Quality of Service (QoS), violation of Service Level Agreement (SLA), over-provisioning of resources, under-provisioning of resources and so on. The main objective of the paper is to formulate optimal resource provisioning policies by efficiently handling the uncertainties in the jobs and resources with the application of Neutrosophic Soft-Set (NSS) and Fuzzy Neutrosophic Soft-Set (FNSS). The performance of the proposed work compared to the existing fuzzy auto scaling work achieves the throughput of 80% with the learning rate of 75% on homogeneous and heterogeneous workloads by considering the RUBiS, RUBBoS, and Olio benchmark applications.

scholarly journals Priority-Based Virtual Machine Selection Algorithm in Cloud Computing

2019 ◽  
Vol 8 (3) ◽  
pp. 1457-1462
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Cloud Service Provider

Cloud computing technology has gained the attention of researchers in recent years. Almost every application is using cloud computing in one way or another. Virtualization allows running many virtual machines on a single physical computer by sharing its resources. Users can store their data on datacenter and run their applications from anywhere using the internet and pay as per service level agreement documents accordingly. It leads to an increase in demand for cloud services and may decrease the quality of service. This paper presents a priority-based selection of virtual machines by cloud service provider. The virtual machines in the cloud datacenter are configured as Amazon EC2 and algorithm is simulated in cloud-sim simulator. The results justify that proposed priority-based virtual machine algorithm shortens the makespan, by 11.43 % and 5.81 %, average waiting time by 28.80 % and 24.50%, and cost of using the virtual machine by 21.24% and 11.54% as compared to FCFS and ACO respectively, hence improving quality of service.

QoS-Oriented Service Computing

2011 ◽  
pp. 274-296 ◽  
Author(s):  
Dr. Xiaoyu Yang
Keyword(s):  
Cloud Computing ◽  
Service Provider ◽  
Computing Methodology ◽  
Service Level Agreement ◽  
Resource Provisioning ◽  
Reference Architecture ◽  
Service Computing ◽  
On Demand ◽  
Computing Paradigm

The idea of cloud computing aligns with new dimension emerging in service-oriented infrastructure where service provider does not own physical infrastructure but instead outsources to dedicated infrastructure providers. Cloud computing has now become a new computing paradigm as it can provide scalable IT infrastructure, QoS-assured services, and customizable computing environment. However, it still remains a challenging task to provide QoS assured services to serve customers with minimized cost, while also to guarantee the maximization of the business objectives (e.g. margin profit) to service provider and infrastructure provider within certain constraints. In order to address these issues, this chapter proposes a QoS-oriented service computing methodology, and discusses associated topics including service level agreement and associated reference architecture, green service, service metering and metrics, service monitoring, and on-demand resource provisioning. In the case study, we demonstrate how we employ QoS-oriented service computing in a multi-server, multi-user on-line game to facilitate the on-demand resource provisioning to maintain quality of service and quality of experience.

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