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

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.

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 852 ◽  
Author(s):  
Sajid Latif ◽  
Syed Mushhad Gilani ◽  
Rana Liaqat Ali ◽  
Misbah Liaqat ◽  
Kwang-Man Ko

The interconnected cloud (Intercloud) federation is an emerging paradigm that revolutionizes the scalable service provision of geographically distributed resources. Large-scale distributed resources require well-coordinated and automated frameworks to facilitate service provision in a seamless and systematic manner. Unquestionably, standalone service providers must communicate and federate their cloud sites with other vendors to enable the infinite pooling of resources. The pooling of these resources provides uninterpretable services to increasingly growing cloud users more efficiently, and ensures an improved Service Level Agreement (SLA). However, the research of Intercloud resource management is in its infancy. Therefore, standard interfaces, protocols, and uniform architectural components need to be developed for seamless interaction among federated clouds. In this study, we propose a distributed meta-brokering-enabled scheduling framework for provision of user application services in the federated cloud environment. Modularized architecture of the proposed system with uniform configuration in participating resource sites orchestrate the critical operations of resource management effectively, and form the federation schema. Overlaid meta-brokering instances are implemented on the top of local resource brokers to keep the global functionality isolated. These instances in overlay topology communicate in a P2P manner to maintain decentralization, high scalability, and load manageability. The proposed framework has been implemented and evaluated by extending the Java-based CloudSim 3.0.3 simulation application programming interfaces (APIs). The presented results validate the proposed model and its efficiency to facilitate user application execution with the desired QoS parameters.


Author(s):  
Marcus Tanque

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.


Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey

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.


2014 ◽  
Vol 69 (2) ◽  
Author(s):  
Mohamed Firdhous ◽  
Osman Ghazali ◽  
Suhaidi Hassan

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.


Author(s):  
Gurpreet Singh ◽  
Manish Mahajan ◽  
Rajni Mohana

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.


2017 ◽  
Vol 7 (1.5) ◽  
pp. 253
Author(s):  
N. Srinivasu ◽  
O. Sree Priyanka ◽  
M. Prudhvi ◽  
G. Meghana

Cloud Security was provided for the services such as storage, network, applications and software through internet. The Security was given at each layer (Saas, Paas, and Iaas), in each layer, there are some security threats which became the major problem in cloud computing. In Saas, the security issues are mainly present in Web Application services and this issue can be overcome by web application scanners and service level agreement(SLA). In Paas, the major problem is Data Transmission. During transmission of data, some data may be lost or modified. The PaaS environment accomplishes proficiency to some extent through duplication of information. The duplication of information makes high accessibility of information for engineers and clients. However, data is never fully deleted instead the pointers to the data are deleted. In order to overcome this problem the techniques that used are encryption[12], data backup. In Iaas the security threat that occurs in is virtualization and the techniques that are used to overcome the threats are Dynamic Security Provisioning(DSC), operational security procedure, for which Cloud Software is available in the market, for e.g. Eucalyptus, Nimbus 6.


2021 ◽  
Vol 17 (2) ◽  
pp. 179-195
Author(s):  
Priyanka Bharti ◽  
Rajeev Ranjan ◽  
Bhanu Prasad

Cloud computing provisions and allocates resources, in advance or real-time, to dynamic applications planned for execution. This is a challenging task as the Cloud-Service-Providers (CSPs) may not have sufficient resources at all times to satisfy the resource requests of the Cloud-Service-Users (CSUs). Further, the CSPs and CSUs have conflicting interests and may have different utilities. Service-Level-Agreement (SLA) negotiations among CSPs and CSUs can address these limitations. User Agents (UAs) negotiate for resources on behalf of the CSUs and help reduce the overall costs for the CSUs and enhance the resource utilization for the CSPs. This research proposes a broker-based mediation framework to optimize the SLA negotiation strategies between UAs and CSPs in Cloud environment. The impact of the proposed framework on utility, negotiation time, and request satisfaction are evaluated. The empirical results show that these strategies favor cooperative negotiation and achieve significantly higher utilities, higher satisfaction, and faster negotiation speed for all the entities involved in the negotiation.


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